2025-07-31 12:27:21.559 | INFO     | yolox_microbt.core.trainer:before_train:88 - args: Namespace(config='configs.sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain', experiment_name='sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain', name=None, dist_backend='nccl', dist_url=None, batch_size=64, devices=8, exp_file=None, resume=False, ckpt='YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1/epoch_525_ckpt.pth', start_epoch=None, num_machines=1, machine_rank=0, fp16=False, cache=None, occupy=False, logger='tensorboard', opts=[])
2025-07-31 12:27:21.564 | INFO     | yolox_microbt.core.trainer:before_train:89 - exp value:
╒═══════════════════╤═════════════════════════════════════════════════════════════╕
│ keys              │ values                                                      │
╞═══════════════════╪═════════════════════════════════════════════════════════════╡
│ seed              │ None                                                        │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ output_dir        │ './YOLOX_outputs'                                           │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ print_interval    │ 20                                                          │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ eval_interval     │ 5                                                           │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ dataset           │ None                                                        │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ num_classes       │ 3                                                           │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ depth             │ 1.0                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ width             │ 1.0                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ act               │ 'silu'                                                      │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ data_num_workers  │ 2                                                           │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ input_size        │ (416, 416)                                                  │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ multiscale_range  │ 5                                                           │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ data_dir          │ None                                                        │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ train_ann         │ 'instances_train2017.json'                                  │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ val_ann           │ 'instances_val2017.json'                                    │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ test_ann          │ 'instances_test2017.json'                                   │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ mosaic_prob       │ 1.0                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ mixup_prob        │ 0.5                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ hsv_prob          │ 0.5                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ flip_prob         │ 0.5                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ degrees           │ 10.0                                                        │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ translate         │ 0.1                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ mosaic_scale      │ (0.1, 2)                                                    │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ enable_mixup      │ True                                                        │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ mixup_scale       │ (0.5, 1.5)                                                  │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ shear             │ 2.0                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ warmup_epochs     │ 5                                                           │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ max_epoch         │ 600                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ warmup_lr         │ 0                                                           │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ min_lr_ratio      │ 0.05                                                        │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ basic_lr_per_img  │ 0.00015625                                                  │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ scheduler         │ 'yoloxwarmcos'                                              │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ no_aug_epochs     │ 200                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ ema               │ False                                                       │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ weight_decay      │ 0.0005                                                      │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ momentum          │ 0.9                                                         │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ save_history_ckpt │ True                                                        │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ exp_name          │ 'sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain' │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ test_size         │ (416, 416)                                                  │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ test_conf         │ 0.01                                                        │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ nmsthre           │ 0.65                                                        │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ qat_warmup_epoch  │ -1                                                          │
├───────────────────┼─────────────────────────────────────────────────────────────┤
│ qat_clib_epoch    │ 1                                                           │
╘═══════════════════╧═════════════════════════════════════════════════════════════╛
2025-07-31 12:27:21.620 | INFO     | yolox_microbt.core.trainer:resume_train:325 - loading checkpoint for fine tuning
2025-07-31 12:27:22.380 | INFO     | yolox_microbt.core.trainer:before_train:129 - init prefetcher, this might take one minute or less...
2025-07-31 12:27:25.596 | INFO     | yolox_microbt.core.trainer:before_train:168 - Training start...
2025-07-31 12:27:25.598 | INFO     | yolox_microbt.core.trainer:before_train:169 - 
DistributedDataParallel(
  (module): YOLOXTrainer(
    (yolox): YOLOXDetector(
      (backbone0): MBNetV2Backbone(
        (backbone): Sequential(
          (0): Sequential(
            (0): ConvBnAct(
              (conv): Conv2d(3, 8, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
              (bn): BatchNorm2d(8, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act): ReLU()
            )
          )
          (1): Sequential(
            (0): DepthwiseSeparableConv(
              (conv_dw): Conv2d(8, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=8, bias=False)
              (bn1): BatchNorm2d(8, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_pw): Conv2d(8, 10, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn2): BatchNorm2d(10, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (2): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(10, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(40, 40, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=40, bias=False)
              (bn2): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(40, 8, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(8, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
            (1): InvertedResidual(
              (conv_pw): Conv2d(8, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(32, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=32, bias=False)
              (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(32, 8, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(8, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (3): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(8, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(32, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(32, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=32, bias=False)
              (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(32, 10, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(10, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
            (1): InvertedResidual(
              (conv_pw): Conv2d(10, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(40, 40, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=40, bias=False)
              (bn2): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(40, 10, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(10, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (4): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(10, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(40, 40, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=40, bias=False)
              (bn2): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(40, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(16, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
            (1): InvertedResidual(
              (conv_pw): Conv2d(16, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64, bias=False)
              (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(64, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(16, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
            (2): InvertedResidual(
              (conv_pw): Conv2d(16, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64, bias=False)
              (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(64, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(16, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (5): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(16, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64, bias=False)
              (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(64, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(48, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (6): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(48, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(192, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(192, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=192, bias=False)
              (bn2): BatchNorm2d(192, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(192, 52, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(52, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (7): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(52, 208, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(208, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(208, 208, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=208, bias=False)
              (bn2): BatchNorm2d(208, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(208, 88, kernel_size=(1, 1), stride=(1, 1), groups=2, bias=False)
              (bn3): BatchNorm2d(88, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
            (1): InvertedResidual(
              (conv_pw): Conv2d(88, 352, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(352, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(352, 352, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=352, bias=False)
              (bn2): BatchNorm2d(352, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(352, 88, kernel_size=(1, 1), stride=(1, 1), groups=2, bias=False)
              (bn3): BatchNorm2d(88, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (8): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(88, 352, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(352, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(352, 352, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=352, bias=False)
              (bn2): BatchNorm2d(352, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(352, 144, kernel_size=(1, 1), stride=(1, 1), groups=2, bias=False)
              (bn3): BatchNorm2d(144, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
        )
      )
      (head0): YOLOXHead(
        (shared_layer_8): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(10, 64, kernel_size=(1, 1), stride=(1, 1))
            (act0): ReLU()
          )
          (conv1): ConvBlock(
            (conv0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64)
            (act0): ReLU()
          )
          (conv2): ConvBlock(
            (conv0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))
            (act0): ReLU()
          )
        )
        (layer_8_obj): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 1, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (layer_8_cls): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 3, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (layer_8_box): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 4, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (shared_layer_16): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(52, 64, kernel_size=(1, 1), stride=(1, 1))
            (act0): ReLU()
          )
          (conv1): ConvBlock(
            (conv0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64)
            (act0): ReLU()
          )
          (conv2): ConvBlock(
            (conv0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))
            (act0): ReLU()
          )
        )
        (layer_16_obj): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 1, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (layer_16_cls): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 3, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (layer_16_box): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 4, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (shared_layer_32): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(144, 64, kernel_size=(1, 1), stride=(1, 1))
            (act0): ReLU()
          )
          (conv1): ConvBlock(
            (conv0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64)
            (act0): ReLU()
          )
          (conv2): ConvBlock(
            (conv0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))
            (act0): ReLU()
          )
        )
        (layer_32_obj): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 1, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (layer_32_cls): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 3, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (layer_32_box): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 4, kernel_size=(1, 1), stride=(1, 1))
          )
        )
      )
    )
    (loss): YOLOXLoss(
      (l1_loss): L1Loss()
      (bcewithlog_loss): BCEWithLogitsLoss()
      (iou_loss): IOUloss()
    )
  )
)
2025-07-31 12:27:25.599 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch1
2025-07-31 12:27:25.600 | INFO     | yolox_microbt.core.trainer:before_epoch:204 - --->enable mosaic aug for quantization training!
2025-07-31 12:27:29.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 20/129, gpu mem: 1051Mb, mem: 76.0Gb, iter_time: 0.215s, data_time: 0.004s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.615e-06, size: 512, ETA: 4:37:09
2025-07-31 12:27:32.754 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 40/129, gpu mem: 1051Mb, mem: 76.0Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 3.846e-05, size: 288, ETA: 3:48:03
2025-07-31 12:27:35.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 60/129, gpu mem: 1051Mb, mem: 76.1Gb, iter_time: 0.144s, data_time: 0.015s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.653e-05, size: 256, ETA: 3:33:42
2025-07-31 12:27:38.822 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 80/129, gpu mem: 1051Mb, mem: 76.0Gb, iter_time: 0.147s, data_time: 0.004s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.2, lr: 1.538e-04, size: 448, ETA: 3:27:40
2025-07-31 12:27:41.779 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 100/129, gpu mem: 1051Mb, mem: 76.0Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.404e-04, size: 256, ETA: 3:21:13
2025-07-31 12:27:44.687 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 120/129, gpu mem: 1603Mb, mem: 76.0Gb, iter_time: 0.144s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 3.461e-04, size: 544, ETA: 3:18:28
2025-07-31 12:27:45.984 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:27:46.082 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch2
2025-07-31 12:27:49.000 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 20/129, gpu mem: 1603Mb, mem: 76.0Gb, iter_time: 0.138s, data_time: 0.014s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.336e-04, size: 480, ETA: 3:14:40
2025-07-31 12:27:51.985 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.138s, data_time: 0.008s, total_loss: 6.7, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.865e-04, size: 288, ETA: 3:12:35
2025-07-31 12:27:54.947 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.3, lr: 8.586e-04, size: 288, ETA: 3:10:27
2025-07-31 12:27:57.947 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 1.050e-03, size: 256, ETA: 3:08:49
2025-07-31 12:28:00.863 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.261e-03, size: 576, ETA: 3:07:16
2025-07-31 12:28:03.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.490e-03, size: 416, ETA: 3:05:56
2025-07-31 12:28:05.215 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:28:05.255 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch3
2025-07-31 12:28:08.124 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.135s, data_time: 0.023s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 1.858e-03, size: 416, ETA: 3:04:55
2025-07-31 12:28:11.013 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 2.135e-03, size: 512, ETA: 3:04:31
2025-07-31 12:28:13.974 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.147s, data_time: 0.065s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 2.431e-03, size: 512, ETA: 3:04:45
2025-07-31 12:28:16.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.138s, data_time: 0.050s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.746e-03, size: 288, ETA: 3:04:17
2025-07-31 12:28:19.738 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.136s, data_time: 0.033s, total_loss: 7.7, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 3.081e-03, size: 256, ETA: 3:03:41
2025-07-31 12:28:22.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.138s, data_time: 0.006s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 3.435e-03, size: 416, ETA: 3:03:16
2025-07-31 12:28:23.863 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:28:23.905 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch4
2025-07-31 12:28:26.784 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.128s, data_time: 0.016s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 3.982e-03, size: 320, ETA: 3:02:19
2025-07-31 12:28:29.651 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.135s, data_time: 0.041s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 4.383e-03, size: 384, ETA: 3:01:52
2025-07-31 12:28:32.593 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.134s, data_time: 0.011s, total_loss: 7.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 4.803e-03, size: 256, ETA: 3:01:21
2025-07-31 12:28:35.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 5.242e-03, size: 448, ETA: 3:00:48
2025-07-31 12:28:38.453 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 5.701e-03, size: 384, ETA: 3:00:11
2025-07-31 12:28:41.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 6.179e-03, size: 576, ETA: 2:59:55
2025-07-31 12:28:42.763 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:28:42.889 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch5
2025-07-31 12:28:45.759 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 6.906e-03, size: 256, ETA: 2:58:51
2025-07-31 12:28:48.709 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.127s, data_time: 0.010s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.431e-03, size: 320, ETA: 2:58:13
2025-07-31 12:28:51.627 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.132s, data_time: 0.036s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.975e-03, size: 416, ETA: 2:57:53
2025-07-31 12:28:54.484 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 8.538e-03, size: 448, ETA: 2:57:33
2025-07-31 12:28:57.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.136s, data_time: 0.033s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.121e-03, size: 448, ETA: 2:57:22
2025-07-31 12:29:00.336 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.0Gb, iter_time: 0.145s, data_time: 0.014s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.723e-03, size: 448, ETA: 2:57:35
2025-07-31 12:29:01.602 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:29:08.015 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:29:10.934 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:29:12.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3533
2025-07-31 12:29:13.052 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3129
2025-07-31 12:29:13.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2028
2025-07-31 12:29:13.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2897
2025-07-31 12:29:13.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:29:13.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:29:13.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.353
2025-07-31 12:29:13.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.313
2025-07-31 12:29:13.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.203
2025-07-31 12:29:13.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.290
2025-07-31 12:29:13.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:29:13.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:29:13.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:29:13.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:29:13.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:29:13.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:29:13.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:29:13.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:29:13.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:29:15.440 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:29:17.622 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:29:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:29:21.961 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:29:24.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:29:26.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:29:28.504 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:29:30.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:29:32.974 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:29:32.974 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.14
2025-07-31 12:29:32.974 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.29
2025-07-31 12:29:32.974 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:29:33.006 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 0.98 ms, Average inference time: 2.45 ms

2025-07-31 12:29:33.008 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:29:33.037 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:29:33.071 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch6
2025-07-31 12:29:35.555 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.114s, data_time: 0.017s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 1.000e-02, size: 320, ETA: 2:56:35
2025-07-31 12:29:38.492 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.139s, data_time: 0.010s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.000e-02, size: 448, ETA: 2:56:33
2025-07-31 12:29:41.390 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 1.000e-02, size: 352, ETA: 2:56:21
2025-07-31 12:29:44.374 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.000e-02, size: 352, ETA: 2:56:24
2025-07-31 12:29:47.296 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.1, lr: 1.000e-02, size: 576, ETA: 2:56:18
2025-07-31 12:29:50.327 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 1.000e-02, size: 480, ETA: 2:56:26
2025-07-31 12:29:51.542 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:29:51.588 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch7
2025-07-31 12:29:54.426 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.130s, data_time: 0.026s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.000e-02, size: 416, ETA: 2:56:01
2025-07-31 12:29:57.298 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.000e-02, size: 512, ETA: 2:55:40
2025-07-31 12:30:00.129 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.139s, data_time: 0.007s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 1.000e-02, size: 288, ETA: 2:55:39
2025-07-31 12:30:03.063 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.129s, data_time: 0.011s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 1.000e-02, size: 352, ETA: 2:55:21
2025-07-31 12:30:05.955 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.138s, data_time: 0.019s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 1.000e-02, size: 448, ETA: 2:55:20
2025-07-31 12:30:08.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.138s, data_time: 0.043s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.999e-03, size: 576, ETA: 2:55:18
2025-07-31 12:30:10.136 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:30:10.176 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch8
2025-07-31 12:30:13.001 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.134s, data_time: 0.033s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.999e-03, size: 288, ETA: 2:55:17
2025-07-31 12:30:15.910 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.143s, data_time: 0.037s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.999e-03, size: 416, ETA: 2:55:22
2025-07-31 12:30:18.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.141s, data_time: 0.042s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.999e-03, size: 320, ETA: 2:55:24
2025-07-31 12:30:21.696 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.145s, data_time: 0.055s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.999e-03, size: 576, ETA: 2:55:33
2025-07-31 12:30:24.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.149s, data_time: 0.060s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 9.999e-03, size: 384, ETA: 2:55:48
2025-07-31 12:30:27.586 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.999e-03, size: 576, ETA: 2:55:53
2025-07-31 12:30:28.890 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:30:28.934 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch9
2025-07-31 12:30:31.754 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.135s, data_time: 0.019s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.999e-03, size: 544, ETA: 2:55:46
2025-07-31 12:30:34.602 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 9.998e-03, size: 320, ETA: 2:55:43
2025-07-31 12:30:37.478 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.023s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.998e-03, size: 544, ETA: 2:55:38
2025-07-31 12:30:40.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.125s, data_time: 0.018s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.998e-03, size: 416, ETA: 2:55:18
2025-07-31 12:30:43.248 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.142s, data_time: 0.047s, total_loss: 7.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.998e-03, size: 256, ETA: 2:55:21
2025-07-31 12:30:46.349 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.154s, data_time: 0.069s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 9.998e-03, size: 384, ETA: 2:55:39
2025-07-31 12:30:47.672 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:30:47.718 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch10
2025-07-31 12:30:50.598 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.142s, data_time: 0.050s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.997e-03, size: 256, ETA: 2:55:45
2025-07-31 12:30:53.474 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.055s, total_loss: 8.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.997e-03, size: 352, ETA: 2:55:48
2025-07-31 12:30:56.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.146s, data_time: 0.054s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 9.997e-03, size: 576, ETA: 2:55:54
2025-07-31 12:30:59.257 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.139s, data_time: 0.051s, total_loss: 6.5, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.997e-03, size: 352, ETA: 2:55:52
2025-07-31 12:31:02.125 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.137s, data_time: 0.046s, total_loss: 7.6, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.997e-03, size: 320, ETA: 2:55:48
2025-07-31 12:31:05.012 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.008s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 9.996e-03, size: 576, ETA: 2:55:41
2025-07-31 12:31:06.339 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:31:12.792 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:31:15.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:31:17.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4574
2025-07-31 12:31:17.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3922
2025-07-31 12:31:18.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1998
2025-07-31 12:31:18.060 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3498
2025-07-31 12:31:18.060 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.457
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.392
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.200
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.350
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:31:18.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:31:18.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:31:18.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:31:20.451 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:31:22.758 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:31:25.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:31:27.454 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:31:29.720 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:31:32.057 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:31:34.343 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:31:36.652 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:31:38.986 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:31:38.987 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.14
2025-07-31 12:31:38.987 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.35
2025-07-31 12:31:38.987 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:31:39.016 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.99 ms, Average inference time: 2.38 ms

2025-07-31 12:31:39.017 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:31:39.049 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:31:39.085 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch11
2025-07-31 12:31:41.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.129s, data_time: 0.044s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.996e-03, size: 544, ETA: 2:55:24
2025-07-31 12:31:44.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.148s, data_time: 0.061s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.996e-03, size: 352, ETA: 2:55:32
2025-07-31 12:31:47.587 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.996e-03, size: 576, ETA: 2:55:32
2025-07-31 12:31:50.537 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.146s, data_time: 0.058s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.995e-03, size: 352, ETA: 2:55:37
2025-07-31 12:31:53.430 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.057s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.995e-03, size: 288, ETA: 2:55:40
2025-07-31 12:31:56.339 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.144s, data_time: 0.058s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.995e-03, size: 480, ETA: 2:55:43
2025-07-31 12:31:57.649 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:31:57.694 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch12
2025-07-31 12:32:00.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.138s, data_time: 0.034s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.994e-03, size: 416, ETA: 2:55:41
2025-07-31 12:32:03.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.139s, data_time: 0.023s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 9.994e-03, size: 480, ETA: 2:55:39
2025-07-31 12:32:06.331 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.128s, data_time: 0.004s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 9.994e-03, size: 416, ETA: 2:55:25
2025-07-31 12:32:09.231 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 9.993e-03, size: 512, ETA: 2:55:18
2025-07-31 12:32:12.137 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.126s, data_time: 0.007s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.3, lr: 9.993e-03, size: 320, ETA: 2:55:03
2025-07-31 12:32:15.171 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.003s, total_loss: 6.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.993e-03, size: 384, ETA: 2:55:05
2025-07-31 12:32:16.406 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:32:16.471 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch13
2025-07-31 12:32:19.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.143s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.992e-03, size: 480, ETA: 2:55:04
2025-07-31 12:32:22.158 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.005s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.992e-03, size: 448, ETA: 2:54:58
2025-07-31 12:32:25.130 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.141s, data_time: 0.013s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.992e-03, size: 320, ETA: 2:54:57
2025-07-31 12:32:27.989 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.991e-03, size: 384, ETA: 2:54:47
2025-07-31 12:32:30.916 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.013s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.991e-03, size: 448, ETA: 2:54:38
2025-07-31 12:32:33.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.129s, data_time: 0.013s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 9.991e-03, size: 576, ETA: 2:54:27
2025-07-31 12:32:35.027 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:32:35.066 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch14
2025-07-31 12:32:38.014 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.039s, total_loss: 5.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 9.990e-03, size: 544, ETA: 2:54:17
2025-07-31 12:32:40.802 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.013s, total_loss: 8.7, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 9.990e-03, size: 384, ETA: 2:54:10
2025-07-31 12:32:43.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.010s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.989e-03, size: 512, ETA: 2:54:03
2025-07-31 12:32:46.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.010s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.989e-03, size: 480, ETA: 2:53:54
2025-07-31 12:32:49.606 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.988e-03, size: 384, ETA: 2:53:49
2025-07-31 12:32:52.474 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 7.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.988e-03, size: 576, ETA: 2:53:42
2025-07-31 12:32:53.672 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:32:53.824 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch15
2025-07-31 12:32:56.685 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.123s, data_time: 0.016s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.987e-03, size: 480, ETA: 2:53:18
2025-07-31 12:32:59.596 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.127s, data_time: 0.032s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.987e-03, size: 320, ETA: 2:53:07
2025-07-31 12:33:02.566 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.024s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.987e-03, size: 480, ETA: 2:53:03
2025-07-31 12:33:05.424 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.141s, data_time: 0.055s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.986e-03, size: 448, ETA: 2:53:04
2025-07-31 12:33:08.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.130s, data_time: 0.040s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.3, lr: 9.986e-03, size: 256, ETA: 2:52:55
2025-07-31 12:33:11.248 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.128s, data_time: 0.026s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.985e-03, size: 288, ETA: 2:52:45
2025-07-31 12:33:12.508 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:33:19.027 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:33:21.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:33:23.751 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4794
2025-07-31 12:33:24.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3480
2025-07-31 12:33:24.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2591
2025-07-31 12:33:24.156 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3622
2025-07-31 12:33:24.156 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:33:24.156 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:33:24.156 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.479
2025-07-31 12:33:24.156 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.348
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.259
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.362
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:33:24.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:33:24.158 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:33:26.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:33:28.771 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:33:31.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:33:33.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:33:35.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:33:38.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:33:40.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:33:42.682 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:33:45.005 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:33:45.005 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.13
2025-07-31 12:33:45.006 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-31 12:33:45.006 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:33:45.031 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.99 ms, Average inference time: 2.41 ms

2025-07-31 12:33:45.032 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:33:45.062 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:33:45.095 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch16
2025-07-31 12:33:47.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.121s, data_time: 0.037s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.985e-03, size: 256, ETA: 2:52:27
2025-07-31 12:33:50.536 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.145s, data_time: 0.057s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 9.984e-03, size: 320, ETA: 2:52:30
2025-07-31 12:33:53.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.022s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.984e-03, size: 544, ETA: 2:52:24
2025-07-31 12:33:56.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.016s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.983e-03, size: 416, ETA: 2:52:20
2025-07-31 12:33:59.121 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.043s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.983e-03, size: 256, ETA: 2:52:17
2025-07-31 12:34:02.067 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.139s, data_time: 0.044s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.982e-03, size: 448, ETA: 2:52:16
2025-07-31 12:34:03.293 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:34:03.452 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch17
2025-07-31 12:34:06.303 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.024s, total_loss: 7.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.981e-03, size: 448, ETA: 2:52:03
2025-07-31 12:34:09.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.1Gb, iter_time: 0.141s, data_time: 0.044s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 9.981e-03, size: 480, ETA: 2:52:03
2025-07-31 12:34:12.053 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.132s, data_time: 0.038s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.980e-03, size: 384, ETA: 2:51:57
2025-07-31 12:34:14.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.029s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.980e-03, size: 448, ETA: 2:51:52
2025-07-31 12:34:17.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.036s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.979e-03, size: 512, ETA: 2:51:47
2025-07-31 12:34:20.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.132s, data_time: 0.046s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.979e-03, size: 512, ETA: 2:51:41
2025-07-31 12:34:22.063 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:34:22.103 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch18
2025-07-31 12:34:24.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.128s, data_time: 0.029s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.978e-03, size: 512, ETA: 2:51:30
2025-07-31 12:34:27.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.977e-03, size: 512, ETA: 2:51:27
2025-07-31 12:34:30.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.977e-03, size: 256, ETA: 2:51:18
2025-07-31 12:34:33.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.976e-03, size: 416, ETA: 2:51:15
2025-07-31 12:34:36.663 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.139s, data_time: 0.011s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.976e-03, size: 320, ETA: 2:51:13
2025-07-31 12:34:39.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 8.9, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 9.975e-03, size: 320, ETA: 2:51:07
2025-07-31 12:34:40.867 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:34:40.991 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch19
2025-07-31 12:34:43.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.974e-03, size: 544, ETA: 2:50:56
2025-07-31 12:34:46.930 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.007s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.973e-03, size: 416, ETA: 2:50:51
2025-07-31 12:34:49.732 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.126s, data_time: 0.004s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.973e-03, size: 384, ETA: 2:50:42
2025-07-31 12:34:52.569 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.125s, data_time: 0.006s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.972e-03, size: 352, ETA: 2:50:32
2025-07-31 12:34:55.435 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 9.972e-03, size: 256, ETA: 2:50:29
2025-07-31 12:34:58.348 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.011s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.971e-03, size: 512, ETA: 2:50:26
2025-07-31 12:34:59.581 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:34:59.628 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch20
2025-07-31 12:35:02.691 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.141s, data_time: 0.007s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.970e-03, size: 256, ETA: 2:50:20
2025-07-31 12:35:05.606 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.004s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.969e-03, size: 576, ETA: 2:50:16
2025-07-31 12:35:08.597 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.969e-03, size: 448, ETA: 2:50:14
2025-07-31 12:35:11.562 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.008s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.968e-03, size: 320, ETA: 2:50:11
2025-07-31 12:35:14.389 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.127s, data_time: 0.033s, total_loss: 7.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.967e-03, size: 256, ETA: 2:50:03
2025-07-31 12:35:17.388 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.144s, data_time: 0.058s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.967e-03, size: 512, ETA: 2:50:04
2025-07-31 12:35:18.620 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:35:25.012 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:35:27.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:35:28.847 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4818
2025-07-31 12:35:29.049 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3759
2025-07-31 12:35:29.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2327
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3635
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.482
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.376
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.233
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.363
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:35:29.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:35:29.102 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:35:29.102 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:35:29.102 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:35:29.102 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:35:29.102 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:35:29.102 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:35:30.975 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:35:32.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:35:34.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:35:36.592 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:35:38.442 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:35:40.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:35:42.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:35:44.086 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:35:45.943 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:35:45.943 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-07-31 12:35:45.943 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-31 12:35:45.943 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:35:45.968 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 0.97 ms, Average inference time: 2.41 ms

2025-07-31 12:35:45.970 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:35:45.998 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:35:46.033 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch21
2025-07-31 12:35:48.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.046s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.966e-03, size: 352, ETA: 2:49:57
2025-07-31 12:35:51.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.140s, data_time: 0.052s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 9.965e-03, size: 256, ETA: 2:49:56
2025-07-31 12:35:54.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.141s, data_time: 0.038s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 9.964e-03, size: 416, ETA: 2:49:56
2025-07-31 12:35:57.449 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.028s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.963e-03, size: 256, ETA: 2:49:53
2025-07-31 12:36:00.458 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.019s, total_loss: 8.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.963e-03, size: 544, ETA: 2:49:51
2025-07-31 12:36:03.419 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 9.962e-03, size: 352, ETA: 2:49:47
2025-07-31 12:36:04.703 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:36:04.760 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch22
2025-07-31 12:36:07.625 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.961e-03, size: 416, ETA: 2:49:43
2025-07-31 12:36:10.541 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.017s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.960e-03, size: 480, ETA: 2:49:40
2025-07-31 12:36:13.511 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.959e-03, size: 448, ETA: 2:49:37
2025-07-31 12:36:16.374 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 9.959e-03, size: 320, ETA: 2:49:33
2025-07-31 12:36:19.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.958e-03, size: 448, ETA: 2:49:29
2025-07-31 12:36:22.141 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.025s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 9.957e-03, size: 320, ETA: 2:49:23
2025-07-31 12:36:23.472 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:36:23.509 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch23
2025-07-31 12:36:26.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.956e-03, size: 576, ETA: 2:49:24
2025-07-31 12:36:29.295 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.141s, data_time: 0.004s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.955e-03, size: 480, ETA: 2:49:24
2025-07-31 12:36:32.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.145s, data_time: 0.003s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.954e-03, size: 576, ETA: 2:49:25
2025-07-31 12:36:35.175 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.953e-03, size: 576, ETA: 2:49:28
2025-07-31 12:36:38.013 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.004s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 9.953e-03, size: 544, ETA: 2:49:26
2025-07-31 12:36:40.885 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.952e-03, size: 384, ETA: 2:49:25
2025-07-31 12:36:42.163 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:36:42.364 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch24
2025-07-31 12:36:45.237 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 8.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 9.951e-03, size: 416, ETA: 2:49:21
2025-07-31 12:36:48.126 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.950e-03, size: 256, ETA: 2:49:17
2025-07-31 12:36:51.046 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.949e-03, size: 544, ETA: 2:49:15
2025-07-31 12:36:53.956 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.948e-03, size: 320, ETA: 2:49:12
2025-07-31 12:36:56.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.3, lr: 9.947e-03, size: 352, ETA: 2:49:09
2025-07-31 12:36:59.738 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.138s, data_time: 0.027s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.946e-03, size: 320, ETA: 2:49:07
2025-07-31 12:37:00.989 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:37:01.074 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch25
2025-07-31 12:37:03.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 9.945e-03, size: 480, ETA: 2:49:00
2025-07-31 12:37:06.889 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.944e-03, size: 352, ETA: 2:48:59
2025-07-31 12:37:09.801 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.138s, data_time: 0.006s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.943e-03, size: 384, ETA: 2:48:57
2025-07-31 12:37:12.709 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.942e-03, size: 384, ETA: 2:48:49
2025-07-31 12:37:15.583 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.941e-03, size: 352, ETA: 2:48:41
2025-07-31 12:37:18.451 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.124s, data_time: 0.007s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 9.940e-03, size: 288, ETA: 2:48:33
2025-07-31 12:37:19.678 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:37:26.036 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:37:27.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:37:28.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4988
2025-07-31 12:37:28.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4119
2025-07-31 12:37:28.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2707
2025-07-31 12:37:28.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3938
2025-07-31 12:37:28.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:37:28.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:37:28.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.499
2025-07-31 12:37:28.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.412
2025-07-31 12:37:28.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.271
2025-07-31 12:37:28.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.394
2025-07-31 12:37:28.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:37:28.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:37:28.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:37:28.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:37:28.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:37:28.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:37:28.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:37:28.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:37:28.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:37:29.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:37:30.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:37:31.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:37:32.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:37:33.482 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:37:34.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:37:35.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:37:36.542 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:37:37.570 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:37:37.570 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-07-31 12:37:37.570 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-31 12:37:37.570 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:37:37.577 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.96 ms, Average inference time: 2.36 ms

2025-07-31 12:37:37.579 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:37:37.603 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:37:37.634 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch26
2025-07-31 12:37:40.234 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.129s, data_time: 0.042s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.939e-03, size: 352, ETA: 2:48:22
2025-07-31 12:37:43.113 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.045s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 9.938e-03, size: 448, ETA: 2:48:19
2025-07-31 12:37:46.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.138s, data_time: 0.014s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.937e-03, size: 320, ETA: 2:48:17
2025-07-31 12:37:49.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.936e-03, size: 512, ETA: 2:48:15
2025-07-31 12:37:51.822 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.935e-03, size: 448, ETA: 2:48:11
2025-07-31 12:37:54.888 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.003s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 9.934e-03, size: 448, ETA: 2:48:11
2025-07-31 12:37:56.195 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:37:56.233 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch27
2025-07-31 12:37:59.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 9.933e-03, size: 288, ETA: 2:48:10
2025-07-31 12:38:02.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.146s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 9.932e-03, size: 512, ETA: 2:48:12
2025-07-31 12:38:04.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.037s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.931e-03, size: 352, ETA: 2:48:12
2025-07-31 12:38:07.933 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.147s, data_time: 0.031s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 9.930e-03, size: 384, ETA: 2:48:14
2025-07-31 12:38:10.851 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.007s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.929e-03, size: 576, ETA: 2:48:14
2025-07-31 12:38:13.716 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.042s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 9.928e-03, size: 448, ETA: 2:48:11
2025-07-31 12:38:15.025 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:38:15.106 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch28
2025-07-31 12:38:18.013 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.012s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.926e-03, size: 416, ETA: 2:48:07
2025-07-31 12:38:20.830 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.132s, data_time: 0.033s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.925e-03, size: 416, ETA: 2:48:03
2025-07-31 12:38:23.631 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.021s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 9.924e-03, size: 384, ETA: 2:47:59
2025-07-31 12:38:26.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.144s, data_time: 0.028s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.923e-03, size: 480, ETA: 2:48:00
2025-07-31 12:38:29.594 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.922e-03, size: 576, ETA: 2:47:58
2025-07-31 12:38:32.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.140s, data_time: 0.040s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.921e-03, size: 352, ETA: 2:47:57
2025-07-31 12:38:33.763 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:38:33.802 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch29
2025-07-31 12:38:36.796 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.149s, data_time: 0.064s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 9.920e-03, size: 352, ETA: 2:47:58
2025-07-31 12:38:39.597 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.919e-03, size: 544, ETA: 2:47:56
2025-07-31 12:38:42.595 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.148s, data_time: 0.018s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.918e-03, size: 576, ETA: 2:47:57
2025-07-31 12:38:45.427 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.139s, data_time: 0.013s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.916e-03, size: 544, ETA: 2:47:56
2025-07-31 12:38:48.301 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.139s, data_time: 0.009s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 9.915e-03, size: 576, ETA: 2:47:54
2025-07-31 12:38:51.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.914e-03, size: 416, ETA: 2:47:51
2025-07-31 12:38:52.602 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:38:52.690 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch30
2025-07-31 12:38:55.574 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.913e-03, size: 352, ETA: 2:47:48
2025-07-31 12:38:58.441 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.013s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.911e-03, size: 544, ETA: 2:47:46
2025-07-31 12:39:01.301 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.139s, data_time: 0.038s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.910e-03, size: 256, ETA: 2:47:44
2025-07-31 12:39:04.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.132s, data_time: 0.038s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.909e-03, size: 320, ETA: 2:47:40
2025-07-31 12:39:06.948 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.048s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.908e-03, size: 256, ETA: 2:47:36
2025-07-31 12:39:09.876 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.050s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.907e-03, size: 416, ETA: 2:47:36
2025-07-31 12:39:11.253 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:39:17.687 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:39:19.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:39:20.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4885
2025-07-31 12:39:20.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3045
2025-07-31 12:39:20.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2773
2025-07-31 12:39:20.854 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3568
2025-07-31 12:39:20.855 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:39:20.855 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:39:20.856 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.489
2025-07-31 12:39:20.856 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.305
2025-07-31 12:39:20.856 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.277
2025-07-31 12:39:20.857 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.357
2025-07-31 12:39:20.857 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:39:20.858 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:39:20.858 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:39:20.858 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:39:20.859 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:39:20.859 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:39:20.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:39:20.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:39:20.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:39:22.296 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:39:23.634 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:39:25.005 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:39:26.394 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:39:27.747 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:39:29.071 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:39:30.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:39:31.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:39:33.214 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:39:33.214 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.13
2025-07-31 12:39:33.214 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-31 12:39:33.214 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:39:33.224 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.95 ms, Average inference time: 2.37 ms

2025-07-31 12:39:33.224 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:39:33.246 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:39:33.278 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch31
2025-07-31 12:39:35.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.120s, data_time: 0.032s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.1, lr: 9.905e-03, size: 288, ETA: 2:47:24
2025-07-31 12:39:38.750 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.036s, total_loss: 8.9, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 0.8, lr: 9.904e-03, size: 576, ETA: 2:47:22
2025-07-31 12:39:41.663 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.024s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.903e-03, size: 512, ETA: 2:47:18
2025-07-31 12:39:44.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.141s, data_time: 0.031s, total_loss: 7.3, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.902e-03, size: 288, ETA: 2:47:17
2025-07-31 12:39:47.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.040s, total_loss: 7.7, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.901e-03, size: 256, ETA: 2:47:15
2025-07-31 12:39:50.358 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.146s, data_time: 0.044s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.899e-03, size: 352, ETA: 2:47:15
2025-07-31 12:39:51.587 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:39:51.659 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch32
2025-07-31 12:39:54.540 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.143s, data_time: 0.051s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.898e-03, size: 384, ETA: 2:47:13
2025-07-31 12:39:57.406 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.140s, data_time: 0.056s, total_loss: 6.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.896e-03, size: 256, ETA: 2:47:12
2025-07-31 12:40:00.373 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.009s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.895e-03, size: 352, ETA: 2:47:08
2025-07-31 12:40:03.325 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.894e-03, size: 256, ETA: 2:47:06
2025-07-31 12:40:06.108 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.018s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.893e-03, size: 512, ETA: 2:47:02
2025-07-31 12:40:09.065 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.044s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.891e-03, size: 416, ETA: 2:46:59
2025-07-31 12:40:10.383 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:40:10.563 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch33
2025-07-31 12:40:13.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.123s, data_time: 0.013s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.890e-03, size: 448, ETA: 2:46:50
2025-07-31 12:40:16.327 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.123s, data_time: 0.015s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.888e-03, size: 480, ETA: 2:46:42
2025-07-31 12:40:19.203 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.041s, total_loss: 8.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.2, lr: 9.887e-03, size: 544, ETA: 2:46:38
2025-07-31 12:40:22.146 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.130s, data_time: 0.014s, total_loss: 6.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.886e-03, size: 288, ETA: 2:46:33
2025-07-31 12:40:24.944 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.131s, data_time: 0.015s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.885e-03, size: 416, ETA: 2:46:29
2025-07-31 12:40:27.880 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.130s, data_time: 0.019s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 9.883e-03, size: 256, ETA: 2:46:24
2025-07-31 12:40:29.084 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:40:29.124 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch34
2025-07-31 12:40:32.125 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.013s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.881e-03, size: 576, ETA: 2:46:15
2025-07-31 12:40:35.066 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 9.880e-03, size: 448, ETA: 2:46:10
2025-07-31 12:40:37.976 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 9.879e-03, size: 256, ETA: 2:46:06
2025-07-31 12:40:40.893 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.877e-03, size: 544, ETA: 2:46:02
2025-07-31 12:40:43.787 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.876e-03, size: 576, ETA: 2:45:58
2025-07-31 12:40:46.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.028s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.875e-03, size: 448, ETA: 2:45:55
2025-07-31 12:40:48.052 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:40:48.107 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch35
2025-07-31 12:40:50.928 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.029s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.873e-03, size: 416, ETA: 2:45:50
2025-07-31 12:40:53.824 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.038s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.872e-03, size: 352, ETA: 2:45:46
2025-07-31 12:40:56.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.870e-03, size: 384, ETA: 2:45:40
2025-07-31 12:40:59.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.869e-03, size: 352, ETA: 2:45:35
2025-07-31 12:41:02.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.867e-03, size: 256, ETA: 2:45:29
2025-07-31 12:41:05.607 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.2, lr: 9.866e-03, size: 320, ETA: 2:45:24
2025-07-31 12:41:06.818 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:41:13.290 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:41:14.523 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:41:15.201 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4345
2025-07-31 12:41:15.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3878
2025-07-31 12:41:15.445 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2163
2025-07-31 12:41:15.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3462
2025-07-31 12:41:15.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:41:15.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.434
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.388
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.216
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.346
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:41:15.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:41:15.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:41:15.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:41:15.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:41:16.359 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:41:17.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:41:18.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:41:19.092 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:41:19.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:41:20.984 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:41:21.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:41:22.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:41:23.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:41:23.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-07-31 12:41:23.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.35
2025-07-31 12:41:23.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:41:23.699 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 0.99 ms, Average inference time: 2.41 ms

2025-07-31 12:41:23.700 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:41:23.724 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:41:23.755 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch36
2025-07-31 12:41:26.269 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.122s, data_time: 0.031s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.864e-03, size: 256, ETA: 2:45:12
2025-07-31 12:41:29.266 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.012s, total_loss: 8.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.1, lr: 9.863e-03, size: 320, ETA: 2:45:09
2025-07-31 12:41:32.191 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.861e-03, size: 352, ETA: 2:45:04
2025-07-31 12:41:35.152 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.138s, data_time: 0.010s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.860e-03, size: 448, ETA: 2:45:02
2025-07-31 12:41:37.955 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.858e-03, size: 448, ETA: 2:44:57
2025-07-31 12:41:40.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.144s, data_time: 0.028s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.857e-03, size: 416, ETA: 2:44:57
2025-07-31 12:41:42.166 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:41:42.247 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch37
2025-07-31 12:41:45.081 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.037s, total_loss: 7.3, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.855e-03, size: 256, ETA: 2:44:54
2025-07-31 12:41:48.066 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.147s, data_time: 0.009s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.853e-03, size: 416, ETA: 2:44:55
2025-07-31 12:41:50.947 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.852e-03, size: 384, ETA: 2:44:53
2025-07-31 12:41:53.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.851e-03, size: 320, ETA: 2:44:50
2025-07-31 12:41:56.891 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.849e-03, size: 416, ETA: 2:44:47
2025-07-31 12:41:59.711 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.127s, data_time: 0.026s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.848e-03, size: 320, ETA: 2:44:42
2025-07-31 12:42:01.018 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:42:01.058 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch38
2025-07-31 12:42:03.901 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.846e-03, size: 544, ETA: 2:44:35
2025-07-31 12:42:06.814 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.844e-03, size: 352, ETA: 2:44:31
2025-07-31 12:42:09.735 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.127s, data_time: 0.008s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.2, lr: 9.843e-03, size: 288, ETA: 2:44:26
2025-07-31 12:42:12.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.841e-03, size: 576, ETA: 2:44:22
2025-07-31 12:42:15.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.840e-03, size: 512, ETA: 2:44:21
2025-07-31 12:42:18.500 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.020s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.838e-03, size: 352, ETA: 2:44:17
2025-07-31 12:42:19.826 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:42:19.868 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch39
2025-07-31 12:42:22.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.836e-03, size: 512, ETA: 2:44:13
2025-07-31 12:42:25.852 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.834e-03, size: 384, ETA: 2:44:10
2025-07-31 12:42:28.731 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.128s, data_time: 0.006s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.833e-03, size: 544, ETA: 2:44:05
2025-07-31 12:42:31.664 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.831e-03, size: 576, ETA: 2:43:59
2025-07-31 12:42:34.472 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.830e-03, size: 288, ETA: 2:43:55
2025-07-31 12:42:37.300 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.828e-03, size: 352, ETA: 2:43:50
2025-07-31 12:42:38.575 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:42:38.642 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch40
2025-07-31 12:42:41.536 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.027s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.826e-03, size: 256, ETA: 2:43:46
2025-07-31 12:42:44.541 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.014s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.824e-03, size: 288, ETA: 2:43:43
2025-07-31 12:42:47.430 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.008s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.823e-03, size: 320, ETA: 2:43:40
2025-07-31 12:42:50.366 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.035s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.821e-03, size: 544, ETA: 2:43:37
2025-07-31 12:42:53.236 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.011s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.819e-03, size: 416, ETA: 2:43:33
2025-07-31 12:42:56.155 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.818e-03, size: 480, ETA: 2:43:29
2025-07-31 12:42:57.427 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:43:04.017 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:43:05.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:43:06.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4847
2025-07-31 12:43:06.211 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4014
2025-07-31 12:43:06.264 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2631
2025-07-31 12:43:06.264 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3831
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.485
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.401
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.263
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.383
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:43:06.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:43:06.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:43:06.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:43:06.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:43:07.233 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:43:08.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:43:09.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:43:10.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:43:11.051 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:43:11.999 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:43:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:43:13.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:43:14.885 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:43:14.886 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-31 12:43:14.886 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.38
2025-07-31 12:43:14.886 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:43:14.893 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.95 ms, Average inference time: 2.31 ms

2025-07-31 12:43:14.894 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:43:14.920 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:43:14.951 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch41
2025-07-31 12:43:17.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.120s, data_time: 0.027s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 9.816e-03, size: 448, ETA: 2:43:20
2025-07-31 12:43:20.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.142s, data_time: 0.018s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.814e-03, size: 288, ETA: 2:43:19
2025-07-31 12:43:23.288 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.812e-03, size: 320, ETA: 2:43:18
2025-07-31 12:43:26.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.811e-03, size: 480, ETA: 2:43:18
2025-07-31 12:43:29.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.028s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.809e-03, size: 416, ETA: 2:43:14
2025-07-31 12:43:32.038 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.145s, data_time: 0.055s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.807e-03, size: 416, ETA: 2:43:14
2025-07-31 12:43:33.419 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:43:33.461 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch42
2025-07-31 12:43:36.242 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.805e-03, size: 384, ETA: 2:43:13
2025-07-31 12:43:39.078 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.049s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.803e-03, size: 576, ETA: 2:43:11
2025-07-31 12:43:42.055 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.147s, data_time: 0.058s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.802e-03, size: 288, ETA: 2:43:11
2025-07-31 12:43:45.001 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.146s, data_time: 0.056s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.800e-03, size: 320, ETA: 2:43:11
2025-07-31 12:43:47.938 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.798e-03, size: 288, ETA: 2:43:09
2025-07-31 12:43:50.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.049s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.797e-03, size: 576, ETA: 2:43:06
2025-07-31 12:43:51.993 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:43:52.113 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch43
2025-07-31 12:43:54.985 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.024s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.794e-03, size: 416, ETA: 2:43:01
2025-07-31 12:43:57.968 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.143s, data_time: 0.015s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.792e-03, size: 576, ETA: 2:43:01
2025-07-31 12:44:00.889 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.036s, total_loss: 7.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.791e-03, size: 288, ETA: 2:42:58
2025-07-31 12:44:03.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.035s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.789e-03, size: 352, ETA: 2:42:56
2025-07-31 12:44:06.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.047s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.787e-03, size: 416, ETA: 2:42:53
2025-07-31 12:44:09.511 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.127s, data_time: 0.009s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.785e-03, size: 384, ETA: 2:42:48
2025-07-31 12:44:10.816 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:44:10.854 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch44
2025-07-31 12:44:13.752 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.028s, total_loss: 6.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 9.783e-03, size: 384, ETA: 2:42:44
2025-07-31 12:44:16.611 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 9.781e-03, size: 576, ETA: 2:42:39
2025-07-31 12:44:19.608 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.139s, data_time: 0.005s, total_loss: 8.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.6, lr: 9.779e-03, size: 256, ETA: 2:42:37
2025-07-31 12:44:22.475 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.130s, data_time: 0.014s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.778e-03, size: 512, ETA: 2:42:33
2025-07-31 12:44:25.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.024s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.776e-03, size: 352, ETA: 2:42:30
2025-07-31 12:44:28.373 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.010s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.774e-03, size: 576, ETA: 2:42:27
2025-07-31 12:44:29.673 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:44:29.832 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch45
2025-07-31 12:44:32.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 9.772e-03, size: 512, ETA: 2:42:19
2025-07-31 12:44:35.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.770e-03, size: 544, ETA: 2:42:15
2025-07-31 12:44:38.444 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.125s, data_time: 0.005s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.3, lr: 9.768e-03, size: 256, ETA: 2:42:10
2025-07-31 12:44:41.406 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.766e-03, size: 448, ETA: 2:42:08
2025-07-31 12:44:44.253 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 9.764e-03, size: 320, ETA: 2:42:05
2025-07-31 12:44:47.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.149s, data_time: 0.004s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.762e-03, size: 480, ETA: 2:42:06
2025-07-31 12:44:48.480 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:44:55.104 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:44:56.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:44:58.131 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4343
2025-07-31 12:44:58.366 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3621
2025-07-31 12:44:58.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1898
2025-07-31 12:44:58.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3287
2025-07-31 12:44:58.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:44:58.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:44:58.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.434
2025-07-31 12:44:58.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.362
2025-07-31 12:44:58.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.190
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.329
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:44:58.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:44:59.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:45:01.396 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:45:02.905 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:45:04.430 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:45:05.829 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:45:07.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:45:08.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:45:10.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:45:11.661 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:45:11.661 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.14
2025-07-31 12:45:11.661 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.33
2025-07-31 12:45:11.661 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:45:11.671 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 0.98 ms, Average inference time: 2.39 ms

2025-07-31 12:45:11.672 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:45:11.697 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:45:11.729 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch46
2025-07-31 12:45:14.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.124s, data_time: 0.007s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.760e-03, size: 448, ETA: 2:41:58
2025-07-31 12:45:17.182 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.758e-03, size: 448, ETA: 2:41:55
2025-07-31 12:45:20.115 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.756e-03, size: 320, ETA: 2:41:51
2025-07-31 12:45:23.078 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.754e-03, size: 480, ETA: 2:41:49
2025-07-31 12:45:25.996 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 9.752e-03, size: 320, ETA: 2:41:46
2025-07-31 12:45:28.833 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 9.751e-03, size: 384, ETA: 2:41:43
2025-07-31 12:45:30.112 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:45:30.174 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch47
2025-07-31 12:45:33.149 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.007s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.748e-03, size: 576, ETA: 2:41:39
2025-07-31 12:45:36.122 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.746e-03, size: 384, ETA: 2:41:35
2025-07-31 12:45:39.054 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.744e-03, size: 288, ETA: 2:41:31
2025-07-31 12:45:42.064 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.742e-03, size: 512, ETA: 2:41:27
2025-07-31 12:45:45.003 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.740e-03, size: 352, ETA: 2:41:23
2025-07-31 12:45:47.795 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.738e-03, size: 480, ETA: 2:41:19
2025-07-31 12:45:49.133 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:45:49.219 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch48
2025-07-31 12:45:51.948 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.131s, data_time: 0.015s, total_loss: 6.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 9.736e-03, size: 288, ETA: 2:41:16
2025-07-31 12:45:54.990 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.143s, data_time: 0.020s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.734e-03, size: 544, ETA: 2:41:15
2025-07-31 12:45:57.854 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.037s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.732e-03, size: 320, ETA: 2:41:12
2025-07-31 12:46:00.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.148s, data_time: 0.059s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.730e-03, size: 448, ETA: 2:41:12
2025-07-31 12:46:03.667 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.141s, data_time: 0.053s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.728e-03, size: 544, ETA: 2:41:11
2025-07-31 12:46:06.659 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.025s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.726e-03, size: 352, ETA: 2:41:08
2025-07-31 12:46:07.975 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:46:08.074 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch49
2025-07-31 12:46:10.847 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.125s, data_time: 0.006s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.723e-03, size: 448, ETA: 2:41:02
2025-07-31 12:46:13.793 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.721e-03, size: 320, ETA: 2:41:00
2025-07-31 12:46:16.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.010s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.719e-03, size: 288, ETA: 2:40:58
2025-07-31 12:46:19.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.130s, data_time: 0.036s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.717e-03, size: 256, ETA: 2:40:54
2025-07-31 12:46:22.680 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.147s, data_time: 0.061s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.715e-03, size: 384, ETA: 2:40:53
2025-07-31 12:46:25.611 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.146s, data_time: 0.057s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.713e-03, size: 416, ETA: 2:40:53
2025-07-31 12:46:26.961 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:46:27.025 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch50
2025-07-31 12:46:29.925 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.144s, data_time: 0.054s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.710e-03, size: 448, ETA: 2:40:52
2025-07-31 12:46:32.736 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 9.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 5.5, cls_loss: 0.9, lr: 9.708e-03, size: 576, ETA: 2:40:50
2025-07-31 12:46:35.672 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.007s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.706e-03, size: 384, ETA: 2:40:48
2025-07-31 12:46:38.612 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.704e-03, size: 320, ETA: 2:40:44
2025-07-31 12:46:41.539 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.702e-03, size: 544, ETA: 2:40:42
2025-07-31 12:46:44.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.141s, data_time: 0.023s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.700e-03, size: 448, ETA: 2:40:40
2025-07-31 12:46:45.838 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:46:52.155 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:46:55.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:46:58.569 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4402
2025-07-31 12:46:58.818 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3904
2025-07-31 12:46:58.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2298
2025-07-31 12:46:58.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3535
2025-07-31 12:46:58.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:46:58.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:46:58.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.440
2025-07-31 12:46:58.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.390
2025-07-31 12:46:58.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.230
2025-07-31 12:46:58.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.353
2025-07-31 12:46:58.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:46:58.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:46:58.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:46:58.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:46:58.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:46:58.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:46:58.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:46:58.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:46:58.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:47:01.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:47:05.142 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:47:08.198 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:47:11.268 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:47:14.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:47:17.422 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:47:20.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:47:23.569 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:47:26.629 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:47:26.631 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-07-31 12:47:26.631 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.35
2025-07-31 12:47:26.632 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:47:26.670 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.99 ms, Average inference time: 2.41 ms

2025-07-31 12:47:26.672 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:47:26.709 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:47:26.755 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch51
2025-07-31 12:47:29.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.040s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.697e-03, size: 576, ETA: 2:40:35
2025-07-31 12:47:32.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.147s, data_time: 0.057s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.695e-03, size: 544, ETA: 2:40:34
2025-07-31 12:47:35.338 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.151s, data_time: 0.065s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.693e-03, size: 480, ETA: 2:40:35
2025-07-31 12:47:38.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.154s, data_time: 0.067s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.691e-03, size: 448, ETA: 2:40:36
2025-07-31 12:47:41.400 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.147s, data_time: 0.058s, total_loss: 8.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 9.689e-03, size: 416, ETA: 2:40:36
2025-07-31 12:47:44.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.142s, data_time: 0.055s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 9.687e-03, size: 256, ETA: 2:40:34
2025-07-31 12:47:45.469 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:47:45.524 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch52
2025-07-31 12:47:48.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.140s, data_time: 0.039s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.684e-03, size: 288, ETA: 2:40:31
2025-07-31 12:47:51.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.142s, data_time: 0.011s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.681e-03, size: 320, ETA: 2:40:30
2025-07-31 12:47:54.440 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 9.679e-03, size: 448, ETA: 2:40:27
2025-07-31 12:47:57.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.677e-03, size: 544, ETA: 2:40:24
2025-07-31 12:48:00.207 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.036s, total_loss: 7.5, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.675e-03, size: 448, ETA: 2:40:21
2025-07-31 12:48:03.153 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.140s, data_time: 0.023s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.673e-03, size: 416, ETA: 2:40:19
2025-07-31 12:48:04.459 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:48:04.514 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch53
2025-07-31 12:48:07.517 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.670e-03, size: 512, ETA: 2:40:14
2025-07-31 12:48:10.438 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.008s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 9.668e-03, size: 512, ETA: 2:40:11
2025-07-31 12:48:13.328 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.666e-03, size: 416, ETA: 2:40:07
2025-07-31 12:48:16.246 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.141s, data_time: 0.034s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.663e-03, size: 352, ETA: 2:40:06
2025-07-31 12:48:19.181 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.144s, data_time: 0.020s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.661e-03, size: 576, ETA: 2:40:05
2025-07-31 12:48:22.067 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.014s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 9.659e-03, size: 576, ETA: 2:40:01
2025-07-31 12:48:23.344 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:48:23.504 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch54
2025-07-31 12:48:26.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.018s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.656e-03, size: 320, ETA: 2:39:56
2025-07-31 12:48:29.344 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.145s, data_time: 0.027s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.654e-03, size: 544, ETA: 2:39:56
2025-07-31 12:48:32.349 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.141s, data_time: 0.007s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.651e-03, size: 576, ETA: 2:39:54
2025-07-31 12:48:35.338 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.649e-03, size: 480, ETA: 2:39:51
2025-07-31 12:48:38.219 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.647e-03, size: 384, ETA: 2:39:47
2025-07-31 12:48:41.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 6.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.645e-03, size: 288, ETA: 2:39:44
2025-07-31 12:48:42.464 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:48:42.580 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch55
2025-07-31 12:48:45.406 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.642e-03, size: 320, ETA: 2:39:37
2025-07-31 12:48:48.371 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.018s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.639e-03, size: 448, ETA: 2:39:32
2025-07-31 12:48:51.270 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.141s, data_time: 0.005s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.637e-03, size: 384, ETA: 2:39:30
2025-07-31 12:48:54.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.152s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.635e-03, size: 512, ETA: 2:39:31
2025-07-31 12:48:57.283 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.146s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.633e-03, size: 320, ETA: 2:39:30
2025-07-31 12:49:00.273 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.148s, data_time: 0.009s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.630e-03, size: 480, ETA: 2:39:30
2025-07-31 12:49:01.609 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:49:08.167 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:49:09.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:49:09.882 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4979
2025-07-31 12:49:10.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4121
2025-07-31 12:49:10.153 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2755
2025-07-31 12:49:10.153 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3952
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.498
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.412
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.275
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.395
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:49:10.154 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:49:10.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:49:10.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:49:10.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:49:10.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:49:10.988 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:49:11.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:49:12.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:49:13.349 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:49:14.148 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:49:14.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:49:15.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:49:16.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:49:17.307 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:49:17.308 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-07-31 12:49:17.308 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-07-31 12:49:17.308 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:49:17.316 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 0.98 ms, Average inference time: 2.43 ms

2025-07-31 12:49:17.317 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:49:17.340 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:49:17.373 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch56
2025-07-31 12:49:19.932 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.120s, data_time: 0.016s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.627e-03, size: 320, ETA: 2:39:24
2025-07-31 12:49:22.877 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.039s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.625e-03, size: 480, ETA: 2:39:20
2025-07-31 12:49:25.821 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.623e-03, size: 576, ETA: 2:39:17
2025-07-31 12:49:28.730 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.620e-03, size: 576, ETA: 2:39:14
2025-07-31 12:49:31.808 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.144s, data_time: 0.003s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.618e-03, size: 320, ETA: 2:39:13
2025-07-31 12:49:34.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.138s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.616e-03, size: 416, ETA: 2:39:10
2025-07-31 12:49:35.953 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:49:36.113 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch57
2025-07-31 12:49:38.970 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.126s, data_time: 0.014s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.2, lr: 9.612e-03, size: 256, ETA: 2:39:04
2025-07-31 12:49:41.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.010s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.610e-03, size: 544, ETA: 2:38:59
2025-07-31 12:49:44.756 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.039s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.608e-03, size: 384, ETA: 2:38:55
2025-07-31 12:49:47.771 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.019s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.605e-03, size: 512, ETA: 2:38:51
2025-07-31 12:49:50.755 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.007s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.603e-03, size: 320, ETA: 2:38:47
2025-07-31 12:49:53.623 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 9.601e-03, size: 384, ETA: 2:38:42
2025-07-31 12:49:55.009 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:49:55.049 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch58
2025-07-31 12:49:57.846 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.047s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.597e-03, size: 576, ETA: 2:38:39
2025-07-31 12:50:00.739 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.142s, data_time: 0.054s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.595e-03, size: 256, ETA: 2:38:38
2025-07-31 12:50:03.663 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.044s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.592e-03, size: 416, ETA: 2:38:35
2025-07-31 12:50:06.692 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.010s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.590e-03, size: 352, ETA: 2:38:33
2025-07-31 12:50:09.678 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 9.588e-03, size: 256, ETA: 2:38:29
2025-07-31 12:50:12.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.585e-03, size: 576, ETA: 2:38:26
2025-07-31 12:50:13.968 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:50:14.045 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch59
2025-07-31 12:50:17.010 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.582e-03, size: 480, ETA: 2:38:21
2025-07-31 12:50:19.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.0, lr: 9.579e-03, size: 480, ETA: 2:38:17
2025-07-31 12:50:22.842 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.577e-03, size: 576, ETA: 2:38:13
2025-07-31 12:50:25.807 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.575e-03, size: 256, ETA: 2:38:09
2025-07-31 12:50:28.607 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.005s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.572e-03, size: 384, ETA: 2:38:05
2025-07-31 12:50:31.491 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.142s, data_time: 0.043s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.570e-03, size: 448, ETA: 2:38:04
2025-07-31 12:50:32.881 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:50:32.941 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch60
2025-07-31 12:50:35.740 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.039s, total_loss: 7.0, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.566e-03, size: 256, ETA: 2:38:02
2025-07-31 12:50:38.653 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.014s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.564e-03, size: 416, ETA: 2:37:58
2025-07-31 12:50:41.508 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.007s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.561e-03, size: 512, ETA: 2:37:55
2025-07-31 12:50:44.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.018s, total_loss: 7.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.559e-03, size: 384, ETA: 2:37:52
2025-07-31 12:50:47.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.139s, data_time: 0.036s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.556e-03, size: 448, ETA: 2:37:50
2025-07-31 12:50:50.236 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.141s, data_time: 0.005s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.554e-03, size: 480, ETA: 2:37:48
2025-07-31 12:50:51.516 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:50:57.940 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:51:00.321 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:51:01.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4798
2025-07-31 12:51:01.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4335
2025-07-31 12:51:02.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2638
2025-07-31 12:51:02.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3924
2025-07-31 12:51:02.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:51:02.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:51:02.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.480
2025-07-31 12:51:02.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.434
2025-07-31 12:51:02.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.264
2025-07-31 12:51:02.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.392
2025-07-31 12:51:02.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:51:02.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:51:02.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:51:02.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:51:02.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:51:02.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:51:02.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:51:02.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:51:02.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:51:03.847 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:51:05.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:51:07.348 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:51:09.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:51:10.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:51:12.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:51:14.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:51:16.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:51:17.957 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:51:17.957 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-31 12:51:17.957 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-31 12:51:17.958 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:51:17.984 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.96 ms, Average inference time: 2.36 ms

2025-07-31 12:51:17.985 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:51:18.017 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:51:18.051 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch61
2025-07-31 12:51:20.565 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.125s, data_time: 0.038s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.550e-03, size: 384, ETA: 2:37:43
2025-07-31 12:51:23.478 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.143s, data_time: 0.048s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.548e-03, size: 288, ETA: 2:37:41
2025-07-31 12:51:26.545 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.139s, data_time: 0.024s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.545e-03, size: 288, ETA: 2:37:39
2025-07-31 12:51:29.568 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.543e-03, size: 288, ETA: 2:37:36
2025-07-31 12:51:32.507 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.540e-03, size: 288, ETA: 2:37:33
2025-07-31 12:51:35.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.538e-03, size: 352, ETA: 2:37:30
2025-07-31 12:51:36.642 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:51:36.700 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch62
2025-07-31 12:51:39.550 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.138s, data_time: 0.015s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.534e-03, size: 256, ETA: 2:37:27
2025-07-31 12:51:42.395 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 9.532e-03, size: 480, ETA: 2:37:23
2025-07-31 12:51:45.262 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 9.529e-03, size: 384, ETA: 2:37:19
2025-07-31 12:51:48.276 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 9.526e-03, size: 352, ETA: 2:37:16
2025-07-31 12:51:51.224 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.524e-03, size: 544, ETA: 2:37:13
2025-07-31 12:51:54.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.521e-03, size: 416, ETA: 2:37:10
2025-07-31 12:51:55.482 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:51:55.619 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch63
2025-07-31 12:51:58.480 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.030s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.518e-03, size: 576, ETA: 2:37:05
2025-07-31 12:52:01.329 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.014s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 9.515e-03, size: 320, ETA: 2:37:01
2025-07-31 12:52:04.223 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.142s, data_time: 0.004s, total_loss: 7.3, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.512e-03, size: 256, ETA: 2:36:59
2025-07-31 12:52:07.133 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.140s, data_time: 0.024s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 9.510e-03, size: 576, ETA: 2:36:57
2025-07-31 12:52:10.052 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.143s, data_time: 0.006s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.507e-03, size: 480, ETA: 2:36:56
2025-07-31 12:52:12.939 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.142s, data_time: 0.005s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.505e-03, size: 320, ETA: 2:36:54
2025-07-31 12:52:14.264 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:52:14.450 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch64
2025-07-31 12:52:17.395 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 9.501e-03, size: 480, ETA: 2:36:51
2025-07-31 12:52:20.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.498e-03, size: 480, ETA: 2:36:49
2025-07-31 12:52:23.194 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.496e-03, size: 256, ETA: 2:36:46
2025-07-31 12:52:26.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.493e-03, size: 448, ETA: 2:36:44
2025-07-31 12:52:29.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.141s, data_time: 0.005s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.490e-03, size: 416, ETA: 2:36:42
2025-07-31 12:52:32.228 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.488e-03, size: 256, ETA: 2:36:40
2025-07-31 12:52:33.668 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:52:33.705 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch65
2025-07-31 12:52:36.650 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.145s, data_time: 0.005s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.484e-03, size: 352, ETA: 2:36:39
2025-07-31 12:52:39.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.148s, data_time: 0.004s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.6, lr: 9.481e-03, size: 448, ETA: 2:36:38
2025-07-31 12:52:42.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.140s, data_time: 0.013s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.479e-03, size: 352, ETA: 2:36:36
2025-07-31 12:52:45.408 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.144s, data_time: 0.028s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.476e-03, size: 416, ETA: 2:36:35
2025-07-31 12:52:48.357 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.144s, data_time: 0.011s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.473e-03, size: 256, ETA: 2:36:33
2025-07-31 12:52:51.281 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.143s, data_time: 0.043s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.471e-03, size: 256, ETA: 2:36:32
2025-07-31 12:52:52.625 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:52:59.178 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:53:00.035 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:53:00.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3865
2025-07-31 12:53:00.601 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3455
2025-07-31 12:53:00.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2392
2025-07-31 12:53:00.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3237
2025-07-31 12:53:00.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:53:00.680 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:53:00.680 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.386
2025-07-31 12:53:00.681 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.345
2025-07-31 12:53:00.681 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.239
2025-07-31 12:53:00.682 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.324
2025-07-31 12:53:00.682 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:53:00.683 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:53:00.683 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:53:00.683 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:53:00.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:53:00.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:53:00.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:53:00.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:53:00.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:53:01.350 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:53:01.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:53:02.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:53:03.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:53:03.854 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:53:04.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:53:05.075 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:53:05.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:53:06.294 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:53:06.295 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.14
2025-07-31 12:53:06.295 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.32
2025-07-31 12:53:06.295 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:53:06.302 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.92 ms, Average inference time: 2.35 ms

2025-07-31 12:53:06.303 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:53:06.329 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:53:06.360 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch66
2025-07-31 12:53:08.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.120s, data_time: 0.018s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.467e-03, size: 288, ETA: 2:36:26
2025-07-31 12:53:11.758 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.018s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.464e-03, size: 256, ETA: 2:36:22
2025-07-31 12:53:14.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.016s, total_loss: 8.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 9.461e-03, size: 256, ETA: 2:36:18
2025-07-31 12:53:17.640 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.009s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.459e-03, size: 544, ETA: 2:36:15
2025-07-31 12:53:20.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 9.456e-03, size: 352, ETA: 2:36:12
2025-07-31 12:53:23.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.453e-03, size: 384, ETA: 2:36:08
2025-07-31 12:53:24.903 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:53:25.035 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch67
2025-07-31 12:53:27.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.449e-03, size: 256, ETA: 2:36:02
2025-07-31 12:53:30.835 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.017s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 9.446e-03, size: 448, ETA: 2:35:58
2025-07-31 12:53:33.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.444e-03, size: 448, ETA: 2:35:54
2025-07-31 12:53:36.730 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.005s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 9.441e-03, size: 320, ETA: 2:35:50
2025-07-31 12:53:39.783 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.438e-03, size: 544, ETA: 2:35:47
2025-07-31 12:53:42.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.435e-03, size: 352, ETA: 2:35:43
2025-07-31 12:53:44.087 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:53:44.152 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch68
2025-07-31 12:53:46.901 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.123s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.431e-03, size: 544, ETA: 2:35:36
2025-07-31 12:53:49.786 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.031s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.429e-03, size: 352, ETA: 2:35:33
2025-07-31 12:53:52.679 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.010s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.426e-03, size: 544, ETA: 2:35:30
2025-07-31 12:53:55.644 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 9.423e-03, size: 416, ETA: 2:35:27
2025-07-31 12:53:58.620 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.420e-03, size: 576, ETA: 2:35:25
2025-07-31 12:54:01.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 9.417e-03, size: 416, ETA: 2:35:22
2025-07-31 12:54:02.921 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:54:03.059 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch69
2025-07-31 12:54:05.892 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.413e-03, size: 352, ETA: 2:35:16
2025-07-31 12:54:08.811 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.410e-03, size: 352, ETA: 2:35:13
2025-07-31 12:54:11.732 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.037s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.408e-03, size: 480, ETA: 2:35:10
2025-07-31 12:54:14.634 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.024s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.405e-03, size: 576, ETA: 2:35:06
2025-07-31 12:54:17.644 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.019s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.402e-03, size: 480, ETA: 2:35:03
2025-07-31 12:54:20.500 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.125s, data_time: 0.004s, total_loss: 6.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 9.399e-03, size: 416, ETA: 2:34:58
2025-07-31 12:54:21.790 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:54:21.827 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch70
2025-07-31 12:54:24.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 9.395e-03, size: 448, ETA: 2:34:54
2025-07-31 12:54:27.716 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.392e-03, size: 416, ETA: 2:34:51
2025-07-31 12:54:30.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 9.389e-03, size: 416, ETA: 2:34:48
2025-07-31 12:54:33.609 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.019s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.5, lr: 9.386e-03, size: 256, ETA: 2:34:45
2025-07-31 12:54:36.574 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.136s, data_time: 0.011s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.383e-03, size: 512, ETA: 2:34:43
2025-07-31 12:54:39.602 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.143s, data_time: 0.054s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 9.381e-03, size: 352, ETA: 2:34:41
2025-07-31 12:54:40.884 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:54:47.379 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:54:48.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:54:49.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5090
2025-07-31 12:54:50.159 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3923
2025-07-31 12:54:50.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2513
2025-07-31 12:54:50.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3842
2025-07-31 12:54:50.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:54:50.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:54:50.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.509
2025-07-31 12:54:50.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.392
2025-07-31 12:54:50.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.251
2025-07-31 12:54:50.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.384
2025-07-31 12:54:50.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:54:50.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:54:50.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:54:50.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:54:50.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:54:50.211 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:54:50.211 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:54:50.211 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:54:50.211 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:54:51.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:54:52.598 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:54:53.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:54:55.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:54:56.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:54:57.531 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:54:58.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:55:00.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:55:01.211 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:55:01.211 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-07-31 12:55:01.211 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.38
2025-07-31 12:55:01.212 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:55:01.219 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 0.97 ms, Average inference time: 2.38 ms

2025-07-31 12:55:01.220 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:55:01.248 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:55:01.292 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch71
2025-07-31 12:55:03.889 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.005s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.6, lr: 9.376e-03, size: 288, ETA: 2:34:36
2025-07-31 12:55:06.797 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.373e-03, size: 256, ETA: 2:34:34
2025-07-31 12:55:09.804 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.149s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.371e-03, size: 544, ETA: 2:34:33
2025-07-31 12:55:12.814 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.149s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.368e-03, size: 384, ETA: 2:34:33
2025-07-31 12:55:15.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.146s, data_time: 0.009s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.365e-03, size: 352, ETA: 2:34:31
2025-07-31 12:55:18.686 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.143s, data_time: 0.006s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 9.362e-03, size: 544, ETA: 2:34:30
2025-07-31 12:55:20.009 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:55:20.057 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch72
2025-07-31 12:55:22.966 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.144s, data_time: 0.056s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.358e-03, size: 384, ETA: 2:34:28
2025-07-31 12:55:25.881 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.145s, data_time: 0.058s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.355e-03, size: 352, ETA: 2:34:26
2025-07-31 12:55:28.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.025s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.352e-03, size: 288, ETA: 2:34:23
2025-07-31 12:55:31.710 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.141s, data_time: 0.004s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.349e-03, size: 384, ETA: 2:34:21
2025-07-31 12:55:34.576 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.011s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 9.346e-03, size: 512, ETA: 2:34:18
2025-07-31 12:55:37.662 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 9.343e-03, size: 416, ETA: 2:34:15
2025-07-31 12:55:38.859 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:55:38.942 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch73
2025-07-31 12:55:41.979 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.338e-03, size: 544, ETA: 2:34:11
2025-07-31 12:55:44.917 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.026s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.335e-03, size: 480, ETA: 2:34:07
2025-07-31 12:55:47.751 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.041s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.332e-03, size: 256, ETA: 2:34:04
2025-07-31 12:55:50.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.148s, data_time: 0.064s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.329e-03, size: 384, ETA: 2:34:03
2025-07-31 12:55:53.721 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.147s, data_time: 0.062s, total_loss: 9.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 5.2, cls_loss: 1.3, lr: 9.326e-03, size: 544, ETA: 2:34:02
2025-07-31 12:55:56.556 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.139s, data_time: 0.042s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.323e-03, size: 512, ETA: 2:34:00
2025-07-31 12:55:57.808 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:55:57.857 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch74
2025-07-31 12:56:00.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.020s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.319e-03, size: 256, ETA: 2:33:55
2025-07-31 12:56:03.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.142s, data_time: 0.034s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 9.316e-03, size: 544, ETA: 2:33:53
2025-07-31 12:56:06.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.021s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.313e-03, size: 448, ETA: 2:33:50
2025-07-31 12:56:09.653 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.310e-03, size: 416, ETA: 2:33:47
2025-07-31 12:56:12.511 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.307e-03, size: 512, ETA: 2:33:44
2025-07-31 12:56:15.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.010s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.304e-03, size: 352, ETA: 2:33:41
2025-07-31 12:56:16.654 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:56:16.742 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch75
2025-07-31 12:56:19.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.010s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.299e-03, size: 352, ETA: 2:33:36
2025-07-31 12:56:22.522 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.013s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.296e-03, size: 576, ETA: 2:33:33
2025-07-31 12:56:25.428 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.031s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.293e-03, size: 448, ETA: 2:33:30
2025-07-31 12:56:28.492 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.048s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.290e-03, size: 384, ETA: 2:33:27
2025-07-31 12:56:31.423 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.014s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.287e-03, size: 512, ETA: 2:33:23
2025-07-31 12:56:34.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.127s, data_time: 0.012s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.284e-03, size: 384, ETA: 2:33:19
2025-07-31 12:56:35.513 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:56:41.930 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:56:46.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:56:50.354 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3892
2025-07-31 12:56:50.883 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4407
2025-07-31 12:56:50.980 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2199
2025-07-31 12:56:50.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3499
2025-07-31 12:56:50.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:56:50.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:56:50.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.389
2025-07-31 12:56:50.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.441
2025-07-31 12:56:50.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.220
2025-07-31 12:56:50.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.350
2025-07-31 12:56:50.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:56:50.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:56:50.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:56:50.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:56:50.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:56:50.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:56:50.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:56:50.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:56:50.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:56:55.192 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:56:59.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:57:03.527 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:57:07.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:57:11.810 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:57:15.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:57:20.196 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:57:24.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:57:28.414 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:57:28.414 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-07-31 12:57:28.414 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.35
2025-07-31 12:57:28.414 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:57:28.440 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.98 ms, Average inference time: 2.38 ms

2025-07-31 12:57:28.441 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:57:28.469 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:57:28.502 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch76
2025-07-31 12:57:31.080 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.124s, data_time: 0.017s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.280e-03, size: 576, ETA: 2:33:13
2025-07-31 12:57:33.974 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.276e-03, size: 576, ETA: 2:33:10
2025-07-31 12:57:36.913 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.141s, data_time: 0.029s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.273e-03, size: 320, ETA: 2:33:08
2025-07-31 12:57:39.791 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.012s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.270e-03, size: 544, ETA: 2:33:05
2025-07-31 12:57:42.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.267e-03, size: 448, ETA: 2:33:02
2025-07-31 12:57:45.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.264e-03, size: 480, ETA: 2:32:58
2025-07-31 12:57:46.903 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:57:47.032 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch77
2025-07-31 12:57:49.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.126s, data_time: 0.013s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.259e-03, size: 352, ETA: 2:32:53
2025-07-31 12:57:52.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 7.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.256e-03, size: 544, ETA: 2:32:49
2025-07-31 12:57:55.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.253e-03, size: 416, ETA: 2:32:47
2025-07-31 12:57:58.692 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.147s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.250e-03, size: 512, ETA: 2:32:45
2025-07-31 12:58:01.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.247e-03, size: 544, ETA: 2:32:44
2025-07-31 12:58:04.728 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.4Gb, iter_time: 0.150s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.244e-03, size: 576, ETA: 2:32:43
2025-07-31 12:58:06.016 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:58:06.142 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch78
2025-07-31 12:58:09.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 9.239e-03, size: 448, ETA: 2:32:39
2025-07-31 12:58:11.841 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 9.236e-03, size: 576, ETA: 2:32:37
2025-07-31 12:58:14.798 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.233e-03, size: 352, ETA: 2:32:34
2025-07-31 12:58:17.622 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.004s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.229e-03, size: 576, ETA: 2:32:31
2025-07-31 12:58:20.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.226e-03, size: 352, ETA: 2:32:28
2025-07-31 12:58:23.415 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.008s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.223e-03, size: 480, ETA: 2:32:25
2025-07-31 12:58:24.701 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:58:24.777 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch79
2025-07-31 12:58:27.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.047s, total_loss: 7.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 9.218e-03, size: 512, ETA: 2:32:20
2025-07-31 12:58:30.593 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.144s, data_time: 0.051s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.215e-03, size: 544, ETA: 2:32:19
2025-07-31 12:58:33.572 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.147s, data_time: 0.058s, total_loss: 8.8, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.0, lr: 9.212e-03, size: 352, ETA: 2:32:18
2025-07-31 12:58:36.614 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.151s, data_time: 0.065s, total_loss: 6.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 9.209e-03, size: 352, ETA: 2:32:17
2025-07-31 12:58:39.598 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.148s, data_time: 0.067s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.206e-03, size: 448, ETA: 2:32:16
2025-07-31 12:58:42.500 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.141s, data_time: 0.052s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.202e-03, size: 352, ETA: 2:32:14
2025-07-31 12:58:43.848 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:58:44.000 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch80
2025-07-31 12:58:46.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.136s, data_time: 0.012s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 9.198e-03, size: 512, ETA: 2:32:10
2025-07-31 12:58:49.729 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.194e-03, size: 384, ETA: 2:32:08
2025-07-31 12:58:52.615 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.191e-03, size: 512, ETA: 2:32:05
2025-07-31 12:58:55.600 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.188e-03, size: 320, ETA: 2:32:03
2025-07-31 12:58:58.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.184e-03, size: 256, ETA: 2:32:00
2025-07-31 12:59:01.502 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.016s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.181e-03, size: 384, ETA: 2:31:57
2025-07-31 12:59:02.826 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:59:09.325 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 12:59:11.200 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 12:59:12.474 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5213
2025-07-31 12:59:12.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4155
2025-07-31 12:59:12.768 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2533
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3967
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.521
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.415
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.253
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.397
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 12:59:12.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 12:59:12.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 12:59:12.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 12:59:12.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 12:59:12.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 12:59:12.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 12:59:12.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 12:59:14.220 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 12:59:15.675 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 12:59:17.170 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 12:59:18.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 12:59:20.122 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 12:59:21.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 12:59:23.036 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 12:59:24.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 12:59:25.915 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 12:59:25.915 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-31 12:59:25.915 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-07-31 12:59:25.915 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 12:59:25.924 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 0.99 ms, Average inference time: 2.40 ms

2025-07-31 12:59:25.926 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:59:25.949 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:59:25.982 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch81
2025-07-31 12:59:28.444 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.120s, data_time: 0.030s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.176e-03, size: 544, ETA: 2:31:50
2025-07-31 12:59:31.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.142s, data_time: 0.043s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.173e-03, size: 416, ETA: 2:31:48
2025-07-31 12:59:34.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.147s, data_time: 0.059s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.170e-03, size: 384, ETA: 2:31:47
2025-07-31 12:59:37.291 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.140s, data_time: 0.051s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.166e-03, size: 544, ETA: 2:31:45
2025-07-31 12:59:40.232 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.025s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.163e-03, size: 352, ETA: 2:31:42
2025-07-31 12:59:43.238 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.160e-03, size: 480, ETA: 2:31:39
2025-07-31 12:59:44.436 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 12:59:44.493 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch82
2025-07-31 12:59:47.375 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.016s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.155e-03, size: 384, ETA: 2:31:34
2025-07-31 12:59:50.247 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.041s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 9.152e-03, size: 256, ETA: 2:31:31
2025-07-31 12:59:53.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.037s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.148e-03, size: 320, ETA: 2:31:29
2025-07-31 12:59:56.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.139s, data_time: 0.015s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 9.145e-03, size: 576, ETA: 2:31:26
2025-07-31 12:59:59.083 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.142e-03, size: 256, ETA: 2:31:23
2025-07-31 13:00:02.034 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.138e-03, size: 480, ETA: 2:31:21
2025-07-31 13:00:03.338 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:00:03.466 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch83
2025-07-31 13:00:06.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.133e-03, size: 384, ETA: 2:31:15
2025-07-31 13:00:09.193 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.030s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.130e-03, size: 512, ETA: 2:31:13
2025-07-31 13:00:12.079 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.011s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.127e-03, size: 256, ETA: 2:31:09
2025-07-31 13:00:14.942 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.123e-03, size: 544, ETA: 2:31:06
2025-07-31 13:00:17.933 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.143s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.120e-03, size: 416, ETA: 2:31:04
2025-07-31 13:00:20.715 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.036s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.3, lr: 9.116e-03, size: 480, ETA: 2:31:01
2025-07-31 13:00:22.069 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:00:22.109 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch84
2025-07-31 13:00:24.847 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.136s, data_time: 0.050s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.2, lr: 9.112e-03, size: 320, ETA: 2:30:57
2025-07-31 13:00:27.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.027s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 9.108e-03, size: 448, ETA: 2:30:54
2025-07-31 13:00:30.871 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.105e-03, size: 384, ETA: 2:30:51
2025-07-31 13:00:33.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.101e-03, size: 480, ETA: 2:30:48
2025-07-31 13:00:36.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.139s, data_time: 0.046s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.098e-03, size: 544, ETA: 2:30:46
2025-07-31 13:00:39.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.142s, data_time: 0.053s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 9.094e-03, size: 288, ETA: 2:30:44
2025-07-31 13:00:40.985 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:00:41.038 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch85
2025-07-31 13:00:43.852 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.046s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 9.089e-03, size: 320, ETA: 2:30:40
2025-07-31 13:00:46.858 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.043s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.086e-03, size: 320, ETA: 2:30:37
2025-07-31 13:00:49.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.124s, data_time: 0.039s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.082e-03, size: 416, ETA: 2:30:32
2025-07-31 13:00:52.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.034s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.079e-03, size: 576, ETA: 2:30:29
2025-07-31 13:00:55.661 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.007s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.076e-03, size: 320, ETA: 2:30:26
2025-07-31 13:00:58.508 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.024s, total_loss: 8.9, iou_loss: 3.8, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.072e-03, size: 384, ETA: 2:30:22
2025-07-31 13:00:59.748 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:01:06.293 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:01:10.286 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:01:12.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4663
2025-07-31 13:01:13.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4490
2025-07-31 13:01:13.522 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2647
2025-07-31 13:01:13.523 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3933
2025-07-31 13:01:13.523 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:01:13.523 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:01:13.523 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.466
2025-07-31 13:01:13.523 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.449
2025-07-31 13:01:13.523 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.265
2025-07-31 13:01:13.523 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.393
2025-07-31 13:01:13.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:01:13.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:01:13.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:01:13.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:01:13.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:01:13.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:01:13.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:01:13.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:01:13.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:01:17.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:01:20.315 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:01:23.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:01:26.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:01:30.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:01:33.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:01:36.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:01:39.990 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:01:43.241 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:01:43.242 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-07-31 13:01:43.242 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-31 13:01:43.242 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:01:43.268 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 1.04 ms, Average inference time: 2.51 ms

2025-07-31 13:01:43.270 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:01:43.302 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:01:43.345 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch86
2025-07-31 13:01:45.858 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.119s, data_time: 0.015s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 9.067e-03, size: 480, ETA: 2:30:16
2025-07-31 13:01:48.719 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.007s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.064e-03, size: 416, ETA: 2:30:13
2025-07-31 13:01:51.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.141s, data_time: 0.039s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.060e-03, size: 512, ETA: 2:30:11
2025-07-31 13:01:54.685 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.005s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.057e-03, size: 320, ETA: 2:30:09
2025-07-31 13:01:57.592 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.016s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.053e-03, size: 352, ETA: 2:30:06
2025-07-31 13:02:00.511 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.017s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.050e-03, size: 384, ETA: 2:30:03
2025-07-31 13:02:01.810 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:02:01.958 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch87
2025-07-31 13:02:04.758 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.124s, data_time: 0.004s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.044e-03, size: 384, ETA: 2:29:57
2025-07-31 13:02:07.785 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 9.041e-03, size: 288, ETA: 2:29:55
2025-07-31 13:02:10.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.037e-03, size: 480, ETA: 2:29:52
2025-07-31 13:02:13.649 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.034e-03, size: 416, ETA: 2:29:48
2025-07-31 13:02:16.516 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.127s, data_time: 0.006s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 9.030e-03, size: 256, ETA: 2:29:45
2025-07-31 13:02:19.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 9.027e-03, size: 352, ETA: 2:29:41
2025-07-31 13:02:20.631 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:02:20.721 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch88
2025-07-31 13:02:23.598 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.031s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.022e-03, size: 544, ETA: 2:29:37
2025-07-31 13:02:26.471 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.031s, total_loss: 8.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.2, lr: 9.018e-03, size: 544, ETA: 2:29:34
2025-07-31 13:02:29.385 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.145s, data_time: 0.056s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.014e-03, size: 352, ETA: 2:29:33
2025-07-31 13:02:32.302 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.023s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.011e-03, size: 416, ETA: 2:29:30
2025-07-31 13:02:35.192 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.008s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.007e-03, size: 480, ETA: 2:29:27
2025-07-31 13:02:38.121 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.015s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.004e-03, size: 480, ETA: 2:29:24
2025-07-31 13:02:39.461 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:02:39.584 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch89
2025-07-31 13:02:42.444 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.011s, total_loss: 7.4, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.998e-03, size: 352, ETA: 2:29:19
2025-07-31 13:02:45.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.018s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.995e-03, size: 544, ETA: 2:29:16
2025-07-31 13:02:48.470 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.991e-03, size: 480, ETA: 2:29:13
2025-07-31 13:02:51.307 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.124s, data_time: 0.004s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.6, lr: 8.988e-03, size: 384, ETA: 2:29:09
2025-07-31 13:02:54.284 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.984e-03, size: 320, ETA: 2:29:06
2025-07-31 13:02:57.123 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 8.980e-03, size: 352, ETA: 2:29:03
2025-07-31 13:02:58.411 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:02:58.561 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch90
2025-07-31 13:03:01.299 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.975e-03, size: 480, ETA: 2:28:59
2025-07-31 13:03:04.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.036s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 8.972e-03, size: 544, ETA: 2:28:56
2025-07-31 13:03:07.050 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.041s, total_loss: 8.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.3, lr: 8.968e-03, size: 384, ETA: 2:28:53
2025-07-31 13:03:10.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.964e-03, size: 416, ETA: 2:28:51
2025-07-31 13:03:12.916 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.017s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.961e-03, size: 544, ETA: 2:28:48
2025-07-31 13:03:15.758 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.010s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.2, lr: 8.957e-03, size: 384, ETA: 2:28:44
2025-07-31 13:03:17.047 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:03:23.439 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:03:27.236 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:03:29.683 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4914
2025-07-31 13:03:30.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4532
2025-07-31 13:03:30.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3067
2025-07-31 13:03:30.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4171
2025-07-31 13:03:30.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:03:30.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:03:30.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.491
2025-07-31 13:03:30.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.453
2025-07-31 13:03:30.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.307
2025-07-31 13:03:30.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.417
2025-07-31 13:03:30.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:03:30.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:03:30.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:03:30.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:03:30.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:03:30.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:03:30.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:03:30.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:03:30.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:03:33.298 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:03:36.307 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:03:39.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:03:42.326 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:03:45.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:03:48.440 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:03:51.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:03:54.406 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:03:57.402 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:03:57.403 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-31 13:03:57.403 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-31 13:03:57.403 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:03:57.430 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 1.00 ms, Average inference time: 2.41 ms

2025-07-31 13:03:57.431 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:03:57.457 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:03:57.489 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch91
2025-07-31 13:04:00.132 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.044s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 8.952e-03, size: 320, ETA: 2:28:40
2025-07-31 13:04:02.995 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.142s, data_time: 0.053s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.2, lr: 8.948e-03, size: 320, ETA: 2:28:38
2025-07-31 13:04:05.812 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.048s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.944e-03, size: 480, ETA: 2:28:36
2025-07-31 13:04:08.691 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.142s, data_time: 0.051s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.941e-03, size: 544, ETA: 2:28:34
2025-07-31 13:04:11.582 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.139s, data_time: 0.049s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 8.937e-03, size: 320, ETA: 2:28:31
2025-07-31 13:04:14.510 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.145s, data_time: 0.057s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 8.933e-03, size: 544, ETA: 2:28:30
2025-07-31 13:04:15.874 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:04:15.912 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch92
2025-07-31 13:04:18.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.042s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 8.928e-03, size: 512, ETA: 2:28:26
2025-07-31 13:04:21.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.053s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 8.924e-03, size: 320, ETA: 2:28:24
2025-07-31 13:04:24.592 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.141s, data_time: 0.050s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.920e-03, size: 512, ETA: 2:28:22
2025-07-31 13:04:27.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.917e-03, size: 256, ETA: 2:28:19
2025-07-31 13:04:30.331 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.141s, data_time: 0.051s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 8.913e-03, size: 256, ETA: 2:28:17
2025-07-31 13:04:33.197 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.051s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 8.909e-03, size: 416, ETA: 2:28:15
2025-07-31 13:04:34.430 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:04:34.480 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch93
2025-07-31 13:04:37.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.145s, data_time: 0.012s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.904e-03, size: 480, ETA: 2:28:12
2025-07-31 13:04:40.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.900e-03, size: 480, ETA: 2:28:10
2025-07-31 13:04:43.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.896e-03, size: 512, ETA: 2:28:07
2025-07-31 13:04:46.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.143s, data_time: 0.003s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.893e-03, size: 544, ETA: 2:28:05
2025-07-31 13:04:49.060 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.148s, data_time: 0.012s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.889e-03, size: 256, ETA: 2:28:04
2025-07-31 13:04:52.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.143s, data_time: 0.016s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.2, lr: 8.885e-03, size: 480, ETA: 2:28:02
2025-07-31 13:04:53.101 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:04:53.228 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch94
2025-07-31 13:04:56.028 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.022s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 8.880e-03, size: 416, ETA: 2:27:57
2025-07-31 13:04:58.925 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.026s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 8.876e-03, size: 352, ETA: 2:27:54
2025-07-31 13:05:01.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.872e-03, size: 288, ETA: 2:27:51
2025-07-31 13:05:04.651 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.007s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.868e-03, size: 320, ETA: 2:27:48
2025-07-31 13:05:07.485 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.034s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.864e-03, size: 256, ETA: 2:27:44
2025-07-31 13:05:10.532 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.142s, data_time: 0.026s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.4, lr: 8.861e-03, size: 448, ETA: 2:27:42
2025-07-31 13:05:11.811 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:05:11.980 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch95
2025-07-31 13:05:14.851 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 8.855e-03, size: 352, ETA: 2:27:37
2025-07-31 13:05:17.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.031s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.851e-03, size: 576, ETA: 2:27:35
2025-07-31 13:05:20.666 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.145s, data_time: 0.021s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.847e-03, size: 448, ETA: 2:27:33
2025-07-31 13:05:23.623 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.010s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.844e-03, size: 544, ETA: 2:27:30
2025-07-31 13:05:26.435 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.040s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 8.840e-03, size: 256, ETA: 2:27:27
2025-07-31 13:05:29.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.143s, data_time: 0.033s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 8.836e-03, size: 448, ETA: 2:27:25
2025-07-31 13:05:30.655 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:05:37.165 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:05:38.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:05:39.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5090
2025-07-31 13:05:39.995 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4388
2025-07-31 13:05:40.044 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2447
2025-07-31 13:05:40.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3975
2025-07-31 13:05:40.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:05:40.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:05:40.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.509
2025-07-31 13:05:40.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.439
2025-07-31 13:05:40.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.245
2025-07-31 13:05:40.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.397
2025-07-31 13:05:40.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:05:40.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:05:40.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:05:40.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:05:40.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:05:40.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:05:40.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:05:40.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:05:40.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:05:41.326 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:05:42.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:05:43.890 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:05:45.142 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:05:46.393 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:05:47.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:05:48.937 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:05:50.256 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:05:51.496 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:05:51.496 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-31 13:05:51.496 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-07-31 13:05:51.496 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:05:51.503 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 1.01 ms, Average inference time: 2.45 ms

2025-07-31 13:05:51.504 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:05:51.525 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:05:51.555 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch96
2025-07-31 13:05:54.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.122s, data_time: 0.029s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 8.830e-03, size: 448, ETA: 2:27:20
2025-07-31 13:05:56.874 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.042s, total_loss: 7.1, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.826e-03, size: 256, ETA: 2:27:17
2025-07-31 13:05:59.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.023s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.823e-03, size: 448, ETA: 2:27:14
2025-07-31 13:06:02.763 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.023s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.819e-03, size: 544, ETA: 2:27:11
2025-07-31 13:06:05.662 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.143s, data_time: 0.046s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.6, lr: 8.815e-03, size: 448, ETA: 2:27:09
2025-07-31 13:06:08.500 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.040s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.811e-03, size: 352, ETA: 2:27:06
2025-07-31 13:06:09.744 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:06:09.837 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch97
2025-07-31 13:06:12.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.145s, data_time: 0.052s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.805e-03, size: 448, ETA: 2:27:02
2025-07-31 13:06:15.739 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.047s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.802e-03, size: 576, ETA: 2:26:59
2025-07-31 13:06:18.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.144s, data_time: 0.053s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.798e-03, size: 416, ETA: 2:26:58
2025-07-31 13:06:21.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.142s, data_time: 0.049s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.794e-03, size: 288, ETA: 2:26:55
2025-07-31 13:06:24.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.049s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 8.790e-03, size: 512, ETA: 2:26:53
2025-07-31 13:06:27.279 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 8.786e-03, size: 256, ETA: 2:26:51
2025-07-31 13:06:28.669 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:06:28.715 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch98
2025-07-31 13:06:31.512 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.046s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.780e-03, size: 576, ETA: 2:26:48
2025-07-31 13:06:34.331 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.044s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.776e-03, size: 416, ETA: 2:26:45
2025-07-31 13:06:37.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.040s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.1, lr: 8.772e-03, size: 256, ETA: 2:26:42
2025-07-31 13:06:40.147 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.043s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 8.768e-03, size: 352, ETA: 2:26:39
2025-07-31 13:06:43.030 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.025s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.765e-03, size: 416, ETA: 2:26:36
2025-07-31 13:06:45.987 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.139s, data_time: 0.014s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 8.761e-03, size: 384, ETA: 2:26:34
2025-07-31 13:06:47.261 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:06:47.360 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch99
2025-07-31 13:06:50.257 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.016s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.755e-03, size: 576, ETA: 2:26:29
2025-07-31 13:06:53.048 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.018s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.751e-03, size: 512, ETA: 2:26:25
2025-07-31 13:06:55.936 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.040s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 8.747e-03, size: 256, ETA: 2:26:22
2025-07-31 13:06:58.880 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.125s, data_time: 0.006s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.743e-03, size: 384, ETA: 2:26:18
2025-07-31 13:07:01.705 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.739e-03, size: 352, ETA: 2:26:16
2025-07-31 13:07:04.716 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.735e-03, size: 576, ETA: 2:26:14
2025-07-31 13:07:06.000 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:07:06.049 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch100
2025-07-31 13:07:08.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.020s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 8.729e-03, size: 480, ETA: 2:26:10
2025-07-31 13:07:11.796 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.010s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.725e-03, size: 512, ETA: 2:26:07
2025-07-31 13:07:14.759 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.721e-03, size: 352, ETA: 2:26:04
2025-07-31 13:07:17.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.007s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 8.717e-03, size: 288, ETA: 2:26:01
2025-07-31 13:07:20.458 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.007s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 8.713e-03, size: 544, ETA: 2:25:58
2025-07-31 13:07:23.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.013s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.709e-03, size: 416, ETA: 2:25:56
2025-07-31 13:07:24.735 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:07:31.248 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:07:33.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:07:35.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5293
2025-07-31 13:07:35.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4579
2025-07-31 13:07:35.833 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3135
2025-07-31 13:07:35.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4336
2025-07-31 13:07:35.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:07:35.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:07:35.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.529
2025-07-31 13:07:35.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.458
2025-07-31 13:07:35.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.314
2025-07-31 13:07:35.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.434
2025-07-31 13:07:35.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:07:35.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:07:35.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:07:35.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:07:35.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:07:35.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:07:35.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:07:35.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:07:35.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:07:37.872 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:07:39.915 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:07:41.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:07:44.036 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:07:46.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:07:48.075 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:07:50.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:07:52.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:07:54.167 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:07:54.167 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-31 13:07:54.167 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-31 13:07:54.167 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:07:54.194 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 1.01 ms, Average inference time: 2.44 ms

2025-07-31 13:07:54.195 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:07:54.226 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:07:54.274 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch101
2025-07-31 13:07:56.783 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.122s, data_time: 0.035s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.703e-03, size: 512, ETA: 2:25:50
2025-07-31 13:07:59.729 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.146s, data_time: 0.058s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.699e-03, size: 288, ETA: 2:25:48
2025-07-31 13:08:02.607 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.143s, data_time: 0.054s, total_loss: 7.2, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.695e-03, size: 288, ETA: 2:25:46
2025-07-31 13:08:05.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.142s, data_time: 0.053s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.1, lr: 8.691e-03, size: 512, ETA: 2:25:44
2025-07-31 13:08:08.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.145s, data_time: 0.050s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 8.687e-03, size: 512, ETA: 2:25:42
2025-07-31 13:08:11.267 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.141s, data_time: 0.049s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.683e-03, size: 256, ETA: 2:25:40
2025-07-31 13:08:12.479 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:08:12.540 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch102
2025-07-31 13:08:15.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.145s, data_time: 0.061s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 8.677e-03, size: 288, ETA: 2:25:37
2025-07-31 13:08:18.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.152s, data_time: 0.066s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.673e-03, size: 544, ETA: 2:25:36
2025-07-31 13:08:21.428 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.145s, data_time: 0.036s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.669e-03, size: 512, ETA: 2:25:34
2025-07-31 13:08:24.377 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.008s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.665e-03, size: 416, ETA: 2:25:31
2025-07-31 13:08:27.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 8.661e-03, size: 480, ETA: 2:25:28
2025-07-31 13:08:30.224 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.657e-03, size: 256, ETA: 2:25:25
2025-07-31 13:08:31.388 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:08:31.466 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch103
2025-07-31 13:08:34.393 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.651e-03, size: 384, ETA: 2:25:20
2025-07-31 13:08:37.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.647e-03, size: 416, ETA: 2:25:17
2025-07-31 13:08:40.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.643e-03, size: 576, ETA: 2:25:14
2025-07-31 13:08:43.345 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 8.639e-03, size: 384, ETA: 2:25:11
2025-07-31 13:08:46.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.5Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.635e-03, size: 512, ETA: 2:25:09
2025-07-31 13:08:49.146 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.631e-03, size: 384, ETA: 2:25:06
2025-07-31 13:08:50.513 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:08:50.679 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch104
2025-07-31 13:08:53.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 8.625e-03, size: 448, ETA: 2:25:03
2025-07-31 13:08:56.385 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 8.620e-03, size: 544, ETA: 2:25:00
2025-07-31 13:08:59.219 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.138s, data_time: 0.008s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.616e-03, size: 480, ETA: 2:24:58
2025-07-31 13:09:02.079 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.036s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.612e-03, size: 288, ETA: 2:24:54
2025-07-31 13:09:05.047 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.047s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.608e-03, size: 576, ETA: 2:24:52
2025-07-31 13:09:07.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.046s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.604e-03, size: 512, ETA: 2:24:49
2025-07-31 13:09:09.253 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:09:09.318 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch105
2025-07-31 13:09:12.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.138s, data_time: 0.010s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.598e-03, size: 512, ETA: 2:24:45
2025-07-31 13:09:15.111 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.144s, data_time: 0.011s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.594e-03, size: 384, ETA: 2:24:43
2025-07-31 13:09:18.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.144s, data_time: 0.028s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.590e-03, size: 576, ETA: 2:24:41
2025-07-31 13:09:20.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.019s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.585e-03, size: 352, ETA: 2:24:38
2025-07-31 13:09:23.816 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.037s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.581e-03, size: 384, ETA: 2:24:36
2025-07-31 13:09:26.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.034s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 8.577e-03, size: 352, ETA: 2:24:33
2025-07-31 13:09:27.994 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:09:34.588 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:09:40.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:09:44.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4868
2025-07-31 13:09:45.714 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4103
2025-07-31 13:09:45.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2202
2025-07-31 13:09:45.791 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3724
2025-07-31 13:09:45.791 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.487
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.410
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.220
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.372
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:09:45.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:09:45.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:09:45.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:09:50.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:09:55.897 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:10:00.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:10:06.019 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:10:11.057 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:10:16.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:10:20.991 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:10:25.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:10:30.889 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:10:30.890 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-07-31 13:10:30.890 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-07-31 13:10:30.890 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:10:30.917 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 1.00 ms, Average inference time: 2.40 ms

2025-07-31 13:10:30.918 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:10:30.952 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:10:30.988 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch106
2025-07-31 13:10:33.485 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.119s, data_time: 0.035s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.571e-03, size: 384, ETA: 2:24:28
2025-07-31 13:10:36.378 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.055s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.567e-03, size: 576, ETA: 2:24:25
2025-07-31 13:10:39.279 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.141s, data_time: 0.055s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 8.563e-03, size: 544, ETA: 2:24:23
2025-07-31 13:10:42.190 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.143s, data_time: 0.051s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.558e-03, size: 576, ETA: 2:24:21
2025-07-31 13:10:45.023 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.028s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 8.554e-03, size: 288, ETA: 2:24:17
2025-07-31 13:10:47.989 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.550e-03, size: 256, ETA: 2:24:15
2025-07-31 13:10:49.296 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:10:49.335 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch107
2025-07-31 13:10:52.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 8.544e-03, size: 480, ETA: 2:24:10
2025-07-31 13:10:54.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.034s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.540e-03, size: 384, ETA: 2:24:07
2025-07-31 13:10:57.953 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.144s, data_time: 0.041s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 8.535e-03, size: 384, ETA: 2:24:05
2025-07-31 13:11:00.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.142s, data_time: 0.054s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.531e-03, size: 448, ETA: 2:24:03
2025-07-31 13:11:03.675 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.045s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 8.527e-03, size: 320, ETA: 2:24:01
2025-07-31 13:11:06.567 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.523e-03, size: 448, ETA: 2:23:58
2025-07-31 13:11:07.867 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:11:07.911 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch108
2025-07-31 13:11:10.763 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.517e-03, size: 352, ETA: 2:23:53
2025-07-31 13:11:13.727 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.143s, data_time: 0.058s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 8.512e-03, size: 384, ETA: 2:23:51
2025-07-31 13:11:16.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.508e-03, size: 544, ETA: 2:23:49
2025-07-31 13:11:19.487 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.033s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 8.504e-03, size: 256, ETA: 2:23:47
2025-07-31 13:11:22.424 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.012s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.500e-03, size: 512, ETA: 2:23:44
2025-07-31 13:11:25.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.022s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.495e-03, size: 320, ETA: 2:23:41
2025-07-31 13:11:26.424 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:11:26.526 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch109
2025-07-31 13:11:29.311 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.489e-03, size: 384, ETA: 2:23:36
2025-07-31 13:11:32.360 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.151s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.4, lr: 8.485e-03, size: 448, ETA: 2:23:35
2025-07-31 13:11:35.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 7.5, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 8.480e-03, size: 256, ETA: 2:23:32
2025-07-31 13:11:38.062 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.476e-03, size: 416, ETA: 2:23:30
2025-07-31 13:11:41.078 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.146s, data_time: 0.004s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.472e-03, size: 544, ETA: 2:23:28
2025-07-31 13:11:43.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 8.468e-03, size: 256, ETA: 2:23:26
2025-07-31 13:11:45.199 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:11:45.322 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch110
2025-07-31 13:11:48.126 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 8.461e-03, size: 480, ETA: 2:23:22
2025-07-31 13:11:51.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.052s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.6, lr: 8.457e-03, size: 384, ETA: 2:23:20
2025-07-31 13:11:53.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.022s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.453e-03, size: 576, ETA: 2:23:17
2025-07-31 13:11:56.730 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.007s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.448e-03, size: 512, ETA: 2:23:14
2025-07-31 13:11:59.615 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.444e-03, size: 480, ETA: 2:23:11
2025-07-31 13:12:02.594 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.138s, data_time: 0.019s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.440e-03, size: 416, ETA: 2:23:08
2025-07-31 13:12:03.936 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:12:10.321 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:12:14.103 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:12:15.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5314
2025-07-31 13:12:16.791 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4587
2025-07-31 13:12:16.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2757
2025-07-31 13:12:16.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4219
2025-07-31 13:12:16.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:12:16.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:12:16.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.531
2025-07-31 13:12:16.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.459
2025-07-31 13:12:16.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.276
2025-07-31 13:12:16.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.422
2025-07-31 13:12:16.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:12:16.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:12:16.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:12:16.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:12:16.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:12:16.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:12:16.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:12:16.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:12:16.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:12:19.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:12:22.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:12:25.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:12:28.055 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:12:30.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:12:33.703 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:12:36.540 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:12:39.333 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:12:42.179 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:12:42.180 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-31 13:12:42.180 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-31 13:12:42.180 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:12:42.205 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 0.99 ms, Average inference time: 2.42 ms

2025-07-31 13:12:42.208 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:12:42.241 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:12:42.275 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch111
2025-07-31 13:12:44.861 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.121s, data_time: 0.029s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.433e-03, size: 544, ETA: 2:23:03
2025-07-31 13:12:47.718 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.140s, data_time: 0.037s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.429e-03, size: 352, ETA: 2:23:01
2025-07-31 13:12:50.795 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.151s, data_time: 0.012s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 8.425e-03, size: 448, ETA: 2:22:59
2025-07-31 13:12:53.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.021s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 8.420e-03, size: 352, ETA: 2:22:57
2025-07-31 13:12:56.527 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.144s, data_time: 0.045s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.416e-03, size: 544, ETA: 2:22:55
2025-07-31 13:12:59.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.145s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.5, lr: 8.412e-03, size: 384, ETA: 2:22:53
2025-07-31 13:13:00.715 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:13:00.804 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch112
2025-07-31 13:13:03.664 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.012s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.405e-03, size: 384, ETA: 2:22:49
2025-07-31 13:13:06.635 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.004s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.401e-03, size: 512, ETA: 2:22:46
2025-07-31 13:13:09.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.015s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.396e-03, size: 352, ETA: 2:22:43
2025-07-31 13:13:12.530 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.392e-03, size: 416, ETA: 2:22:41
2025-07-31 13:13:15.338 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.011s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 8.388e-03, size: 384, ETA: 2:22:37
2025-07-31 13:13:18.282 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.007s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 8.383e-03, size: 576, ETA: 2:22:35
2025-07-31 13:13:19.553 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:13:19.703 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch113
2025-07-31 13:13:22.533 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.007s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.377e-03, size: 288, ETA: 2:22:30
2025-07-31 13:13:25.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.020s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 8.372e-03, size: 288, ETA: 2:22:26
2025-07-31 13:13:28.366 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.009s, total_loss: 7.4, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 8.368e-03, size: 384, ETA: 2:22:23
2025-07-31 13:13:31.344 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.364e-03, size: 384, ETA: 2:22:20
2025-07-31 13:13:34.315 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.359e-03, size: 480, ETA: 2:22:16
2025-07-31 13:13:37.355 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.355e-03, size: 384, ETA: 2:22:13
2025-07-31 13:13:38.602 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:13:38.657 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch114
2025-07-31 13:13:41.533 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.348e-03, size: 416, ETA: 2:22:08
2025-07-31 13:13:44.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.037s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.344e-03, size: 576, ETA: 2:22:06
2025-07-31 13:13:47.285 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.144s, data_time: 0.054s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.339e-03, size: 576, ETA: 2:22:04
2025-07-31 13:13:50.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.150s, data_time: 0.064s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.335e-03, size: 384, ETA: 2:22:03
2025-07-31 13:13:53.276 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.054s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.331e-03, size: 576, ETA: 2:22:00
2025-07-31 13:13:56.189 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.142s, data_time: 0.053s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.326e-03, size: 384, ETA: 2:21:58
2025-07-31 13:13:57.450 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:13:57.538 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch115
2025-07-31 13:14:00.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.144s, data_time: 0.053s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 8.320e-03, size: 352, ETA: 2:21:55
2025-07-31 13:14:03.358 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.142s, data_time: 0.057s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.315e-03, size: 544, ETA: 2:21:53
2025-07-31 13:14:06.264 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.144s, data_time: 0.048s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.311e-03, size: 352, ETA: 2:21:50
2025-07-31 13:14:09.118 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.140s, data_time: 0.005s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 8.306e-03, size: 512, ETA: 2:21:48
2025-07-31 13:14:11.982 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.140s, data_time: 0.026s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.302e-03, size: 288, ETA: 2:21:46
2025-07-31 13:14:14.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.143s, data_time: 0.052s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 8.297e-03, size: 512, ETA: 2:21:44
2025-07-31 13:14:16.285 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:14:22.979 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:14:26.352 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:14:28.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5170
2025-07-31 13:14:29.160 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4125
2025-07-31 13:14:29.227 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2691
2025-07-31 13:14:29.228 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3995
2025-07-31 13:14:29.228 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:14:29.228 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:14:29.228 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.517
2025-07-31 13:14:29.228 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.412
2025-07-31 13:14:29.228 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.269
2025-07-31 13:14:29.228 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.400
2025-07-31 13:14:29.228 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:14:29.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:14:29.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:14:29.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:14:29.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:14:29.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:14:29.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:14:29.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:14:29.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:14:32.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:14:35.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:14:37.887 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:14:40.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:14:43.591 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:14:46.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:14:49.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:14:51.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:14:54.824 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:14:54.824 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-07-31 13:14:54.824 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-07-31 13:14:54.825 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:14:54.849 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 1.03 ms, Average inference time: 2.49 ms

2025-07-31 13:14:54.852 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:14:54.878 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:14:54.911 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch116
2025-07-31 13:14:57.469 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.123s, data_time: 0.041s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.291e-03, size: 352, ETA: 2:21:39
2025-07-31 13:15:00.484 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.141s, data_time: 0.027s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 8.286e-03, size: 416, ETA: 2:21:37
2025-07-31 13:15:03.435 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.282e-03, size: 576, ETA: 2:21:34
2025-07-31 13:15:06.343 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 8.277e-03, size: 352, ETA: 2:21:32
2025-07-31 13:15:09.188 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.273e-03, size: 512, ETA: 2:21:29
2025-07-31 13:15:12.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.142s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 8.268e-03, size: 352, ETA: 2:21:27
2025-07-31 13:15:13.441 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:15:13.495 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch117
2025-07-31 13:15:16.344 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.262e-03, size: 256, ETA: 2:21:23
2025-07-31 13:15:19.241 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.142s, data_time: 0.021s, total_loss: 6.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.257e-03, size: 352, ETA: 2:21:21
2025-07-31 13:15:22.131 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.142s, data_time: 0.039s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.253e-03, size: 288, ETA: 2:21:19
2025-07-31 13:15:25.081 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.144s, data_time: 0.020s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.1, lr: 8.248e-03, size: 256, ETA: 2:21:17
2025-07-31 13:15:27.964 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.143s, data_time: 0.054s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.243e-03, size: 416, ETA: 2:21:14
2025-07-31 13:15:30.941 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.148s, data_time: 0.055s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 8.239e-03, size: 256, ETA: 2:21:13
2025-07-31 13:15:32.199 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:15:32.240 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch118
2025-07-31 13:15:35.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.049s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 8.232e-03, size: 448, ETA: 2:21:09
2025-07-31 13:15:37.902 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.228e-03, size: 480, ETA: 2:21:06
2025-07-31 13:15:40.844 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.040s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 8.223e-03, size: 384, ETA: 2:21:04
2025-07-31 13:15:43.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.040s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.219e-03, size: 480, ETA: 2:21:01
2025-07-31 13:15:46.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.144s, data_time: 0.055s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.214e-03, size: 320, ETA: 2:20:59
2025-07-31 13:15:49.657 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.147s, data_time: 0.059s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.209e-03, size: 544, ETA: 2:20:57
2025-07-31 13:15:50.819 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:15:50.923 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch119
2025-07-31 13:15:53.935 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.035s, total_loss: 7.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.203e-03, size: 352, ETA: 2:20:52
2025-07-31 13:15:56.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.031s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.198e-03, size: 288, ETA: 2:20:49
2025-07-31 13:15:59.764 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.017s, total_loss: 6.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.194e-03, size: 512, ETA: 2:20:45
2025-07-31 13:16:02.675 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.006s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.189e-03, size: 448, ETA: 2:20:42
2025-07-31 13:16:05.440 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.045s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 8.184e-03, size: 448, ETA: 2:20:39
2025-07-31 13:16:08.412 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.143s, data_time: 0.054s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 8.180e-03, size: 512, ETA: 2:20:37
2025-07-31 13:16:09.840 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:16:09.879 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch120
2025-07-31 13:16:12.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.041s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.173e-03, size: 480, ETA: 2:20:34
2025-07-31 13:16:15.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.6Gb, iter_time: 0.140s, data_time: 0.039s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.168e-03, size: 448, ETA: 2:20:31
2025-07-31 13:16:18.552 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.011s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.164e-03, size: 416, ETA: 2:20:28
2025-07-31 13:16:21.617 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.146s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.159e-03, size: 384, ETA: 2:20:27
2025-07-31 13:16:24.445 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 8.155e-03, size: 384, ETA: 2:20:24
2025-07-31 13:16:27.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.007s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.150e-03, size: 480, ETA: 2:20:21
2025-07-31 13:16:28.624 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:16:34.930 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:16:37.159 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:16:38.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5284
2025-07-31 13:16:38.991 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4680
2025-07-31 13:16:39.086 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2804
2025-07-31 13:16:39.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4256
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.528
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.468
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.280
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.426
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:16:39.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:16:39.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:16:39.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:16:39.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:16:39.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:16:39.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:16:40.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:16:42.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:16:44.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:16:46.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:16:48.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:16:50.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:16:52.397 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:16:54.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:16:56.145 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:16:56.145 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-31 13:16:56.146 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-31 13:16:56.146 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:16:56.170 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.49 ms, Average NMS time: 1.03 ms, Average inference time: 2.52 ms

2025-07-31 13:16:56.171 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:16:56.199 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:16:56.231 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch121
2025-07-31 13:16:58.777 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.125s, data_time: 0.015s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.143e-03, size: 512, ETA: 2:20:16
2025-07-31 13:17:01.576 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.011s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.139e-03, size: 384, ETA: 2:20:13
2025-07-31 13:17:04.563 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.016s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 8.134e-03, size: 544, ETA: 2:20:11
2025-07-31 13:17:07.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.129e-03, size: 256, ETA: 2:20:07
2025-07-31 13:17:10.270 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.028s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 8.125e-03, size: 352, ETA: 2:20:05
2025-07-31 13:17:13.098 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.008s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.120e-03, size: 448, ETA: 2:20:02
2025-07-31 13:17:14.438 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:17:14.529 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch122
2025-07-31 13:17:17.310 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.013s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 8.113e-03, size: 576, ETA: 2:19:58
2025-07-31 13:17:20.362 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.108e-03, size: 352, ETA: 2:19:56
2025-07-31 13:17:23.274 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.104e-03, size: 576, ETA: 2:19:53
2025-07-31 13:17:26.138 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.140s, data_time: 0.004s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.099e-03, size: 416, ETA: 2:19:51
2025-07-31 13:17:29.079 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 8.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 8.094e-03, size: 544, ETA: 2:19:48
2025-07-31 13:17:31.975 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.037s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.090e-03, size: 576, ETA: 2:19:45
2025-07-31 13:17:33.286 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:17:33.366 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch123
2025-07-31 13:17:36.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.026s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 8.083e-03, size: 320, ETA: 2:19:42
2025-07-31 13:17:39.249 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.129s, data_time: 0.005s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 8.078e-03, size: 448, ETA: 2:19:39
2025-07-31 13:17:42.283 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.074e-03, size: 512, ETA: 2:19:35
2025-07-31 13:17:45.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 8.069e-03, size: 416, ETA: 2:19:32
2025-07-31 13:17:47.930 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.015s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 8.064e-03, size: 416, ETA: 2:19:29
2025-07-31 13:17:50.860 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.030s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.059e-03, size: 352, ETA: 2:19:26
2025-07-31 13:17:52.189 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:17:52.345 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch124
2025-07-31 13:17:55.106 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 8.053e-03, size: 352, ETA: 2:19:22
2025-07-31 13:17:57.946 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.048e-03, size: 320, ETA: 2:19:19
2025-07-31 13:18:00.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.140s, data_time: 0.028s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.043e-03, size: 512, ETA: 2:19:17
2025-07-31 13:18:03.869 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 8.038e-03, size: 448, ETA: 2:19:14
2025-07-31 13:18:06.818 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.005s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.034e-03, size: 512, ETA: 2:19:12
2025-07-31 13:18:09.780 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.009s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 8.029e-03, size: 416, ETA: 2:19:09
2025-07-31 13:18:11.017 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:18:11.132 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch125
2025-07-31 13:18:13.940 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.044s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.022e-03, size: 320, ETA: 2:19:05
2025-07-31 13:18:16.790 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.045s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.017e-03, size: 384, ETA: 2:19:02
2025-07-31 13:18:19.740 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.145s, data_time: 0.017s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.012e-03, size: 448, ETA: 2:19:00
2025-07-31 13:18:22.555 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.026s, total_loss: 8.3, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 8.008e-03, size: 352, ETA: 2:18:57
2025-07-31 13:18:25.423 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.143s, data_time: 0.052s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 8.003e-03, size: 352, ETA: 2:18:55
2025-07-31 13:18:28.374 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.145s, data_time: 0.051s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 7.998e-03, size: 512, ETA: 2:18:53
2025-07-31 13:18:29.761 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:18:36.248 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:18:38.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:18:40.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5460
2025-07-31 13:18:40.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4680
2025-07-31 13:18:40.367 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2881
2025-07-31 13:18:40.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4340
2025-07-31 13:18:40.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.546
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.468
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.288
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.434
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:18:40.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:18:40.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:18:40.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:18:40.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:18:42.159 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:18:44.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:18:45.821 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:18:47.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:18:49.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:18:51.264 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:18:53.090 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:18:54.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:18:56.790 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:18:56.790 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-07-31 13:18:56.790 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-31 13:18:56.790 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:18:56.814 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 1.02 ms, Average inference time: 2.46 ms

2025-07-31 13:18:56.819 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:18:56.845 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:18:56.878 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch126
2025-07-31 13:18:59.501 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.043s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.991e-03, size: 384, ETA: 2:18:49
2025-07-31 13:19:02.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.151s, data_time: 0.054s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 7.986e-03, size: 544, ETA: 2:18:48
2025-07-31 13:19:05.375 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.140s, data_time: 0.047s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 7.982e-03, size: 352, ETA: 2:18:45
2025-07-31 13:19:08.248 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.025s, total_loss: 8.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 7.977e-03, size: 352, ETA: 2:18:42
2025-07-31 13:19:11.341 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.146s, data_time: 0.058s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 7.972e-03, size: 480, ETA: 2:18:40
2025-07-31 13:19:14.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.136s, data_time: 0.033s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.967e-03, size: 288, ETA: 2:18:38
2025-07-31 13:19:15.390 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:19:15.491 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch127
2025-07-31 13:19:18.367 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.029s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.960e-03, size: 544, ETA: 2:18:33
2025-07-31 13:19:21.281 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.144s, data_time: 0.056s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.955e-03, size: 448, ETA: 2:18:31
2025-07-31 13:19:24.230 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.145s, data_time: 0.057s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.951e-03, size: 512, ETA: 2:18:29
2025-07-31 13:19:27.080 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.140s, data_time: 0.039s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 7.946e-03, size: 416, ETA: 2:18:26
2025-07-31 13:19:29.989 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.144s, data_time: 0.052s, total_loss: 8.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.3, lr: 7.941e-03, size: 576, ETA: 2:18:24
2025-07-31 13:19:32.922 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.143s, data_time: 0.052s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 7.936e-03, size: 480, ETA: 2:18:22
2025-07-31 13:19:34.300 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:19:34.336 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch128
2025-07-31 13:19:37.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.929e-03, size: 320, ETA: 2:18:17
2025-07-31 13:19:40.129 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.924e-03, size: 320, ETA: 2:18:14
2025-07-31 13:19:42.971 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.041s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 7.919e-03, size: 288, ETA: 2:18:12
2025-07-31 13:19:45.811 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.037s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.915e-03, size: 320, ETA: 2:18:09
2025-07-31 13:19:48.586 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.129s, data_time: 0.005s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 7.910e-03, size: 320, ETA: 2:18:06
2025-07-31 13:19:51.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.010s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 7.905e-03, size: 512, ETA: 2:18:03
2025-07-31 13:19:52.760 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:19:52.816 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch129
2025-07-31 13:19:55.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.036s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.898e-03, size: 256, ETA: 2:17:58
2025-07-31 13:19:58.693 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.129s, data_time: 0.006s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.893e-03, size: 544, ETA: 2:17:55
2025-07-31 13:20:01.583 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.008s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.888e-03, size: 384, ETA: 2:17:52
2025-07-31 13:20:04.414 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.007s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.883e-03, size: 448, ETA: 2:17:49
2025-07-31 13:20:07.328 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.129s, data_time: 0.012s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.2, lr: 7.878e-03, size: 256, ETA: 2:17:45
2025-07-31 13:20:10.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.129s, data_time: 0.015s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 7.873e-03, size: 320, ETA: 2:17:42
2025-07-31 13:20:11.549 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:20:11.579 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch130
2025-07-31 13:20:14.486 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.046s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.866e-03, size: 256, ETA: 2:17:38
2025-07-31 13:20:17.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.125s, data_time: 0.017s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 7.861e-03, size: 320, ETA: 2:17:34
2025-07-31 13:20:20.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.022s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 7.857e-03, size: 512, ETA: 2:17:32
2025-07-31 13:20:23.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.147s, data_time: 0.053s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.852e-03, size: 576, ETA: 2:17:30
2025-07-31 13:20:26.108 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.144s, data_time: 0.057s, total_loss: 7.7, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.847e-03, size: 256, ETA: 2:17:28
2025-07-31 13:20:28.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.049s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.842e-03, size: 288, ETA: 2:17:25
2025-07-31 13:20:30.182 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:20:36.571 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:20:41.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:20:44.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4914
2025-07-31 13:20:45.225 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4077
2025-07-31 13:20:45.298 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2470
2025-07-31 13:20:45.299 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3820
2025-07-31 13:20:45.299 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:20:45.299 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:20:45.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.491
2025-07-31 13:20:45.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.408
2025-07-31 13:20:45.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.247
2025-07-31 13:20:45.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.382
2025-07-31 13:20:45.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:20:45.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:20:45.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:20:45.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:20:45.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:20:45.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:20:45.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:20:45.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:20:45.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:20:49.508 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:20:53.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:20:57.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:21:01.308 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:21:05.277 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:21:09.187 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:21:13.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:21:17.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:21:20.919 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:21:20.920 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-07-31 13:21:20.920 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.38
2025-07-31 13:21:20.920 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:21:20.946 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.99 ms, Average inference time: 2.39 ms

2025-07-31 13:21:20.947 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:21:20.977 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:21:21.012 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch131
2025-07-31 13:21:23.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.124s, data_time: 0.039s, total_loss: 6.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.835e-03, size: 320, ETA: 2:17:20
2025-07-31 13:21:26.415 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.143s, data_time: 0.055s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 7.830e-03, size: 448, ETA: 2:17:18
2025-07-31 13:21:29.383 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.141s, data_time: 0.053s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.2, lr: 7.825e-03, size: 480, ETA: 2:17:16
2025-07-31 13:21:32.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.043s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 7.820e-03, size: 288, ETA: 2:17:13
2025-07-31 13:21:35.021 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.015s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.815e-03, size: 448, ETA: 2:17:10
2025-07-31 13:21:37.855 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.005s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.810e-03, size: 416, ETA: 2:17:07
2025-07-31 13:21:39.130 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:21:39.200 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch132
2025-07-31 13:21:42.147 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.803e-03, size: 480, ETA: 2:17:03
2025-07-31 13:21:45.012 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.798e-03, size: 256, ETA: 2:17:00
2025-07-31 13:21:47.940 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.015s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.793e-03, size: 320, ETA: 2:16:58
2025-07-31 13:21:50.876 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.788e-03, size: 576, ETA: 2:16:55
2025-07-31 13:21:53.685 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.024s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.783e-03, size: 352, ETA: 2:16:52
2025-07-31 13:21:56.636 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.778e-03, size: 448, ETA: 2:16:49
2025-07-31 13:21:57.814 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:21:57.907 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch133
2025-07-31 13:22:00.820 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.011s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 7.771e-03, size: 320, ETA: 2:16:44
2025-07-31 13:22:03.689 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.009s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.766e-03, size: 448, ETA: 2:16:41
2025-07-31 13:22:06.667 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.013s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.761e-03, size: 288, ETA: 2:16:38
2025-07-31 13:22:09.521 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.756e-03, size: 384, ETA: 2:16:35
2025-07-31 13:22:12.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.129s, data_time: 0.034s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.751e-03, size: 416, ETA: 2:16:31
2025-07-31 13:22:15.145 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.136s, data_time: 0.038s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.746e-03, size: 448, ETA: 2:16:29
2025-07-31 13:22:16.459 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:22:16.515 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch134
2025-07-31 13:22:19.348 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.739e-03, size: 416, ETA: 2:16:24
2025-07-31 13:22:22.269 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 7.734e-03, size: 416, ETA: 2:16:21
2025-07-31 13:22:25.294 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.729e-03, size: 416, ETA: 2:16:18
2025-07-31 13:22:28.008 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.017s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.724e-03, size: 448, ETA: 2:16:15
2025-07-31 13:22:30.887 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.036s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.719e-03, size: 256, ETA: 2:16:11
2025-07-31 13:22:33.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.033s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 7.714e-03, size: 384, ETA: 2:16:08
2025-07-31 13:22:35.072 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:22:35.156 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch135
2025-07-31 13:22:37.904 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.046s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.707e-03, size: 256, ETA: 2:16:04
2025-07-31 13:22:40.967 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.152s, data_time: 0.060s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.702e-03, size: 352, ETA: 2:16:02
2025-07-31 13:22:43.963 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.148s, data_time: 0.059s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.697e-03, size: 544, ETA: 2:16:00
2025-07-31 13:22:46.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.048s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.692e-03, size: 256, ETA: 2:15:57
2025-07-31 13:22:49.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.045s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 7.687e-03, size: 256, ETA: 2:15:55
2025-07-31 13:22:52.505 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.145s, data_time: 0.005s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.682e-03, size: 544, ETA: 2:15:53
2025-07-31 13:22:53.707 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:23:00.062 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:23:01.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:23:02.519 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5245
2025-07-31 13:23:02.657 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4685
2025-07-31 13:23:02.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2295
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4075
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.524
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.468
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.230
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.407
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:23:02.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:23:02.707 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:23:02.707 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:23:02.707 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:23:02.707 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:23:02.707 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:23:02.707 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:23:04.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:23:05.189 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:23:06.342 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:23:07.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:23:08.605 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:23:09.726 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:23:10.859 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:23:12.011 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:23:13.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:23:13.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-31 13:23:13.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-07-31 13:23:13.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:23:13.137 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.98 ms, Average inference time: 2.42 ms

2025-07-31 13:23:13.139 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:23:13.166 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:23:13.198 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch136
2025-07-31 13:23:15.696 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.122s, data_time: 0.038s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.674e-03, size: 448, ETA: 2:15:47
2025-07-31 13:23:18.691 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.669e-03, size: 416, ETA: 2:15:45
2025-07-31 13:23:21.597 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.664e-03, size: 320, ETA: 2:15:43
2025-07-31 13:23:24.471 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.043s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.659e-03, size: 512, ETA: 2:15:40
2025-07-31 13:23:27.545 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.654e-03, size: 480, ETA: 2:15:37
2025-07-31 13:23:30.453 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.649e-03, size: 352, ETA: 2:15:34
2025-07-31 13:23:31.787 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:23:31.913 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch137
2025-07-31 13:23:34.846 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.642e-03, size: 512, ETA: 2:15:30
2025-07-31 13:23:37.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.0, lr: 7.637e-03, size: 544, ETA: 2:15:26
2025-07-31 13:23:40.636 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.009s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.632e-03, size: 320, ETA: 2:15:23
2025-07-31 13:23:43.520 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.627e-03, size: 512, ETA: 2:15:20
2025-07-31 13:23:46.470 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 7.621e-03, size: 256, ETA: 2:15:16
2025-07-31 13:23:49.418 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.616e-03, size: 416, ETA: 2:15:13
2025-07-31 13:23:50.617 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:23:50.731 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch138
2025-07-31 13:23:53.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.609e-03, size: 256, ETA: 2:15:09
2025-07-31 13:23:56.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 7.604e-03, size: 576, ETA: 2:15:06
2025-07-31 13:23:59.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.007s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 7.599e-03, size: 256, ETA: 2:15:03
2025-07-31 13:24:02.286 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.594e-03, size: 576, ETA: 2:14:59
2025-07-31 13:24:05.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 7.589e-03, size: 480, ETA: 2:14:57
2025-07-31 13:24:08.101 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.012s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.584e-03, size: 256, ETA: 2:14:54
2025-07-31 13:24:09.456 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:24:09.560 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch139
2025-07-31 13:24:12.435 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.576e-03, size: 384, ETA: 2:14:49
2025-07-31 13:24:15.217 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.571e-03, size: 480, ETA: 2:14:46
2025-07-31 13:24:18.112 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.143s, data_time: 0.013s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 7.566e-03, size: 416, ETA: 2:14:44
2025-07-31 13:24:21.072 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.018s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 7.561e-03, size: 416, ETA: 2:14:41
2025-07-31 13:24:24.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.052s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.556e-03, size: 320, ETA: 2:14:39
2025-07-31 13:24:26.930 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.143s, data_time: 0.051s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 7.551e-03, size: 544, ETA: 2:14:36
2025-07-31 13:24:28.243 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:24:28.281 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch140
2025-07-31 13:24:31.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.144s, data_time: 0.051s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.543e-03, size: 576, ETA: 2:14:33
2025-07-31 13:24:34.096 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.039s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.538e-03, size: 320, ETA: 2:14:30
2025-07-31 13:24:36.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 7.533e-03, size: 288, ETA: 2:14:27
2025-07-31 13:24:39.928 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.528e-03, size: 576, ETA: 2:14:25
2025-07-31 13:24:42.855 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.523e-03, size: 416, ETA: 2:14:22
2025-07-31 13:24:45.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.028s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.517e-03, size: 480, ETA: 2:14:19
2025-07-31 13:24:47.182 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:24:53.675 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:24:56.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:24:58.143 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5368
2025-07-31 13:24:58.501 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4691
2025-07-31 13:24:58.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2758
2025-07-31 13:24:58.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4272
2025-07-31 13:24:58.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:24:58.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:24:58.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.537
2025-07-31 13:24:58.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.469
2025-07-31 13:24:58.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.276
2025-07-31 13:24:58.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.427
2025-07-31 13:24:58.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:24:58.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:24:58.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:24:58.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:24:58.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:24:58.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:24:58.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:24:58.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:24:58.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:25:00.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:25:02.768 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:25:04.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:25:06.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:25:08.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:25:11.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:25:13.138 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:25:15.212 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:25:17.271 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:25:17.272 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-31 13:25:17.272 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-31 13:25:17.272 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:25:17.299 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 1.00 ms, Average inference time: 2.44 ms

2025-07-31 13:25:17.300 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:25:17.326 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:25:17.361 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch141
2025-07-31 13:25:19.915 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.030s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 7.510e-03, size: 448, ETA: 2:14:14
2025-07-31 13:25:22.756 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.136s, data_time: 0.013s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.505e-03, size: 576, ETA: 2:14:12
2025-07-31 13:25:25.604 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.010s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.500e-03, size: 416, ETA: 2:14:08
2025-07-31 13:25:28.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.146s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.3, lr: 7.494e-03, size: 320, ETA: 2:14:06
2025-07-31 13:25:31.480 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.489e-03, size: 416, ETA: 2:14:04
2025-07-31 13:25:34.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.144s, data_time: 0.025s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 7.484e-03, size: 384, ETA: 2:14:02
2025-07-31 13:25:35.684 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:25:35.865 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch142
2025-07-31 13:25:38.629 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.005s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 7.477e-03, size: 352, ETA: 2:13:58
2025-07-31 13:25:41.597 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.011s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.5, lr: 7.471e-03, size: 512, ETA: 2:13:55
2025-07-31 13:25:44.562 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.012s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 7.466e-03, size: 256, ETA: 2:13:52
2025-07-31 13:25:47.538 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.6, cls_loss: 0.6, lr: 7.461e-03, size: 544, ETA: 2:13:50
2025-07-31 13:25:50.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.456e-03, size: 480, ETA: 2:13:47
2025-07-31 13:25:53.500 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.451e-03, size: 480, ETA: 2:13:45
2025-07-31 13:25:54.706 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:25:54.838 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch143
2025-07-31 13:25:57.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.443e-03, size: 512, ETA: 2:13:40
2025-07-31 13:26:00.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 7.438e-03, size: 256, ETA: 2:13:37
2025-07-31 13:26:03.682 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 7.433e-03, size: 512, ETA: 2:13:34
2025-07-31 13:26:06.593 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 7.428e-03, size: 480, ETA: 2:13:31
2025-07-31 13:26:09.458 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.006s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.422e-03, size: 416, ETA: 2:13:27
2025-07-31 13:26:12.281 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.034s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.417e-03, size: 352, ETA: 2:13:25
2025-07-31 13:26:13.575 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:26:13.740 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch144
2025-07-31 13:26:16.692 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 7.410e-03, size: 512, ETA: 2:13:21
2025-07-31 13:26:19.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 8.5, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 7.404e-03, size: 288, ETA: 2:13:18
2025-07-31 13:26:22.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.399e-03, size: 352, ETA: 2:13:16
2025-07-31 13:26:25.231 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.026s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 7.394e-03, size: 256, ETA: 2:13:13
2025-07-31 13:26:28.106 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.037s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.389e-03, size: 512, ETA: 2:13:10
2025-07-31 13:26:31.008 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.045s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.384e-03, size: 512, ETA: 2:13:07
2025-07-31 13:26:32.311 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:26:32.374 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch145
2025-07-31 13:26:35.239 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.037s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.376e-03, size: 544, ETA: 2:13:03
2025-07-31 13:26:38.290 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.371e-03, size: 576, ETA: 2:13:00
2025-07-31 13:26:41.203 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.365e-03, size: 544, ETA: 2:12:57
2025-07-31 13:26:44.054 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 7.360e-03, size: 256, ETA: 2:12:53
2025-07-31 13:26:46.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.355e-03, size: 512, ETA: 2:12:50
2025-07-31 13:26:49.735 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 7.350e-03, size: 256, ETA: 2:12:46
2025-07-31 13:26:50.992 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:26:57.472 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:26:59.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:27:01.440 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4768
2025-07-31 13:27:01.811 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4789
2025-07-31 13:27:01.849 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2456
2025-07-31 13:27:01.849 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4004
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.477
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.479
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.246
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.400
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:27:01.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:27:01.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:27:01.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:27:01.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:27:01.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:27:03.791 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:27:05.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:27:07.599 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:27:09.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:27:11.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:27:13.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:27:15.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:27:17.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:27:19.027 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:27:19.028 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-31 13:27:19.028 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-07-31 13:27:19.028 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:27:19.053 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 1.00 ms, Average inference time: 2.42 ms

2025-07-31 13:27:19.054 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:27:19.110 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:27:19.178 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch146
2025-07-31 13:27:21.684 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.124s, data_time: 0.037s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 7.342e-03, size: 256, ETA: 2:12:41
2025-07-31 13:27:24.589 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.144s, data_time: 0.058s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.337e-03, size: 448, ETA: 2:12:39
2025-07-31 13:27:27.540 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.147s, data_time: 0.055s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.332e-03, size: 384, ETA: 2:12:37
2025-07-31 13:27:30.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.144s, data_time: 0.058s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 7.326e-03, size: 480, ETA: 2:12:35
2025-07-31 13:27:33.297 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.043s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 7.321e-03, size: 416, ETA: 2:12:32
2025-07-31 13:27:36.122 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.049s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.316e-03, size: 256, ETA: 2:12:30
2025-07-31 13:27:37.510 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:27:37.543 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch147
2025-07-31 13:27:40.430 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.015s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 7.308e-03, size: 480, ETA: 2:12:26
2025-07-31 13:27:43.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.303e-03, size: 416, ETA: 2:12:23
2025-07-31 13:27:46.308 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 7.298e-03, size: 448, ETA: 2:12:20
2025-07-31 13:27:49.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.007s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.292e-03, size: 512, ETA: 2:12:17
2025-07-31 13:27:52.137 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.287e-03, size: 384, ETA: 2:12:14
2025-07-31 13:27:55.065 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.282e-03, size: 576, ETA: 2:12:10
2025-07-31 13:27:56.287 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:27:56.327 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch148
2025-07-31 13:27:59.203 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.274e-03, size: 448, ETA: 2:12:06
2025-07-31 13:28:02.098 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.269e-03, size: 576, ETA: 2:12:03
2025-07-31 13:28:04.945 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.017s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 7.263e-03, size: 512, ETA: 2:12:00
2025-07-31 13:28:07.932 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.145s, data_time: 0.025s, total_loss: 8.4, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 7.258e-03, size: 288, ETA: 2:11:58
2025-07-31 13:28:10.821 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.011s, total_loss: 9.5, iou_loss: 3.8, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 0.9, lr: 7.253e-03, size: 448, ETA: 2:11:55
2025-07-31 13:28:13.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.007s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.247e-03, size: 256, ETA: 2:11:52
2025-07-31 13:28:14.954 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:28:15.096 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch149
2025-07-31 13:28:17.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.022s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.240e-03, size: 480, ETA: 2:11:48
2025-07-31 13:28:20.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.140s, data_time: 0.047s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.234e-03, size: 416, ETA: 2:11:45
2025-07-31 13:28:23.758 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.137s, data_time: 0.041s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.229e-03, size: 480, ETA: 2:11:43
2025-07-31 13:28:26.582 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.028s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.224e-03, size: 480, ETA: 2:11:40
2025-07-31 13:28:29.531 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.146s, data_time: 0.029s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 7.218e-03, size: 512, ETA: 2:11:38
2025-07-31 13:28:32.495 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.213e-03, size: 576, ETA: 2:11:36
2025-07-31 13:28:33.771 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:28:33.936 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch150
2025-07-31 13:28:36.738 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.015s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.205e-03, size: 384, ETA: 2:11:32
2025-07-31 13:28:39.625 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.143s, data_time: 0.045s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.200e-03, size: 384, ETA: 2:11:30
2025-07-31 13:28:42.640 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.149s, data_time: 0.063s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.195e-03, size: 416, ETA: 2:11:28
2025-07-31 13:28:45.653 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.150s, data_time: 0.056s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 7.189e-03, size: 576, ETA: 2:11:26
2025-07-31 13:28:48.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.144s, data_time: 0.053s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.184e-03, size: 416, ETA: 2:11:24
2025-07-31 13:28:51.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.179e-03, size: 384, ETA: 2:11:22
2025-07-31 13:28:52.714 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:28:59.255 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:29:02.081 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:29:03.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5398
2025-07-31 13:29:04.138 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4920
2025-07-31 13:29:04.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3175
2025-07-31 13:29:04.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4498
2025-07-31 13:29:04.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:29:04.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:29:04.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.540
2025-07-31 13:29:04.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.492
2025-07-31 13:29:04.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.318
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.450
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:29:04.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:29:06.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:29:08.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:29:10.809 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:29:13.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:29:15.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:29:17.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:29:19.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:29:22.111 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:29:24.250 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:29:24.251 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-31 13:29:24.251 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-31 13:29:24.251 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:29:24.278 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 1.03 ms, Average inference time: 2.44 ms

2025-07-31 13:29:24.279 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:29:24.328 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:29:24.382 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch151
2025-07-31 13:29:26.826 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.120s, data_time: 0.039s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 7.171e-03, size: 448, ETA: 2:11:17
2025-07-31 13:29:29.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.041s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.166e-03, size: 288, ETA: 2:11:14
2025-07-31 13:29:32.659 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.004s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 7.160e-03, size: 352, ETA: 2:11:11
2025-07-31 13:29:35.691 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.004s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.155e-03, size: 384, ETA: 2:11:09
2025-07-31 13:29:38.610 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.008s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 7.149e-03, size: 512, ETA: 2:11:06
2025-07-31 13:29:41.360 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.028s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 7.144e-03, size: 512, ETA: 2:11:03
2025-07-31 13:29:42.643 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:29:42.713 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch152
2025-07-31 13:29:45.619 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.038s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.136e-03, size: 512, ETA: 2:10:59
2025-07-31 13:29:48.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.011s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.131e-03, size: 544, ETA: 2:10:56
2025-07-31 13:29:51.553 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.126e-03, size: 512, ETA: 2:10:53
2025-07-31 13:29:54.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 7.120e-03, size: 512, ETA: 2:10:50
2025-07-31 13:29:57.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.115e-03, size: 480, ETA: 2:10:48
2025-07-31 13:30:00.480 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 7.109e-03, size: 448, ETA: 2:10:46
2025-07-31 13:30:01.628 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:30:01.853 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch153
2025-07-31 13:30:04.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.102e-03, size: 480, ETA: 2:10:40
2025-07-31 13:30:07.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.096e-03, size: 320, ETA: 2:10:38
2025-07-31 13:30:10.509 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.091e-03, size: 288, ETA: 2:10:35
2025-07-31 13:30:13.493 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.085e-03, size: 544, ETA: 2:10:32
2025-07-31 13:30:16.316 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.9, lr: 7.080e-03, size: 576, ETA: 2:10:28
2025-07-31 13:30:19.222 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.075e-03, size: 288, ETA: 2:10:25
2025-07-31 13:30:20.516 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:30:20.564 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch154
2025-07-31 13:30:23.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.126s, data_time: 0.016s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.067e-03, size: 576, ETA: 2:10:21
2025-07-31 13:30:26.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.005s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.061e-03, size: 320, ETA: 2:10:18
2025-07-31 13:30:29.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 7.056e-03, size: 384, ETA: 2:10:15
2025-07-31 13:30:32.097 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.050e-03, size: 384, ETA: 2:10:12
2025-07-31 13:30:34.971 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.137s, data_time: 0.004s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 7.045e-03, size: 256, ETA: 2:10:10
2025-07-31 13:30:37.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.007s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.040e-03, size: 288, ETA: 2:10:07
2025-07-31 13:30:39.145 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:30:39.192 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch155
2025-07-31 13:30:42.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.055s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.032e-03, size: 384, ETA: 2:10:03
2025-07-31 13:30:45.036 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.144s, data_time: 0.055s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.026e-03, size: 384, ETA: 2:10:01
2025-07-31 13:30:48.048 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.146s, data_time: 0.011s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 7.021e-03, size: 544, ETA: 2:09:59
2025-07-31 13:30:50.883 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.140s, data_time: 0.031s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.015e-03, size: 544, ETA: 2:09:56
2025-07-31 13:30:53.840 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.034s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.010e-03, size: 384, ETA: 2:09:54
2025-07-31 13:30:56.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.143s, data_time: 0.026s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 7.005e-03, size: 544, ETA: 2:09:52
2025-07-31 13:30:58.146 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:31:04.483 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:31:07.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:31:09.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5078
2025-07-31 13:31:09.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4729
2025-07-31 13:31:09.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2738
2025-07-31 13:31:09.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4182
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.508
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.473
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.274
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.418
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:31:09.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:31:09.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:31:09.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:31:09.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:31:09.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:31:09.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:31:12.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:31:15.019 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:31:17.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:31:20.139 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:31:22.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:31:25.148 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:31:27.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:31:30.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:31:32.609 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:31:32.610 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-31 13:31:32.610 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-31 13:31:32.610 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:31:32.638 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 0.99 ms, Average inference time: 2.42 ms

2025-07-31 13:31:32.651 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:31:32.678 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:31:32.712 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch156
2025-07-31 13:31:35.191 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.118s, data_time: 0.023s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.997e-03, size: 288, ETA: 2:09:48
2025-07-31 13:31:37.999 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.009s, total_loss: 5.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 6.991e-03, size: 288, ETA: 2:09:44
2025-07-31 13:31:40.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.016s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 6.986e-03, size: 448, ETA: 2:09:41
2025-07-31 13:31:43.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.055s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.980e-03, size: 416, ETA: 2:09:39
2025-07-31 13:31:46.821 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.042s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.975e-03, size: 544, ETA: 2:09:37
2025-07-31 13:31:49.850 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.143s, data_time: 0.033s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.969e-03, size: 448, ETA: 2:09:34
2025-07-31 13:31:51.035 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:31:51.091 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch157
2025-07-31 13:31:54.082 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.142s, data_time: 0.026s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 6.961e-03, size: 544, ETA: 2:09:30
2025-07-31 13:31:57.041 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 6.956e-03, size: 320, ETA: 2:09:27
2025-07-31 13:31:59.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.951e-03, size: 352, ETA: 2:09:25
2025-07-31 13:32:02.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.945e-03, size: 320, ETA: 2:09:22
2025-07-31 13:32:05.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.940e-03, size: 480, ETA: 2:09:19
2025-07-31 13:32:08.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.143s, data_time: 0.021s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 6.934e-03, size: 480, ETA: 2:09:17
2025-07-31 13:32:09.886 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:32:10.037 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch158
2025-07-31 13:32:13.064 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.003s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 6.926e-03, size: 352, ETA: 2:09:14
2025-07-31 13:32:15.867 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.921e-03, size: 512, ETA: 2:09:11
2025-07-31 13:32:18.868 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 6.915e-03, size: 480, ETA: 2:09:08
2025-07-31 13:32:21.822 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.910e-03, size: 352, ETA: 2:09:06
2025-07-31 13:32:24.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 6.904e-03, size: 576, ETA: 2:09:03
2025-07-31 13:32:27.614 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.137s, data_time: 0.027s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.899e-03, size: 416, ETA: 2:09:01
2025-07-31 13:32:28.966 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:32:29.003 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch159
2025-07-31 13:32:31.852 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.141s, data_time: 0.050s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.3, lr: 6.891e-03, size: 288, ETA: 2:08:57
2025-07-31 13:32:34.682 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.036s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.885e-03, size: 480, ETA: 2:08:55
2025-07-31 13:32:37.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.880e-03, size: 416, ETA: 2:08:52
2025-07-31 13:32:40.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.874e-03, size: 352, ETA: 2:08:49
2025-07-31 13:32:43.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 6.869e-03, size: 512, ETA: 2:08:46
2025-07-31 13:32:46.203 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.863e-03, size: 384, ETA: 2:08:43
2025-07-31 13:32:47.449 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:32:47.552 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch160
2025-07-31 13:32:50.438 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.855e-03, size: 512, ETA: 2:08:39
2025-07-31 13:32:53.363 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.036s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.850e-03, size: 416, ETA: 2:08:36
2025-07-31 13:32:56.346 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.135s, data_time: 0.009s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.844e-03, size: 480, ETA: 2:08:33
2025-07-31 13:32:59.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.839e-03, size: 544, ETA: 2:08:31
2025-07-31 13:33:02.189 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.833e-03, size: 416, ETA: 2:08:28
2025-07-31 13:33:05.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.828e-03, size: 288, ETA: 2:08:25
2025-07-31 13:33:06.387 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:33:12.785 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:33:20.178 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:33:24.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5182
2025-07-31 13:33:26.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4692
2025-07-31 13:33:26.389 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3110
2025-07-31 13:33:26.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4328
2025-07-31 13:33:26.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:33:26.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:33:26.392 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.518
2025-07-31 13:33:26.392 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.469
2025-07-31 13:33:26.393 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.311
2025-07-31 13:33:26.393 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.433
2025-07-31 13:33:26.394 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:33:26.394 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:33:26.394 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:33:26.395 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:33:26.395 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:33:26.396 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:33:26.396 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:33:26.396 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:33:26.397 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:33:32.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:33:37.987 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:33:44.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:33:50.013 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:33:56.196 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:34:01.772 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:34:07.672 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:34:13.348 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:34:19.139 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:34:19.139 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-31 13:34:19.139 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-31 13:34:19.139 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:34:19.170 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 1.05 ms, Average inference time: 2.51 ms

2025-07-31 13:34:19.174 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:34:19.207 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:34:19.244 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch161
2025-07-31 13:34:21.745 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.025s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.820e-03, size: 576, ETA: 2:08:20
2025-07-31 13:34:24.726 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 6.814e-03, size: 512, ETA: 2:08:18
2025-07-31 13:34:27.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.017s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.809e-03, size: 256, ETA: 2:08:15
2025-07-31 13:34:30.432 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.030s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.803e-03, size: 384, ETA: 2:08:13
2025-07-31 13:34:33.443 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.148s, data_time: 0.052s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 6.798e-03, size: 448, ETA: 2:08:11
2025-07-31 13:34:36.405 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.035s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.7, lr: 6.792e-03, size: 480, ETA: 2:08:09
2025-07-31 13:34:37.646 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:34:37.868 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch162
2025-07-31 13:34:40.752 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.784e-03, size: 320, ETA: 2:08:05
2025-07-31 13:34:43.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.005s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 6.778e-03, size: 384, ETA: 2:08:02
2025-07-31 13:34:46.597 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 6.773e-03, size: 320, ETA: 2:08:00
2025-07-31 13:34:49.487 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.767e-03, size: 352, ETA: 2:07:57
2025-07-31 13:34:52.430 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 5.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 6.762e-03, size: 544, ETA: 2:07:55
2025-07-31 13:34:55.438 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.756e-03, size: 288, ETA: 2:07:52
2025-07-31 13:34:56.670 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:34:56.728 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch163
2025-07-31 13:34:59.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 6.748e-03, size: 256, ETA: 2:07:49
2025-07-31 13:35:02.445 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.134s, data_time: 0.031s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 6.743e-03, size: 512, ETA: 2:07:46
2025-07-31 13:35:05.512 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.145s, data_time: 0.019s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 6.737e-03, size: 576, ETA: 2:07:44
2025-07-31 13:35:08.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.020s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 6.731e-03, size: 320, ETA: 2:07:41
2025-07-31 13:35:11.314 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.137s, data_time: 0.040s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 6.726e-03, size: 480, ETA: 2:07:38
2025-07-31 13:35:14.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.044s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 6.720e-03, size: 416, ETA: 2:07:35
2025-07-31 13:35:15.478 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:35:15.518 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch164
2025-07-31 13:35:18.421 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.143s, data_time: 0.052s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.712e-03, size: 480, ETA: 2:07:32
2025-07-31 13:35:21.405 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.060s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.707e-03, size: 512, ETA: 2:07:30
2025-07-31 13:35:24.298 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.140s, data_time: 0.049s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 6.701e-03, size: 448, ETA: 2:07:27
2025-07-31 13:35:27.185 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.137s, data_time: 0.026s, total_loss: 8.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 6.696e-03, size: 544, ETA: 2:07:25
2025-07-31 13:35:30.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 6.690e-03, size: 544, ETA: 2:07:22
2025-07-31 13:35:32.979 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 6.684e-03, size: 512, ETA: 2:07:19
2025-07-31 13:35:34.204 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:35:34.316 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch165
2025-07-31 13:35:37.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.008s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 6.676e-03, size: 288, ETA: 2:07:14
2025-07-31 13:35:40.213 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.048s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.671e-03, size: 288, ETA: 2:07:12
2025-07-31 13:35:43.022 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.137s, data_time: 0.047s, total_loss: 8.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 6.665e-03, size: 480, ETA: 2:07:09
2025-07-31 13:35:45.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.140s, data_time: 0.050s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.659e-03, size: 288, ETA: 2:07:07
2025-07-31 13:35:48.847 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.140s, data_time: 0.011s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.654e-03, size: 480, ETA: 2:07:04
2025-07-31 13:35:51.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 6.648e-03, size: 288, ETA: 2:07:01
2025-07-31 13:35:53.051 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:35:59.344 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:36:01.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:36:02.170 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5375
2025-07-31 13:36:02.482 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4268
2025-07-31 13:36:02.531 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3204
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4283
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.537
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.427
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.320
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.428
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:36:02.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:36:02.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:36:02.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:36:02.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:36:02.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:36:02.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:36:02.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:36:03.887 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:36:05.262 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:36:06.710 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:36:08.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:36:09.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:36:10.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:36:12.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:36:13.739 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:36:15.174 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:36:15.174 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-31 13:36:15.175 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-31 13:36:15.175 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:36:15.187 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.49 ms, Average NMS time: 1.02 ms, Average inference time: 2.51 ms

2025-07-31 13:36:15.189 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:36:15.228 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:36:15.277 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch166
2025-07-31 13:36:17.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.128s, data_time: 0.036s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.640e-03, size: 576, ETA: 2:06:57
2025-07-31 13:36:20.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.149s, data_time: 0.063s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.635e-03, size: 576, ETA: 2:06:55
2025-07-31 13:36:23.801 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.061s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.629e-03, size: 256, ETA: 2:06:52
2025-07-31 13:36:26.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.147s, data_time: 0.061s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.623e-03, size: 352, ETA: 2:06:50
2025-07-31 13:36:29.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.142s, data_time: 0.022s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 6.618e-03, size: 288, ETA: 2:06:48
2025-07-31 13:36:32.602 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.612e-03, size: 576, ETA: 2:06:45
2025-07-31 13:36:33.927 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:36:33.972 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch167
2025-07-31 13:36:36.835 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.030s, total_loss: 5.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 6.604e-03, size: 512, ETA: 2:06:41
2025-07-31 13:36:39.791 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.020s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.598e-03, size: 320, ETA: 2:06:38
2025-07-31 13:36:42.640 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 6.593e-03, size: 576, ETA: 2:06:35
2025-07-31 13:36:45.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.587e-03, size: 544, ETA: 2:06:31
2025-07-31 13:36:48.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.128s, data_time: 0.005s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.582e-03, size: 352, ETA: 2:06:28
2025-07-31 13:36:51.309 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.042s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 6.576e-03, size: 512, ETA: 2:06:25
2025-07-31 13:36:52.557 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:36:52.673 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch168
2025-07-31 13:36:55.640 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.568e-03, size: 544, ETA: 2:06:21
2025-07-31 13:36:58.605 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.562e-03, size: 544, ETA: 2:06:19
2025-07-31 13:37:01.556 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.557e-03, size: 512, ETA: 2:06:17
2025-07-31 13:37:04.440 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.551e-03, size: 256, ETA: 2:06:14
2025-07-31 13:37:07.348 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.545e-03, size: 416, ETA: 2:06:11
2025-07-31 13:37:10.230 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.540e-03, size: 288, ETA: 2:06:08
2025-07-31 13:37:11.500 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:37:11.552 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch169
2025-07-31 13:37:14.498 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 6.531e-03, size: 256, ETA: 2:06:04
2025-07-31 13:37:17.440 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.012s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 6.526e-03, size: 576, ETA: 2:06:01
2025-07-31 13:37:20.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.014s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.520e-03, size: 576, ETA: 2:05:58
2025-07-31 13:37:23.253 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.030s, total_loss: 6.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.515e-03, size: 288, ETA: 2:05:55
2025-07-31 13:37:26.083 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.509e-03, size: 416, ETA: 2:05:52
2025-07-31 13:37:29.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 6.503e-03, size: 480, ETA: 2:05:50
2025-07-31 13:37:30.435 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:37:30.482 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch170
2025-07-31 13:37:33.346 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 6.495e-03, size: 416, ETA: 2:05:45
2025-07-31 13:37:36.241 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 6.489e-03, size: 448, ETA: 2:05:43
2025-07-31 13:37:39.248 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.484e-03, size: 256, ETA: 2:05:40
2025-07-31 13:37:42.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 6.478e-03, size: 384, ETA: 2:05:37
2025-07-31 13:37:45.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.472e-03, size: 480, ETA: 2:05:34
2025-07-31 13:37:48.183 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 9.6, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 1.3, lr: 6.467e-03, size: 288, ETA: 2:05:32
2025-07-31 13:37:49.554 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:37:56.116 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:38:03.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:38:07.221 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4349
2025-07-31 13:38:08.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4817
2025-07-31 13:38:08.400 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2193
2025-07-31 13:38:08.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3786
2025-07-31 13:38:08.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:38:08.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:38:08.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.435
2025-07-31 13:38:08.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.482
2025-07-31 13:38:08.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.219
2025-07-31 13:38:08.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.379
2025-07-31 13:38:08.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:38:08.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:38:08.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:38:08.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:38:08.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:38:08.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:38:08.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:38:08.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:38:08.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:38:14.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:38:19.894 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:38:25.704 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:38:31.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:38:36.888 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:38:42.612 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:38:47.672 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:38:53.195 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:38:58.663 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:38:58.663 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-07-31 13:38:58.663 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.38
2025-07-31 13:38:58.663 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:38:58.698 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 1.02 ms, Average inference time: 2.43 ms

2025-07-31 13:38:58.707 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:38:58.742 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:38:58.791 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch171
2025-07-31 13:39:01.367 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.031s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 6.459e-03, size: 576, ETA: 2:05:27
2025-07-31 13:39:04.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.144s, data_time: 0.020s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 6.453e-03, size: 544, ETA: 2:05:25
2025-07-31 13:39:07.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.029s, total_loss: 7.2, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.447e-03, size: 320, ETA: 2:05:23
2025-07-31 13:39:10.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.140s, data_time: 0.029s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.442e-03, size: 448, ETA: 2:05:20
2025-07-31 13:39:13.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.145s, data_time: 0.033s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.436e-03, size: 320, ETA: 2:05:18
2025-07-31 13:39:15.979 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.013s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.430e-03, size: 448, ETA: 2:05:15
2025-07-31 13:39:17.217 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:39:17.401 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch172
2025-07-31 13:39:20.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.033s, total_loss: 5.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.8, lr: 6.422e-03, size: 320, ETA: 2:05:11
2025-07-31 13:39:23.120 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.037s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 6.416e-03, size: 576, ETA: 2:05:09
2025-07-31 13:39:26.118 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.147s, data_time: 0.064s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 6.411e-03, size: 480, ETA: 2:05:07
2025-07-31 13:39:29.163 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.151s, data_time: 0.063s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 6.405e-03, size: 320, ETA: 2:05:05
2025-07-31 13:39:32.122 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.146s, data_time: 0.060s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 6.399e-03, size: 288, ETA: 2:05:03
2025-07-31 13:39:35.198 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.152s, data_time: 0.066s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.394e-03, size: 384, ETA: 2:05:01
2025-07-31 13:39:36.462 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:39:36.503 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch173
2025-07-31 13:39:39.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.148s, data_time: 0.062s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 6.385e-03, size: 512, ETA: 2:04:57
2025-07-31 13:39:42.495 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.150s, data_time: 0.060s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.380e-03, size: 480, ETA: 2:04:55
2025-07-31 13:39:45.540 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.151s, data_time: 0.068s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.374e-03, size: 480, ETA: 2:04:53
2025-07-31 13:39:48.470 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.144s, data_time: 0.055s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.368e-03, size: 256, ETA: 2:04:51
2025-07-31 13:39:51.504 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.148s, data_time: 0.021s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.363e-03, size: 320, ETA: 2:04:49
2025-07-31 13:39:54.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.010s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 6.357e-03, size: 512, ETA: 2:04:46
2025-07-31 13:39:55.658 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:39:55.827 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch174
2025-07-31 13:39:58.796 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.349e-03, size: 288, ETA: 2:04:43
2025-07-31 13:40:01.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.144s, data_time: 0.003s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.343e-03, size: 384, ETA: 2:04:41
2025-07-31 13:40:04.751 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.141s, data_time: 0.007s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 6.337e-03, size: 512, ETA: 2:04:38
2025-07-31 13:40:07.782 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.143s, data_time: 0.010s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.331e-03, size: 288, ETA: 2:04:36
2025-07-31 13:40:10.779 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.013s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.326e-03, size: 416, ETA: 2:04:33
2025-07-31 13:40:13.633 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.039s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 1.0, lr: 6.320e-03, size: 288, ETA: 2:04:31
2025-07-31 13:40:14.942 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:40:14.984 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch175
2025-07-31 13:40:17.940 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.010s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.312e-03, size: 320, ETA: 2:04:27
2025-07-31 13:40:20.846 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.135s, data_time: 0.031s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 6.306e-03, size: 480, ETA: 2:04:24
2025-07-31 13:40:23.804 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.144s, data_time: 0.052s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.300e-03, size: 448, ETA: 2:04:22
2025-07-31 13:40:26.847 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.150s, data_time: 0.061s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 6.295e-03, size: 384, ETA: 2:04:20
2025-07-31 13:40:29.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.151s, data_time: 0.057s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.289e-03, size: 416, ETA: 2:04:18
2025-07-31 13:40:32.753 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.142s, data_time: 0.042s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.283e-03, size: 384, ETA: 2:04:16
2025-07-31 13:40:34.078 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:40:40.726 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:40:44.236 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:40:46.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5585
2025-07-31 13:40:46.938 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4935
2025-07-31 13:40:46.995 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2899
2025-07-31 13:40:46.996 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4473
2025-07-31 13:40:46.996 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:40:46.996 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:40:46.996 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.558
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.493
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.290
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.447
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:40:46.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:40:46.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:40:49.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:40:52.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:40:55.220 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:40:57.989 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:41:00.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:41:03.507 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:41:06.196 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:41:08.911 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:41:11.640 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:41:11.640 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-31 13:41:11.640 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-31 13:41:11.640 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:41:11.665 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 1.00 ms, Average inference time: 2.43 ms

2025-07-31 13:41:11.666 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:41:11.696 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:41:11.729 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch176
2025-07-31 13:41:14.305 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.127s, data_time: 0.038s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.275e-03, size: 448, ETA: 2:04:11
2025-07-31 13:41:17.302 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.017s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.269e-03, size: 480, ETA: 2:04:09
2025-07-31 13:41:20.134 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 6.263e-03, size: 576, ETA: 2:04:06
2025-07-31 13:41:23.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.258e-03, size: 512, ETA: 2:04:03
2025-07-31 13:41:26.002 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.252e-03, size: 416, ETA: 2:04:00
2025-07-31 13:41:28.904 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.019s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.246e-03, size: 320, ETA: 2:03:57
2025-07-31 13:41:30.128 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:41:30.226 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch177
2025-07-31 13:41:33.194 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.026s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.238e-03, size: 416, ETA: 2:03:53
2025-07-31 13:41:36.112 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.049s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.232e-03, size: 256, ETA: 2:03:50
2025-07-31 13:41:39.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.150s, data_time: 0.065s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.227e-03, size: 384, ETA: 2:03:48
2025-07-31 13:41:42.171 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 80/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.149s, data_time: 0.064s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.221e-03, size: 544, ETA: 2:03:46
2025-07-31 13:41:45.099 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.145s, data_time: 0.059s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.215e-03, size: 480, ETA: 2:03:44
2025-07-31 13:41:48.037 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.056s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.209e-03, size: 416, ETA: 2:03:41
2025-07-31 13:41:49.434 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:41:49.477 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch178
2025-07-31 13:41:52.367 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.143s, data_time: 0.058s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 6.201e-03, size: 480, ETA: 2:03:38
2025-07-31 13:41:55.224 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.053s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 6.195e-03, size: 576, ETA: 2:03:36
2025-07-31 13:41:58.071 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.190e-03, size: 352, ETA: 2:03:33
2025-07-31 13:42:01.068 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.144s, data_time: 0.004s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.184e-03, size: 512, ETA: 2:03:31
2025-07-31 13:42:03.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.139s, data_time: 0.028s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 6.178e-03, size: 576, ETA: 2:03:28
2025-07-31 13:42:06.938 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.061s, total_loss: 7.3, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.172e-03, size: 352, ETA: 2:03:26
2025-07-31 13:42:08.093 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:42:08.132 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch179
2025-07-31 13:42:11.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.145s, data_time: 0.063s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.164e-03, size: 512, ETA: 2:03:22
2025-07-31 13:42:13.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.053s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.158e-03, size: 288, ETA: 2:03:19
2025-07-31 13:42:16.915 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 60/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.144s, data_time: 0.061s, total_loss: 8.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.0, lr: 6.152e-03, size: 544, ETA: 2:03:17
2025-07-31 13:42:19.869 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.047s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.147e-03, size: 288, ETA: 2:03:14
2025-07-31 13:42:22.719 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.121s, data_time: 0.040s, total_loss: 7.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 6.141e-03, size: 288, ETA: 2:03:11
2025-07-31 13:42:25.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.048s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.135e-03, size: 256, ETA: 2:03:08
2025-07-31 13:42:27.051 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:42:27.090 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch180
2025-07-31 13:42:29.890 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.052s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.127e-03, size: 512, ETA: 2:03:05
2025-07-31 13:42:32.833 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.145s, data_time: 0.061s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.121e-03, size: 320, ETA: 2:03:03
2025-07-31 13:42:35.701 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.143s, data_time: 0.055s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 6.115e-03, size: 288, ETA: 2:03:01
2025-07-31 13:42:38.564 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.053s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.110e-03, size: 384, ETA: 2:02:58
2025-07-31 13:42:41.541 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.146s, data_time: 0.060s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 6.104e-03, size: 512, ETA: 2:02:55
2025-07-31 13:42:44.377 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.044s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.098e-03, size: 416, ETA: 2:02:53
2025-07-31 13:42:45.711 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:42:52.195 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:42:54.785 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:42:56.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5268
2025-07-31 13:42:56.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5044
2025-07-31 13:42:56.897 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3528
2025-07-31 13:42:56.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4613
2025-07-31 13:42:56.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:42:56.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:42:56.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.527
2025-07-31 13:42:56.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.504
2025-07-31 13:42:56.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.353
2025-07-31 13:42:56.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.461
2025-07-31 13:42:56.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:42:56.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:42:56.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:42:56.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:42:56.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:42:56.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:42:56.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:42:56.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:42:56.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:42:58.934 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:43:00.922 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:43:02.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:43:04.866 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:43:06.858 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:43:08.829 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:43:10.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:43:12.821 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:43:14.799 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:43:14.799 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-31 13:43:14.800 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-31 13:43:14.800 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:43:14.828 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.96 ms, Average inference time: 2.40 ms

2025-07-31 13:43:14.829 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:43:14.915 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:43:14.952 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch181
2025-07-31 13:43:17.443 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.118s, data_time: 0.023s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.090e-03, size: 288, ETA: 2:02:48
2025-07-31 13:43:20.413 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 40/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.019s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.084e-03, size: 288, ETA: 2:02:45
2025-07-31 13:43:23.320 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.144s, data_time: 0.012s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.078e-03, size: 288, ETA: 2:02:43
2025-07-31 13:43:26.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 6.072e-03, size: 448, ETA: 2:02:41
2025-07-31 13:43:29.204 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.030s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.067e-03, size: 448, ETA: 2:02:38
2025-07-31 13:43:32.157 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 120/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.146s, data_time: 0.061s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.061e-03, size: 256, ETA: 2:02:36
2025-07-31 13:43:33.487 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:43:33.530 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch182
2025-07-31 13:43:36.443 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.145s, data_time: 0.057s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.053e-03, size: 416, ETA: 2:02:33
2025-07-31 13:43:39.278 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.037s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 6.047e-03, size: 512, ETA: 2:02:30
2025-07-31 13:43:42.237 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.139s, data_time: 0.017s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.041e-03, size: 320, ETA: 2:02:27
2025-07-31 13:43:45.074 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.021s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 6.035e-03, size: 544, ETA: 2:02:24
2025-07-31 13:43:48.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 100/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.018s, total_loss: 9.5, iou_loss: 3.7, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 1.1, lr: 6.029e-03, size: 544, ETA: 2:02:22
2025-07-31 13:43:50.980 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.6, lr: 6.024e-03, size: 320, ETA: 2:02:19
2025-07-31 13:43:52.227 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:43:52.348 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch183
2025-07-31 13:43:55.238 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.041s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.015e-03, size: 320, ETA: 2:02:15
2025-07-31 13:43:58.166 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.049s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.009e-03, size: 544, ETA: 2:02:12
2025-07-31 13:44:01.086 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.129s, data_time: 0.029s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 6.004e-03, size: 448, ETA: 2:02:09
2025-07-31 13:44:04.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.037s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 5.998e-03, size: 512, ETA: 2:02:06
2025-07-31 13:44:06.964 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.143s, data_time: 0.054s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.992e-03, size: 256, ETA: 2:02:03
2025-07-31 13:44:09.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.139s, data_time: 0.052s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.986e-03, size: 352, ETA: 2:02:01
2025-07-31 13:44:11.185 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:44:11.224 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch184
2025-07-31 13:44:14.059 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.020s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.978e-03, size: 352, ETA: 2:01:57
2025-07-31 13:44:16.970 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.012s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.972e-03, size: 320, ETA: 2:01:54
2025-07-31 13:44:19.979 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.023s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 5.966e-03, size: 416, ETA: 2:01:51
2025-07-31 13:44:22.990 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.961e-03, size: 320, ETA: 2:01:48
2025-07-31 13:44:25.830 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.012s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.955e-03, size: 480, ETA: 2:01:45
2025-07-31 13:44:28.689 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.020s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.949e-03, size: 352, ETA: 2:01:42
2025-07-31 13:44:29.938 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:44:30.088 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch185
2025-07-31 13:44:32.920 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.139s, data_time: 0.050s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 5.941e-03, size: 480, ETA: 2:01:38
2025-07-31 13:44:35.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.050s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 5.935e-03, size: 512, ETA: 2:01:36
2025-07-31 13:44:38.625 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.143s, data_time: 0.049s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.929e-03, size: 288, ETA: 2:01:33
2025-07-31 13:44:41.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.019s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 5.923e-03, size: 256, ETA: 2:01:31
2025-07-31 13:44:44.426 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.143s, data_time: 0.006s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.917e-03, size: 288, ETA: 2:01:28
2025-07-31 13:44:47.257 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.912e-03, size: 544, ETA: 2:01:26
2025-07-31 13:44:48.584 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:44:55.085 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:44:56.527 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:44:57.337 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4864
2025-07-31 13:44:57.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4510
2025-07-31 13:44:57.592 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2836
2025-07-31 13:44:57.593 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4070
2025-07-31 13:44:57.593 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:44:57.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:44:57.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.486
2025-07-31 13:44:57.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.451
2025-07-31 13:44:57.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.284
2025-07-31 13:44:57.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.407
2025-07-31 13:44:57.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:44:57.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:44:57.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:44:57.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:44:57.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:44:57.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:44:57.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:44:57.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:44:57.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:44:58.757 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:44:59.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:45:00.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:45:01.869 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:45:02.888 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:45:03.919 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:45:05.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:45:06.226 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:45:07.256 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:45:07.256 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-31 13:45:07.257 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-07-31 13:45:07.257 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:45:07.265 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.96 ms, Average inference time: 2.35 ms

2025-07-31 13:45:07.266 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:45:07.287 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:45:07.319 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch186
2025-07-31 13:45:09.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 20/129, gpu mem: 1723Mb, mem: 76.9Gb, iter_time: 0.125s, data_time: 0.040s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.903e-03, size: 320, ETA: 2:01:21
2025-07-31 13:45:12.744 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.050s, total_loss: 5.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.897e-03, size: 288, ETA: 2:01:19
2025-07-31 13:45:15.627 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.019s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.892e-03, size: 480, ETA: 2:01:16
2025-07-31 13:45:18.610 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.005s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.886e-03, size: 416, ETA: 2:01:13
2025-07-31 13:45:21.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.006s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.880e-03, size: 256, ETA: 2:01:10
2025-07-31 13:45:24.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 5.874e-03, size: 384, ETA: 2:01:07
2025-07-31 13:45:25.724 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:45:25.913 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch187
2025-07-31 13:45:28.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.866e-03, size: 256, ETA: 2:01:03
2025-07-31 13:45:31.629 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.860e-03, size: 384, ETA: 2:01:00
2025-07-31 13:45:34.600 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.009s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 5.854e-03, size: 416, ETA: 2:00:57
2025-07-31 13:45:37.650 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.848e-03, size: 352, ETA: 2:00:55
2025-07-31 13:45:40.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.843e-03, size: 384, ETA: 2:00:51
2025-07-31 13:45:43.489 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.837e-03, size: 256, ETA: 2:00:48
2025-07-31 13:45:44.821 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:45:44.877 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch188
2025-07-31 13:45:47.723 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.828e-03, size: 480, ETA: 2:00:44
2025-07-31 13:45:50.705 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.822e-03, size: 352, ETA: 2:00:41
2025-07-31 13:45:53.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.1, lr: 5.817e-03, size: 480, ETA: 2:00:38
2025-07-31 13:45:56.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.011s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 5.811e-03, size: 544, ETA: 2:00:36
2025-07-31 13:45:59.540 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.805e-03, size: 416, ETA: 2:00:33
2025-07-31 13:46:02.524 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.141s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.799e-03, size: 448, ETA: 2:00:30
2025-07-31 13:46:03.776 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:46:03.901 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch189
2025-07-31 13:46:06.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.009s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.791e-03, size: 480, ETA: 2:00:26
2025-07-31 13:46:09.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.785e-03, size: 256, ETA: 2:00:24
2025-07-31 13:46:12.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.025s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.779e-03, size: 480, ETA: 2:00:21
2025-07-31 13:46:15.432 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.024s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 5.773e-03, size: 352, ETA: 2:00:18
2025-07-31 13:46:18.279 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.017s, total_loss: 5.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.767e-03, size: 320, ETA: 2:00:15
2025-07-31 13:46:21.246 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.762e-03, size: 384, ETA: 2:00:12
2025-07-31 13:46:22.506 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:46:22.562 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch190
2025-07-31 13:46:25.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.009s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.753e-03, size: 480, ETA: 2:00:08
2025-07-31 13:46:28.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.008s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 5.747e-03, size: 416, ETA: 2:00:06
2025-07-31 13:46:31.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.011s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.4, lr: 5.742e-03, size: 416, ETA: 2:00:03
2025-07-31 13:46:34.088 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.020s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.736e-03, size: 416, ETA: 2:00:00
2025-07-31 13:46:36.972 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.018s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.730e-03, size: 384, ETA: 1:59:57
2025-07-31 13:46:39.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.724e-03, size: 320, ETA: 1:59:54
2025-07-31 13:46:41.277 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:46:47.668 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:46:49.919 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:46:51.281 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5590
2025-07-31 13:46:51.616 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4701
2025-07-31 13:46:51.665 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2935
2025-07-31 13:46:51.665 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4409
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.559
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.470
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.293
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.441
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:46:51.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:46:51.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:46:51.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:46:51.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:46:51.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:46:53.407 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:46:55.128 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:46:56.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:46:58.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:47:00.203 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:47:01.976 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:47:03.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:47:05.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:47:07.160 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:47:07.160 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-31 13:47:07.161 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-31 13:47:07.161 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:47:07.185 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 0.96 ms, Average inference time: 2.37 ms

2025-07-31 13:47:07.187 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:47:07.213 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:47:07.262 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch191
2025-07-31 13:47:09.808 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.127s, data_time: 0.035s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.716e-03, size: 416, ETA: 1:59:50
2025-07-31 13:47:12.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.038s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.1, lr: 5.710e-03, size: 288, ETA: 1:59:47
2025-07-31 13:47:15.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.019s, total_loss: 6.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.704e-03, size: 288, ETA: 1:59:45
2025-07-31 13:47:18.497 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.054s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.698e-03, size: 512, ETA: 1:59:42
2025-07-31 13:47:21.400 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.144s, data_time: 0.056s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 5.692e-03, size: 384, ETA: 1:59:40
2025-07-31 13:47:24.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.050s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.686e-03, size: 352, ETA: 1:59:37
2025-07-31 13:47:25.721 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:47:25.785 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch192
2025-07-31 13:47:28.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.141s, data_time: 0.047s, total_loss: 8.6, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 5.678e-03, size: 448, ETA: 1:59:34
2025-07-31 13:47:31.624 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.024s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 5.672e-03, size: 448, ETA: 1:59:31
2025-07-31 13:47:34.589 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.147s, data_time: 0.058s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.666e-03, size: 320, ETA: 1:59:29
2025-07-31 13:47:37.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.150s, data_time: 0.060s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.661e-03, size: 320, ETA: 1:59:27
2025-07-31 13:47:40.510 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.139s, data_time: 0.044s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.655e-03, size: 544, ETA: 1:59:24
2025-07-31 13:47:43.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 5.649e-03, size: 480, ETA: 1:59:21
2025-07-31 13:47:44.749 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:47:44.890 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch193
2025-07-31 13:47:47.842 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 5.640e-03, size: 384, ETA: 1:59:17
2025-07-31 13:47:50.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.635e-03, size: 576, ETA: 1:59:14
2025-07-31 13:47:53.677 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.014s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.629e-03, size: 448, ETA: 1:59:11
2025-07-31 13:47:56.622 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.009s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.623e-03, size: 256, ETA: 1:59:08
2025-07-31 13:47:59.609 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.018s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.617e-03, size: 512, ETA: 1:59:06
2025-07-31 13:48:02.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.126s, data_time: 0.017s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 5.611e-03, size: 576, ETA: 1:59:02
2025-07-31 13:48:03.801 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:48:03.853 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch194
2025-07-31 13:48:06.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.603e-03, size: 384, ETA: 1:58:58
2025-07-31 13:48:09.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.597e-03, size: 480, ETA: 1:58:55
2025-07-31 13:48:12.658 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.141s, data_time: 0.035s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.591e-03, size: 480, ETA: 1:58:53
2025-07-31 13:48:15.604 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.013s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.585e-03, size: 416, ETA: 1:58:50
2025-07-31 13:48:18.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.579e-03, size: 416, ETA: 1:58:47
2025-07-31 13:48:21.544 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.023s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.574e-03, size: 544, ETA: 1:58:44
2025-07-31 13:48:22.794 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:48:22.927 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch195
2025-07-31 13:48:25.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.042s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.565e-03, size: 512, ETA: 1:58:40
2025-07-31 13:48:28.607 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.128s, data_time: 0.023s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.559e-03, size: 256, ETA: 1:58:37
2025-07-31 13:48:31.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.020s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.553e-03, size: 256, ETA: 1:58:34
2025-07-31 13:48:34.559 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.129s, data_time: 0.030s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 5.547e-03, size: 480, ETA: 1:58:31
2025-07-31 13:48:37.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.542e-03, size: 256, ETA: 1:58:28
2025-07-31 13:48:40.424 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.536e-03, size: 384, ETA: 1:58:25
2025-07-31 13:48:41.689 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:48:48.061 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:48:51.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:48:53.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5642
2025-07-31 13:48:54.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5148
2025-07-31 13:48:54.104 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2377
2025-07-31 13:48:54.104 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4389
2025-07-31 13:48:54.104 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:48:54.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:48:54.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-07-31 13:48:54.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.515
2025-07-31 13:48:54.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.238
2025-07-31 13:48:54.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.439
2025-07-31 13:48:54.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:48:54.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:48:54.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:48:54.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:48:54.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:48:54.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:48:54.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:48:54.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:48:54.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:48:56.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:48:59.649 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:49:02.332 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:49:05.067 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:49:07.767 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:49:10.506 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:49:13.195 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:49:15.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:49:18.591 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:49:18.591 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-31 13:49:18.591 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-31 13:49:18.592 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:49:18.620 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 1.00 ms, Average inference time: 2.42 ms

2025-07-31 13:49:18.621 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:49:18.653 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:49:18.685 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch196
2025-07-31 13:49:21.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.121s, data_time: 0.024s, total_loss: 8.6, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 5.527e-03, size: 352, ETA: 1:58:20
2025-07-31 13:49:24.144 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.521e-03, size: 320, ETA: 1:58:17
2025-07-31 13:49:27.049 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.014s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 5.516e-03, size: 512, ETA: 1:58:14
2025-07-31 13:49:29.898 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.031s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.510e-03, size: 576, ETA: 1:58:11
2025-07-31 13:49:32.874 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.028s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.504e-03, size: 256, ETA: 1:58:09
2025-07-31 13:49:35.801 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.498e-03, size: 256, ETA: 1:58:06
2025-07-31 13:49:37.096 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:49:37.208 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch197
2025-07-31 13:49:40.192 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.6, lr: 5.490e-03, size: 416, ETA: 1:58:02
2025-07-31 13:49:43.137 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.484e-03, size: 320, ETA: 1:57:59
2025-07-31 13:49:46.230 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 5.478e-03, size: 352, ETA: 1:57:56
2025-07-31 13:49:49.023 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.124s, data_time: 0.011s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.472e-03, size: 288, ETA: 1:57:52
2025-07-31 13:49:52.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.466e-03, size: 256, ETA: 1:57:50
2025-07-31 13:49:54.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.009s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.460e-03, size: 448, ETA: 1:57:47
2025-07-31 13:49:56.090 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:49:56.264 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch198
2025-07-31 13:49:59.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.046s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.452e-03, size: 544, ETA: 1:57:42
2025-07-31 13:50:02.060 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.446e-03, size: 320, ETA: 1:57:40
2025-07-31 13:50:05.003 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.010s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.440e-03, size: 416, ETA: 1:57:37
2025-07-31 13:50:07.989 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.146s, data_time: 0.012s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.434e-03, size: 416, ETA: 1:57:35
2025-07-31 13:50:10.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.147s, data_time: 0.056s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.428e-03, size: 448, ETA: 1:57:33
2025-07-31 13:50:13.811 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.139s, data_time: 0.044s, total_loss: 8.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.3, lr: 5.423e-03, size: 576, ETA: 1:57:30
2025-07-31 13:50:15.077 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:50:15.111 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch199
2025-07-31 13:50:18.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.145s, data_time: 0.054s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.414e-03, size: 480, ETA: 1:57:26
2025-07-31 13:50:21.006 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.146s, data_time: 0.062s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 5.408e-03, size: 480, ETA: 1:57:24
2025-07-31 13:50:23.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.055s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.402e-03, size: 320, ETA: 1:57:21
2025-07-31 13:50:26.746 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.145s, data_time: 0.059s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.397e-03, size: 512, ETA: 1:57:19
2025-07-31 13:50:29.764 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.149s, data_time: 0.057s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 5.391e-03, size: 480, ETA: 1:57:17
2025-07-31 13:50:32.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.035s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.385e-03, size: 256, ETA: 1:57:14
2025-07-31 13:50:33.903 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:50:34.062 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch200
2025-07-31 13:50:36.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 4.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.6, cls_loss: 0.8, lr: 5.376e-03, size: 256, ETA: 1:57:10
2025-07-31 13:50:39.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.370e-03, size: 416, ETA: 1:57:08
2025-07-31 13:50:42.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 5.365e-03, size: 256, ETA: 1:57:05
2025-07-31 13:50:45.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.359e-03, size: 352, ETA: 1:57:03
2025-07-31 13:50:48.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.353e-03, size: 288, ETA: 1:57:00
2025-07-31 13:50:51.611 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.347e-03, size: 384, ETA: 1:56:57
2025-07-31 13:50:52.894 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:50:59.323 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:51:01.486 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:51:02.992 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5316
2025-07-31 13:51:03.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4911
2025-07-31 13:51:03.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3151
2025-07-31 13:51:03.326 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4459
2025-07-31 13:51:03.326 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:51:03.326 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:51:03.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.532
2025-07-31 13:51:03.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.491
2025-07-31 13:51:03.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.315
2025-07-31 13:51:03.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.446
2025-07-31 13:51:03.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:51:03.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:51:03.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:51:03.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:51:03.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:51:03.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:51:03.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:51:03.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:51:03.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:51:05.111 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:51:07.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:51:08.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:51:10.622 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:51:12.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:51:14.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:51:15.940 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:51:17.729 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:51:19.535 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:51:19.535 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-31 13:51:19.535 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-31 13:51:19.535 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:51:19.562 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 1.01 ms, Average inference time: 2.46 ms

2025-07-31 13:51:19.567 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:51:19.598 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:51:19.631 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch201
2025-07-31 13:51:22.241 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.129s, data_time: 0.047s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.339e-03, size: 480, ETA: 1:56:53
2025-07-31 13:51:25.099 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.141s, data_time: 0.053s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 5.333e-03, size: 448, ETA: 1:56:51
2025-07-31 13:51:28.055 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.047s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.327e-03, size: 480, ETA: 1:56:48
2025-07-31 13:51:30.916 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.006s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.321e-03, size: 256, ETA: 1:56:45
2025-07-31 13:51:33.887 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.146s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.315e-03, size: 320, ETA: 1:56:43
2025-07-31 13:51:36.888 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.309e-03, size: 320, ETA: 1:56:41
2025-07-31 13:51:38.130 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:51:38.301 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch202
2025-07-31 13:51:41.202 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 5.301e-03, size: 384, ETA: 1:56:37
2025-07-31 13:51:44.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.295e-03, size: 512, ETA: 1:56:35
2025-07-31 13:51:47.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.145s, data_time: 0.030s, total_loss: 7.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.289e-03, size: 288, ETA: 1:56:32
2025-07-31 13:51:49.975 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.049s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.283e-03, size: 448, ETA: 1:56:30
2025-07-31 13:51:52.890 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.010s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.277e-03, size: 256, ETA: 1:56:27
2025-07-31 13:51:55.782 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.141s, data_time: 0.051s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.272e-03, size: 480, ETA: 1:56:25
2025-07-31 13:51:57.178 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:51:57.233 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch203
2025-07-31 13:52:00.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.143s, data_time: 0.058s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 5.263e-03, size: 480, ETA: 1:56:21
2025-07-31 13:52:02.979 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.055s, total_loss: 7.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.257e-03, size: 288, ETA: 1:56:19
2025-07-31 13:52:05.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.146s, data_time: 0.052s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.251e-03, size: 544, ETA: 1:56:16
2025-07-31 13:52:08.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.045s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.245e-03, size: 384, ETA: 1:56:14
2025-07-31 13:52:11.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.022s, total_loss: 7.7, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.240e-03, size: 288, ETA: 1:56:11
2025-07-31 13:52:14.618 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.144s, data_time: 0.021s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.234e-03, size: 544, ETA: 1:56:09
2025-07-31 13:52:15.870 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:52:16.016 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch204
2025-07-31 13:52:18.988 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.044s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.225e-03, size: 416, ETA: 1:56:05
2025-07-31 13:52:21.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.022s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 5.219e-03, size: 480, ETA: 1:56:02
2025-07-31 13:52:24.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.049s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 5.214e-03, size: 576, ETA: 1:56:00
2025-07-31 13:52:27.728 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 5.208e-03, size: 288, ETA: 1:55:57
2025-07-31 13:52:30.627 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.142s, data_time: 0.005s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.202e-03, size: 384, ETA: 1:55:55
2025-07-31 13:52:33.629 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.004s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 5.196e-03, size: 384, ETA: 1:55:52
2025-07-31 13:52:34.929 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:52:35.131 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch205
2025-07-31 13:52:37.898 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.124s, data_time: 0.010s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.187e-03, size: 416, ETA: 1:55:48
2025-07-31 13:52:40.889 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.147s, data_time: 0.023s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 5.182e-03, size: 256, ETA: 1:55:45
2025-07-31 13:52:43.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 5.176e-03, size: 544, ETA: 1:55:43
2025-07-31 13:52:46.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.020s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.170e-03, size: 576, ETA: 1:55:40
2025-07-31 13:52:49.504 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.037s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.164e-03, size: 448, ETA: 1:55:37
2025-07-31 13:52:52.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.045s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.158e-03, size: 544, ETA: 1:55:35
2025-07-31 13:52:53.716 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:53:00.279 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:53:02.431 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:53:03.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5441
2025-07-31 13:53:03.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4743
2025-07-31 13:53:04.054 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2692
2025-07-31 13:53:04.055 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4292
2025-07-31 13:53:04.055 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:53:04.055 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:53:04.055 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.544
2025-07-31 13:53:04.055 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.474
2025-07-31 13:53:04.055 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.269
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.429
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:53:04.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:53:05.709 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:53:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:53:09.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:53:10.774 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:53:12.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:53:14.230 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:53:15.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:53:17.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:53:19.278 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:53:19.278 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-31 13:53:19.278 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-31 13:53:19.278 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:53:19.296 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 1.00 ms, Average inference time: 2.45 ms

2025-07-31 13:53:19.297 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:53:19.324 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:53:19.379 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch206
2025-07-31 13:53:21.944 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.124s, data_time: 0.039s, total_loss: 7.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 5.150e-03, size: 320, ETA: 1:55:30
2025-07-31 13:53:24.892 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.143s, data_time: 0.048s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.144e-03, size: 512, ETA: 1:55:28
2025-07-31 13:53:27.841 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.025s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.138e-03, size: 544, ETA: 1:55:25
2025-07-31 13:53:30.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.049s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 5.132e-03, size: 544, ETA: 1:55:22
2025-07-31 13:53:33.790 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.049s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.7, lr: 5.126e-03, size: 448, ETA: 1:55:19
2025-07-31 13:53:36.629 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.046s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.120e-03, size: 384, ETA: 1:55:16
2025-07-31 13:53:37.941 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:53:38.063 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch207
2025-07-31 13:53:41.025 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.033s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.112e-03, size: 320, ETA: 1:55:12
2025-07-31 13:53:43.975 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.032s, total_loss: 9.9, iou_loss: 3.9, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.3, lr: 5.106e-03, size: 480, ETA: 1:55:09
2025-07-31 13:53:47.032 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.010s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.100e-03, size: 480, ETA: 1:55:06
2025-07-31 13:53:49.936 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.126s, data_time: 0.015s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 5.094e-03, size: 544, ETA: 1:55:03
2025-07-31 13:53:53.077 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.089e-03, size: 288, ETA: 1:55:00
2025-07-31 13:53:56.023 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.083e-03, size: 512, ETA: 1:54:57
2025-07-31 13:53:57.234 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:53:57.277 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch208
2025-07-31 13:54:00.126 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.004s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.074e-03, size: 576, ETA: 1:54:53
2025-07-31 13:54:03.081 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.035s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.068e-03, size: 448, ETA: 1:54:50
2025-07-31 13:54:05.969 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.062e-03, size: 448, ETA: 1:54:47
2025-07-31 13:54:08.889 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.017s, total_loss: 8.2, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 5.057e-03, size: 512, ETA: 1:54:44
2025-07-31 13:54:11.771 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.034s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.051e-03, size: 416, ETA: 1:54:42
2025-07-31 13:54:14.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.045s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.045e-03, size: 576, ETA: 1:54:39
2025-07-31 13:54:15.894 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:54:16.064 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch209
2025-07-31 13:54:18.903 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.054s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.036e-03, size: 256, ETA: 1:54:35
2025-07-31 13:54:21.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.0Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 7.7, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 5.031e-03, size: 256, ETA: 1:54:32
2025-07-31 13:54:24.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.035s, total_loss: 5.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.7, lr: 5.025e-03, size: 288, ETA: 1:54:30
2025-07-31 13:54:27.739 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.019e-03, size: 416, ETA: 1:54:27
2025-07-31 13:54:30.565 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.033s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.013e-03, size: 352, ETA: 1:54:24
2025-07-31 13:54:33.625 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.028s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.007e-03, size: 320, ETA: 1:54:21
2025-07-31 13:54:34.935 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:54:34.994 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch210
2025-07-31 13:54:37.843 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.999e-03, size: 384, ETA: 1:54:17
2025-07-31 13:54:40.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.142s, data_time: 0.005s, total_loss: 4.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 4.993e-03, size: 288, ETA: 1:54:15
2025-07-31 13:54:43.763 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.005s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.987e-03, size: 352, ETA: 1:54:12
2025-07-31 13:54:46.636 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 4.981e-03, size: 544, ETA: 1:54:09
2025-07-31 13:54:49.686 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.975e-03, size: 512, ETA: 1:54:06
2025-07-31 13:54:52.684 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 4.969e-03, size: 480, ETA: 1:54:03
2025-07-31 13:54:54.042 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:55:00.496 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:55:01.592 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:55:02.254 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5252
2025-07-31 13:55:02.381 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4430
2025-07-31 13:55:02.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2743
2025-07-31 13:55:02.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4142
2025-07-31 13:55:02.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:55:02.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:55:02.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.525
2025-07-31 13:55:02.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.443
2025-07-31 13:55:02.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.274
2025-07-31 13:55:02.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.414
2025-07-31 13:55:02.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:55:02.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:55:02.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:55:02.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:55:02.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:55:02.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:55:02.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:55:02.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:55:02.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:55:03.202 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:55:03.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:55:04.795 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:55:05.565 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:55:06.406 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:55:07.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:55:07.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:55:08.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:55:09.551 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:55:09.551 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-31 13:55:09.551 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-07-31 13:55:09.551 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:55:09.560 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.99 ms, Average inference time: 2.43 ms

2025-07-31 13:55:09.561 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:55:09.583 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:55:09.616 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch211
2025-07-31 13:55:12.092 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.025s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 4.961e-03, size: 480, ETA: 1:53:59
2025-07-31 13:55:15.030 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.029s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 4.955e-03, size: 320, ETA: 1:53:56
2025-07-31 13:55:18.017 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.144s, data_time: 0.031s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 4.949e-03, size: 576, ETA: 1:53:54
2025-07-31 13:55:20.961 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.145s, data_time: 0.023s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.943e-03, size: 512, ETA: 1:53:52
2025-07-31 13:55:23.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.146s, data_time: 0.061s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 4.938e-03, size: 576, ETA: 1:53:49
2025-07-31 13:55:27.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.155s, data_time: 0.068s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 4.932e-03, size: 416, ETA: 1:53:47
2025-07-31 13:55:28.464 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:55:28.598 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch212
2025-07-31 13:55:31.303 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.045s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 4.923e-03, size: 288, ETA: 1:53:43
2025-07-31 13:55:34.184 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.138s, data_time: 0.043s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 4.917e-03, size: 352, ETA: 1:53:41
2025-07-31 13:55:37.123 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.033s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 4.912e-03, size: 448, ETA: 1:53:38
2025-07-31 13:55:40.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.012s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 4.906e-03, size: 480, ETA: 1:53:36
2025-07-31 13:55:43.073 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.142s, data_time: 0.009s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 4.900e-03, size: 416, ETA: 1:53:33
2025-07-31 13:55:45.928 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.025s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 4.894e-03, size: 512, ETA: 1:53:31
2025-07-31 13:55:47.212 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:55:47.264 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch213
2025-07-31 13:55:50.070 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.047s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 4.886e-03, size: 320, ETA: 1:53:27
2025-07-31 13:55:53.001 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.145s, data_time: 0.060s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 4.880e-03, size: 416, ETA: 1:53:24
2025-07-31 13:55:55.894 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.143s, data_time: 0.056s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 4.874e-03, size: 384, ETA: 1:53:22
2025-07-31 13:55:58.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.143s, data_time: 0.057s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 4.868e-03, size: 448, ETA: 1:53:19
2025-07-31 13:56:01.694 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.014s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.9, lr: 4.862e-03, size: 384, ETA: 1:53:16
2025-07-31 13:56:04.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.009s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.856e-03, size: 480, ETA: 1:53:14
2025-07-31 13:56:05.846 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:56:05.987 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch214
2025-07-31 13:56:08.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.029s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.848e-03, size: 288, ETA: 1:53:10
2025-07-31 13:56:11.743 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.142s, data_time: 0.033s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.842e-03, size: 480, ETA: 1:53:07
2025-07-31 13:56:14.627 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.036s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 4.836e-03, size: 288, ETA: 1:53:04
2025-07-31 13:56:17.606 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.138s, data_time: 0.046s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 4.830e-03, size: 576, ETA: 1:53:01
2025-07-31 13:56:20.589 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.138s, data_time: 0.019s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 4.825e-03, size: 480, ETA: 1:52:59
2025-07-31 13:56:23.408 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 4.819e-03, size: 320, ETA: 1:52:56
2025-07-31 13:56:24.669 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:56:24.711 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch215
2025-07-31 13:56:27.644 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.145s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 4.810e-03, size: 512, ETA: 1:52:52
2025-07-31 13:56:30.521 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.138s, data_time: 0.021s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.804e-03, size: 384, ETA: 1:52:50
2025-07-31 13:56:33.496 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.145s, data_time: 0.004s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 4.799e-03, size: 320, ETA: 1:52:47
2025-07-31 13:56:36.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 4.793e-03, size: 384, ETA: 1:52:45
2025-07-31 13:56:39.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.138s, data_time: 0.004s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 4.787e-03, size: 256, ETA: 1:52:42
2025-07-31 13:56:42.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.143s, data_time: 0.013s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 4.781e-03, size: 352, ETA: 1:52:39
2025-07-31 13:56:43.599 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:56:50.180 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:56:51.891 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:56:52.854 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5610
2025-07-31 13:56:53.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4522
2025-07-31 13:56:53.222 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2999
2025-07-31 13:56:53.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4377
2025-07-31 13:56:53.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:56:53.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:56:53.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.561
2025-07-31 13:56:53.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.452
2025-07-31 13:56:53.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.300
2025-07-31 13:56:53.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.438
2025-07-31 13:56:53.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:56:53.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:56:53.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:56:53.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:56:53.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:56:53.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:56:53.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:56:53.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:56:53.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:56:54.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:56:55.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:56:57.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:56:58.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:56:59.682 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:57:00.910 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:57:02.110 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:57:03.376 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:57:04.611 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:57:04.611 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-31 13:57:04.611 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-31 13:57:04.611 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:57:04.619 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 0.98 ms, Average inference time: 2.39 ms

2025-07-31 13:57:04.620 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:57:04.647 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:57:04.680 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch216
2025-07-31 13:57:07.213 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.027s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 4.773e-03, size: 256, ETA: 1:52:35
2025-07-31 13:57:10.193 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.050s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 4.767e-03, size: 352, ETA: 1:52:33
2025-07-31 13:57:13.197 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.040s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.761e-03, size: 416, ETA: 1:52:30
2025-07-31 13:57:16.184 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.147s, data_time: 0.050s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 4.755e-03, size: 576, ETA: 1:52:28
2025-07-31 13:57:19.109 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.025s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.749e-03, size: 480, ETA: 1:52:25
2025-07-31 13:57:21.982 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.744e-03, size: 512, ETA: 1:52:22
2025-07-31 13:57:23.208 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:57:23.292 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch217
2025-07-31 13:57:26.239 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.011s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.735e-03, size: 480, ETA: 1:52:18
2025-07-31 13:57:29.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.027s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.729e-03, size: 544, ETA: 1:52:15
2025-07-31 13:57:32.070 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.018s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.724e-03, size: 288, ETA: 1:52:12
2025-07-31 13:57:35.063 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.039s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.718e-03, size: 512, ETA: 1:52:09
2025-07-31 13:57:37.893 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.023s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 4.712e-03, size: 320, ETA: 1:52:06
2025-07-31 13:57:40.836 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.125s, data_time: 0.026s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 4.706e-03, size: 320, ETA: 1:52:03
2025-07-31 13:57:42.098 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:57:42.157 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch218
2025-07-31 13:57:45.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.011s, total_loss: 7.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 4.698e-03, size: 288, ETA: 1:51:59
2025-07-31 13:57:47.956 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.020s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.692e-03, size: 352, ETA: 1:51:56
2025-07-31 13:57:50.902 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.146s, data_time: 0.053s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.686e-03, size: 448, ETA: 1:51:54
2025-07-31 13:57:53.779 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.055s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 4.680e-03, size: 320, ETA: 1:51:51
2025-07-31 13:57:56.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.013s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.674e-03, size: 288, ETA: 1:51:49
2025-07-31 13:57:59.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.009s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.669e-03, size: 512, ETA: 1:51:46
2025-07-31 13:58:00.941 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:58:01.115 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch219
2025-07-31 13:58:04.021 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.660e-03, size: 288, ETA: 1:51:41
2025-07-31 13:58:06.968 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.014s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.2, lr: 4.654e-03, size: 352, ETA: 1:51:38
2025-07-31 13:58:09.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.047s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 4.648e-03, size: 544, ETA: 1:51:36
2025-07-31 13:58:12.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.043s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.643e-03, size: 320, ETA: 1:51:33
2025-07-31 13:58:15.680 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.127s, data_time: 0.005s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 4.637e-03, size: 480, ETA: 1:51:30
2025-07-31 13:58:18.616 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 4.631e-03, size: 544, ETA: 1:51:27
2025-07-31 13:58:19.842 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:58:19.908 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch220
2025-07-31 13:58:22.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.623e-03, size: 576, ETA: 1:51:23
2025-07-31 13:58:25.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 4.617e-03, size: 576, ETA: 1:51:20
2025-07-31 13:58:28.801 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 4.611e-03, size: 512, ETA: 1:51:17
2025-07-31 13:58:31.750 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 4.605e-03, size: 576, ETA: 1:51:14
2025-07-31 13:58:34.651 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.599e-03, size: 448, ETA: 1:51:11
2025-07-31 13:58:37.678 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 4.594e-03, size: 416, ETA: 1:51:09
2025-07-31 13:58:38.909 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:58:45.341 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 13:58:48.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 13:58:51.519 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5673
2025-07-31 13:58:51.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5135
2025-07-31 13:58:52.000 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2741
2025-07-31 13:58:52.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4517
2025-07-31 13:58:52.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 13:58:52.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 13:58:52.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.567
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.514
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.274
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.452
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 13:58:52.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 13:58:52.003 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 13:58:55.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 13:58:58.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 13:59:01.139 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 13:59:04.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 13:59:07.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 13:59:10.179 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 13:59:13.146 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 13:59:16.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 13:59:19.078 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 13:59:19.079 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-31 13:59:19.079 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-31 13:59:19.079 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 13:59:19.106 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.49 ms, Average NMS time: 1.05 ms, Average inference time: 2.54 ms

2025-07-31 13:59:19.108 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:59:19.134 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:59:19.166 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch221
2025-07-31 13:59:21.612 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.121s, data_time: 0.031s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.585e-03, size: 512, ETA: 1:51:04
2025-07-31 13:59:24.518 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.142s, data_time: 0.044s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 4.579e-03, size: 352, ETA: 1:51:02
2025-07-31 13:59:27.457 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.039s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 4.574e-03, size: 384, ETA: 1:50:59
2025-07-31 13:59:30.291 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.041s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 4.568e-03, size: 352, ETA: 1:50:56
2025-07-31 13:59:33.296 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 4.562e-03, size: 352, ETA: 1:50:53
2025-07-31 13:59:36.252 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.556e-03, size: 576, ETA: 1:50:51
2025-07-31 13:59:37.520 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:59:37.573 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch222
2025-07-31 13:59:40.463 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 4.548e-03, size: 320, ETA: 1:50:47
2025-07-31 13:59:43.489 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.542e-03, size: 352, ETA: 1:50:44
2025-07-31 13:59:46.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 4.536e-03, size: 288, ETA: 1:50:41
2025-07-31 13:59:49.383 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 4.530e-03, size: 384, ETA: 1:50:38
2025-07-31 13:59:52.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.125s, data_time: 0.007s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.525e-03, size: 480, ETA: 1:50:35
2025-07-31 13:59:55.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.026s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 4.519e-03, size: 384, ETA: 1:50:33
2025-07-31 13:59:56.305 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 13:59:56.458 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch223
2025-07-31 13:59:59.310 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.510e-03, size: 416, ETA: 1:50:28
2025-07-31 14:00:02.098 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.123s, data_time: 0.009s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.505e-03, size: 416, ETA: 1:50:25
2025-07-31 14:00:05.103 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 4.499e-03, size: 480, ETA: 1:50:22
2025-07-31 14:00:08.127 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 4.493e-03, size: 544, ETA: 1:50:19
2025-07-31 14:00:11.038 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 4.487e-03, size: 256, ETA: 1:50:16
2025-07-31 14:00:13.989 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 4.482e-03, size: 448, ETA: 1:50:13
2025-07-31 14:00:15.287 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:00:15.343 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch224
2025-07-31 14:00:18.039 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 4.473e-03, size: 512, ETA: 1:50:09
2025-07-31 14:00:21.092 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 4.467e-03, size: 416, ETA: 1:50:06
2025-07-31 14:00:24.021 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 4.462e-03, size: 320, ETA: 1:50:04
2025-07-31 14:00:26.826 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.008s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 4.456e-03, size: 288, ETA: 1:50:00
2025-07-31 14:00:29.688 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.009s, total_loss: 5.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 4.450e-03, size: 352, ETA: 1:49:57
2025-07-31 14:00:32.688 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.007s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 4.444e-03, size: 256, ETA: 1:49:55
2025-07-31 14:00:33.991 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:00:34.095 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch225
2025-07-31 14:00:36.928 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.011s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 4.436e-03, size: 352, ETA: 1:49:51
2025-07-31 14:00:39.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.016s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 4.430e-03, size: 480, ETA: 1:49:48
2025-07-31 14:00:42.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.056s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 4.424e-03, size: 288, ETA: 1:49:45
2025-07-31 14:00:45.616 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.142s, data_time: 0.059s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.419e-03, size: 480, ETA: 1:49:43
2025-07-31 14:00:48.559 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 4.413e-03, size: 320, ETA: 1:49:40
2025-07-31 14:00:51.538 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 4.407e-03, size: 576, ETA: 1:49:37
2025-07-31 14:00:52.774 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:00:59.484 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:01:03.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:01:06.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5445
2025-07-31 14:01:07.091 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5135
2025-07-31 14:01:07.128 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2500
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4360
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.544
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.513
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.250
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.436
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:01:07.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:01:07.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:01:07.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:01:07.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:01:07.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:01:07.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:01:07.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:01:10.567 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:01:13.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:01:17.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:01:21.283 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:01:24.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:01:27.936 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:01:31.326 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:01:34.574 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:01:37.869 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:01:37.869 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-31 14:01:37.869 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-31 14:01:37.869 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:01:37.894 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 1.00 ms, Average inference time: 2.42 ms

2025-07-31 14:01:37.895 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:01:37.926 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:01:37.960 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch226
2025-07-31 14:01:40.466 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.125s, data_time: 0.043s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 4.399e-03, size: 416, ETA: 1:49:33
2025-07-31 14:01:43.508 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.150s, data_time: 0.066s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 4.393e-03, size: 256, ETA: 1:49:31
2025-07-31 14:01:46.473 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.147s, data_time: 0.065s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.7, lr: 4.387e-03, size: 576, ETA: 1:49:28
2025-07-31 14:01:49.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.045s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 4.381e-03, size: 416, ETA: 1:49:26
2025-07-31 14:01:52.341 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.036s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.376e-03, size: 352, ETA: 1:49:23
2025-07-31 14:01:55.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.370e-03, size: 416, ETA: 1:49:20
2025-07-31 14:01:56.412 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:01:56.461 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch227
2025-07-31 14:01:59.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 4.362e-03, size: 416, ETA: 1:49:16
2025-07-31 14:02:02.281 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.031s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 4.356e-03, size: 576, ETA: 1:49:14
2025-07-31 14:02:05.184 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.005s, total_loss: 6.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 4.350e-03, size: 288, ETA: 1:49:11
2025-07-31 14:02:08.114 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.038s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 4.344e-03, size: 576, ETA: 1:49:09
2025-07-31 14:02:11.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.151s, data_time: 0.064s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 4.339e-03, size: 320, ETA: 1:49:06
2025-07-31 14:02:13.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.051s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.333e-03, size: 512, ETA: 1:49:04
2025-07-31 14:02:15.257 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:02:15.412 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch228
2025-07-31 14:02:18.181 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.009s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 4.325e-03, size: 512, ETA: 1:49:00
2025-07-31 14:02:21.062 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.319e-03, size: 256, ETA: 1:48:57
2025-07-31 14:02:23.918 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 4.313e-03, size: 448, ETA: 1:48:54
2025-07-31 14:02:26.753 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 4.307e-03, size: 352, ETA: 1:48:51
2025-07-31 14:02:29.701 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.006s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.302e-03, size: 480, ETA: 1:48:48
2025-07-31 14:02:32.561 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.032s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.296e-03, size: 384, ETA: 1:48:45
2025-07-31 14:02:33.813 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:02:33.888 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch229
2025-07-31 14:02:36.798 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.023s, total_loss: 5.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 4.287e-03, size: 416, ETA: 1:48:41
2025-07-31 14:02:39.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.032s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 4.282e-03, size: 416, ETA: 1:48:38
2025-07-31 14:02:42.610 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 4.276e-03, size: 416, ETA: 1:48:36
2025-07-31 14:02:45.453 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.138s, data_time: 0.015s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.270e-03, size: 448, ETA: 1:48:33
2025-07-31 14:02:48.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.021s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 4.265e-03, size: 320, ETA: 1:48:30
2025-07-31 14:02:51.247 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.141s, data_time: 0.025s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 4.259e-03, size: 320, ETA: 1:48:28
2025-07-31 14:02:52.483 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:02:52.524 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch230
2025-07-31 14:02:55.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.030s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.251e-03, size: 512, ETA: 1:48:24
2025-07-31 14:02:58.303 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.009s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 4.245e-03, size: 576, ETA: 1:48:21
2025-07-31 14:03:01.214 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.030s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 4.239e-03, size: 448, ETA: 1:48:18
2025-07-31 14:03:04.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.047s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 4.233e-03, size: 288, ETA: 1:48:16
2025-07-31 14:03:07.155 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 4.228e-03, size: 352, ETA: 1:48:13
2025-07-31 14:03:09.944 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.041s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.222e-03, size: 288, ETA: 1:48:10
2025-07-31 14:03:11.278 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:03:17.726 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:03:21.557 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:03:24.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5392
2025-07-31 14:03:24.394 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4769
2025-07-31 14:03:24.505 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2703
2025-07-31 14:03:24.507 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4288
2025-07-31 14:03:24.507 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:03:24.508 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:03:24.508 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.539
2025-07-31 14:03:24.508 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.477
2025-07-31 14:03:24.509 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.270
2025-07-31 14:03:24.509 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.429
2025-07-31 14:03:24.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:03:24.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:03:24.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:03:24.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:03:24.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:03:24.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:03:24.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:03:24.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:03:24.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:03:27.441 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:03:30.315 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:03:33.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:03:36.099 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:03:39.011 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:03:41.913 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:03:44.775 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:03:47.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:03:50.519 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:03:50.519 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-31 14:03:50.520 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-31 14:03:50.520 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:03:50.545 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 1.01 ms, Average inference time: 2.46 ms

2025-07-31 14:03:50.546 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:03:50.568 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:03:50.607 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch231
2025-07-31 14:03:53.152 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.118s, data_time: 0.026s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 4.214e-03, size: 352, ETA: 1:48:06
2025-07-31 14:03:56.072 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 4.208e-03, size: 480, ETA: 1:48:03
2025-07-31 14:03:58.963 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 4.202e-03, size: 352, ETA: 1:48:00
2025-07-31 14:04:01.818 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 4.196e-03, size: 352, ETA: 1:47:57
2025-07-31 14:04:04.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.019s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 4.191e-03, size: 352, ETA: 1:47:54
2025-07-31 14:04:07.710 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.139s, data_time: 0.050s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.185e-03, size: 544, ETA: 1:47:52
2025-07-31 14:04:08.899 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:04:08.963 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch232
2025-07-31 14:04:11.898 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.038s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 4.177e-03, size: 416, ETA: 1:47:48
2025-07-31 14:04:14.946 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.005s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 4.171e-03, size: 576, ETA: 1:47:45
2025-07-31 14:04:17.910 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 4.165e-03, size: 480, ETA: 1:47:43
2025-07-31 14:04:20.820 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 4.160e-03, size: 256, ETA: 1:47:40
2025-07-31 14:04:23.670 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 4.154e-03, size: 384, ETA: 1:47:37
2025-07-31 14:04:26.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.046s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 4.148e-03, size: 448, ETA: 1:47:34
2025-07-31 14:04:27.835 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:04:27.999 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch233
2025-07-31 14:04:30.852 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.024s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.140e-03, size: 384, ETA: 1:47:30
2025-07-31 14:04:33.792 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.019s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 4.134e-03, size: 416, ETA: 1:47:27
2025-07-31 14:04:36.602 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.013s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 4.129e-03, size: 576, ETA: 1:47:24
2025-07-31 14:04:39.510 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.007s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 4.123e-03, size: 576, ETA: 1:47:21
2025-07-31 14:04:42.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.117e-03, size: 512, ETA: 1:47:18
2025-07-31 14:04:45.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 4.112e-03, size: 384, ETA: 1:47:16
2025-07-31 14:04:46.831 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:04:46.870 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch234
2025-07-31 14:04:49.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.005s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 4.103e-03, size: 512, ETA: 1:47:11
2025-07-31 14:04:52.599 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.004s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 4.098e-03, size: 384, ETA: 1:47:09
2025-07-31 14:04:55.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.011s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.092e-03, size: 384, ETA: 1:47:06
2025-07-31 14:04:58.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 4.086e-03, size: 288, ETA: 1:47:03
2025-07-31 14:05:01.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.081e-03, size: 576, ETA: 1:47:00
2025-07-31 14:05:04.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 4.075e-03, size: 576, ETA: 1:46:57
2025-07-31 14:05:05.410 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:05:05.560 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch235
2025-07-31 14:05:08.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.008s, total_loss: 7.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.067e-03, size: 320, ETA: 1:46:53
2025-07-31 14:05:11.415 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 4.061e-03, size: 320, ETA: 1:46:50
2025-07-31 14:05:14.336 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 4.055e-03, size: 544, ETA: 1:46:47
2025-07-31 14:05:17.201 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.013s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 4.050e-03, size: 288, ETA: 1:46:44
2025-07-31 14:05:20.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.044s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 4.044e-03, size: 352, ETA: 1:46:42
2025-07-31 14:05:23.132 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.141s, data_time: 0.034s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.038e-03, size: 448, ETA: 1:46:39
2025-07-31 14:05:24.369 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:05:30.672 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:05:32.430 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:05:33.463 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5777
2025-07-31 14:05:33.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5376
2025-07-31 14:05:33.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3332
2025-07-31 14:05:33.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4828
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.578
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.538
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.333
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.483
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:05:33.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:05:33.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:05:33.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:05:33.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:05:33.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:05:35.163 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:05:36.575 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:05:37.916 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:05:39.262 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:05:40.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:05:42.039 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:05:43.507 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:05:44.884 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:05:46.209 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:05:46.210 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-31 14:05:46.210 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-31 14:05:46.210 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:05:46.220 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 0.98 ms, Average inference time: 2.41 ms

2025-07-31 14:05:46.221 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:05:46.244 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:05:46.281 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch236
2025-07-31 14:05:48.746 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.114s, data_time: 0.014s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 4.030e-03, size: 288, ETA: 1:46:34
2025-07-31 14:05:51.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.051s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 4.024e-03, size: 320, ETA: 1:46:32
2025-07-31 14:05:54.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.013s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 4.019e-03, size: 512, ETA: 1:46:29
2025-07-31 14:05:57.521 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.013e-03, size: 480, ETA: 1:46:26
2025-07-31 14:06:00.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.013s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 4.008e-03, size: 576, ETA: 1:46:24
2025-07-31 14:06:03.288 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.020s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.002e-03, size: 448, ETA: 1:46:21
2025-07-31 14:06:04.616 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:06:04.690 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch237
2025-07-31 14:06:07.584 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.122s, data_time: 0.013s, total_loss: 7.5, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 3.994e-03, size: 256, ETA: 1:46:17
2025-07-31 14:06:10.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 3.988e-03, size: 480, ETA: 1:46:14
2025-07-31 14:06:13.353 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.005s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.982e-03, size: 448, ETA: 1:46:11
2025-07-31 14:06:16.229 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.016s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.977e-03, size: 544, ETA: 1:46:08
2025-07-31 14:06:19.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 3.971e-03, size: 256, ETA: 1:46:05
2025-07-31 14:06:22.025 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.146s, data_time: 0.026s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 3.965e-03, size: 352, ETA: 1:46:03
2025-07-31 14:06:23.341 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:06:23.455 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch238
2025-07-31 14:06:26.299 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 3.957e-03, size: 288, ETA: 1:45:59
2025-07-31 14:06:29.172 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.017s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 3.952e-03, size: 512, ETA: 1:45:56
2025-07-31 14:06:31.964 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.046s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 3.946e-03, size: 416, ETA: 1:45:53
2025-07-31 14:06:34.899 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.141s, data_time: 0.023s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 3.940e-03, size: 576, ETA: 1:45:51
2025-07-31 14:06:37.861 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.031s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 3.935e-03, size: 384, ETA: 1:45:48
2025-07-31 14:06:40.672 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.031s, total_loss: 8.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 3.929e-03, size: 480, ETA: 1:45:45
2025-07-31 14:06:41.981 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:06:42.020 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch239
2025-07-31 14:06:44.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.046s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.921e-03, size: 256, ETA: 1:45:42
2025-07-31 14:06:47.752 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 3.915e-03, size: 448, ETA: 1:45:39
2025-07-31 14:06:50.697 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.146s, data_time: 0.053s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 3.910e-03, size: 384, ETA: 1:45:37
2025-07-31 14:06:53.579 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.050s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.904e-03, size: 544, ETA: 1:45:34
2025-07-31 14:06:56.541 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.043s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 3.899e-03, size: 288, ETA: 1:45:31
2025-07-31 14:06:59.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 3.893e-03, size: 384, ETA: 1:45:29
2025-07-31 14:07:00.883 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:07:00.921 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch240
2025-07-31 14:07:03.917 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.148s, data_time: 0.064s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 3.885e-03, size: 320, ETA: 1:45:25
2025-07-31 14:07:06.827 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.144s, data_time: 0.064s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.879e-03, size: 576, ETA: 1:45:23
2025-07-31 14:07:09.850 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.149s, data_time: 0.059s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 3.874e-03, size: 384, ETA: 1:45:21
2025-07-31 14:07:12.680 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.140s, data_time: 0.053s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 3.868e-03, size: 480, ETA: 1:45:18
2025-07-31 14:07:15.638 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.147s, data_time: 0.058s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.862e-03, size: 416, ETA: 1:45:16
2025-07-31 14:07:18.533 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.141s, data_time: 0.045s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 3.857e-03, size: 352, ETA: 1:45:13
2025-07-31 14:07:19.765 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:07:26.220 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:07:29.035 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:07:30.664 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5759
2025-07-31 14:07:31.068 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5065
2025-07-31 14:07:31.182 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3211
2025-07-31 14:07:31.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4679
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.576
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.507
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.321
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.468
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:07:31.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:07:31.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:07:31.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:07:31.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:07:31.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:07:31.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:07:33.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:07:35.321 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:07:37.371 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:07:39.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:07:41.555 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:07:43.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:07:45.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:07:48.096 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:07:50.224 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:07:50.224 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-31 14:07:50.224 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-31 14:07:50.224 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:07:50.251 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 1.02 ms, Average inference time: 2.46 ms

2025-07-31 14:07:50.256 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:07:50.285 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:07:50.318 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch241
2025-07-31 14:07:52.870 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.127s, data_time: 0.044s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 3.849e-03, size: 256, ETA: 1:45:09
2025-07-31 14:07:55.815 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.144s, data_time: 0.061s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 3.843e-03, size: 480, ETA: 1:45:06
2025-07-31 14:07:58.749 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.018s, total_loss: 5.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 3.837e-03, size: 352, ETA: 1:45:04
2025-07-31 14:08:01.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.139s, data_time: 0.048s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 3.832e-03, size: 256, ETA: 1:45:01
2025-07-31 14:08:04.669 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.153s, data_time: 0.068s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 3.826e-03, size: 384, ETA: 1:44:59
2025-07-31 14:08:07.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.147s, data_time: 0.062s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.821e-03, size: 256, ETA: 1:44:57
2025-07-31 14:08:08.990 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:08:09.027 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch242
2025-07-31 14:08:12.058 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.151s, data_time: 0.059s, total_loss: 7.5, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 3.813e-03, size: 448, ETA: 1:44:53
2025-07-31 14:08:14.890 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.140s, data_time: 0.052s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 3.807e-03, size: 544, ETA: 1:44:51
2025-07-31 14:08:17.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.140s, data_time: 0.031s, total_loss: 7.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.801e-03, size: 288, ETA: 1:44:48
2025-07-31 14:08:20.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.014s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 3.796e-03, size: 384, ETA: 1:44:45
2025-07-31 14:08:23.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.006s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.790e-03, size: 384, ETA: 1:44:43
2025-07-31 14:08:26.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.036s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 3.785e-03, size: 288, ETA: 1:44:40
2025-07-31 14:08:27.665 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:08:27.795 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch243
2025-07-31 14:08:30.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 3.777e-03, size: 256, ETA: 1:44:36
2025-07-31 14:08:33.744 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.008s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.771e-03, size: 288, ETA: 1:44:33
2025-07-31 14:08:36.681 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.765e-03, size: 352, ETA: 1:44:30
2025-07-31 14:08:39.608 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.014s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 3.760e-03, size: 320, ETA: 1:44:27
2025-07-31 14:08:42.617 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.147s, data_time: 0.032s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 3.754e-03, size: 544, ETA: 1:44:25
2025-07-31 14:08:45.606 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.145s, data_time: 0.013s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.749e-03, size: 544, ETA: 1:44:23
2025-07-31 14:08:46.832 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:08:46.942 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch244
2025-07-31 14:08:49.869 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.741e-03, size: 288, ETA: 1:44:19
2025-07-31 14:08:52.802 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.735e-03, size: 512, ETA: 1:44:16
2025-07-31 14:08:55.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.019s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.730e-03, size: 320, ETA: 1:44:13
2025-07-31 14:08:58.769 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.1Gb, iter_time: 0.150s, data_time: 0.067s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.724e-03, size: 512, ETA: 1:44:11
2025-07-31 14:09:01.610 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.141s, data_time: 0.052s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 3.719e-03, size: 512, ETA: 1:44:08
2025-07-31 14:09:04.545 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.014s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 3.713e-03, size: 480, ETA: 1:44:05
2025-07-31 14:09:05.764 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:09:05.865 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch245
2025-07-31 14:09:08.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.032s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 3.705e-03, size: 384, ETA: 1:44:01
2025-07-31 14:09:11.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.148s, data_time: 0.062s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.9, lr: 3.699e-03, size: 480, ETA: 1:43:59
2025-07-31 14:09:14.790 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.041s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 3.694e-03, size: 384, ETA: 1:43:57
2025-07-31 14:09:17.699 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.015s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 3.688e-03, size: 416, ETA: 1:43:54
2025-07-31 14:09:20.605 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.033s, total_loss: 5.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.6, lr: 3.683e-03, size: 416, ETA: 1:43:51
2025-07-31 14:09:23.482 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.010s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.6, lr: 3.677e-03, size: 448, ETA: 1:43:48
2025-07-31 14:09:24.713 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:09:31.300 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:09:33.896 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:09:35.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5831
2025-07-31 14:09:35.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5234
2025-07-31 14:09:35.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2785
2025-07-31 14:09:35.864 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4617
2025-07-31 14:09:35.864 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:09:35.864 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:09:35.864 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.583
2025-07-31 14:09:35.864 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.523
2025-07-31 14:09:35.864 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.278
2025-07-31 14:09:35.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.462
2025-07-31 14:09:35.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:09:35.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:09:35.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:09:35.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:09:35.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:09:35.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:09:35.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:09:35.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:09:35.866 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:09:37.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:09:39.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:09:41.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:09:43.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:09:45.735 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:09:47.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:09:49.620 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:09:51.591 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:09:53.954 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:09:53.955 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-31 14:09:53.955 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-31 14:09:53.955 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:09:53.983 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 1.01 ms, Average inference time: 2.47 ms

2025-07-31 14:09:53.984 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:09:54.015 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:09:54.048 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch246
2025-07-31 14:09:56.692 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.047s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 3.669e-03, size: 480, ETA: 1:43:44
2025-07-31 14:09:59.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.022s, total_loss: 6.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.664e-03, size: 288, ETA: 1:43:41
2025-07-31 14:10:02.423 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.131s, data_time: 0.014s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 3.658e-03, size: 416, ETA: 1:43:39
2025-07-31 14:10:05.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.653e-03, size: 480, ETA: 1:43:36
2025-07-31 14:10:08.213 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 3.647e-03, size: 576, ETA: 1:43:33
2025-07-31 14:10:11.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.018s, total_loss: 5.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 3.642e-03, size: 480, ETA: 1:43:30
2025-07-31 14:10:12.290 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:10:12.399 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch247
2025-07-31 14:10:15.278 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.040s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 3.634e-03, size: 480, ETA: 1:43:26
2025-07-31 14:10:18.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.053s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.628e-03, size: 416, ETA: 1:43:23
2025-07-31 14:10:21.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.037s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 3.623e-03, size: 288, ETA: 1:43:20
2025-07-31 14:10:24.040 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.143s, data_time: 0.055s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.617e-03, size: 416, ETA: 1:43:18
2025-07-31 14:10:26.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.051s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 3.612e-03, size: 288, ETA: 1:43:15
2025-07-31 14:10:29.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.141s, data_time: 0.036s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.2, lr: 3.606e-03, size: 256, ETA: 1:43:13
2025-07-31 14:10:31.052 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:10:31.202 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch248
2025-07-31 14:10:34.034 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.011s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 3.598e-03, size: 320, ETA: 1:43:09
2025-07-31 14:10:36.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.049s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 3.593e-03, size: 480, ETA: 1:43:06
2025-07-31 14:10:39.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.144s, data_time: 0.060s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.587e-03, size: 416, ETA: 1:43:03
2025-07-31 14:10:42.659 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.023s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.582e-03, size: 416, ETA: 1:43:01
2025-07-31 14:10:45.670 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.576e-03, size: 576, ETA: 1:42:58
2025-07-31 14:10:48.557 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.571e-03, size: 512, ETA: 1:42:55
2025-07-31 14:10:49.817 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:10:49.865 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch249
2025-07-31 14:10:52.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.143s, data_time: 0.057s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.6, lr: 3.563e-03, size: 256, ETA: 1:42:52
2025-07-31 14:10:55.650 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.027s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.557e-03, size: 352, ETA: 1:42:49
2025-07-31 14:10:58.667 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 3.552e-03, size: 480, ETA: 1:42:46
2025-07-31 14:11:01.732 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 3.546e-03, size: 256, ETA: 1:42:44
2025-07-31 14:11:04.759 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.541e-03, size: 416, ETA: 1:42:41
2025-07-31 14:11:07.638 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 3.536e-03, size: 448, ETA: 1:42:38
2025-07-31 14:11:08.897 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:11:08.944 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch250
2025-07-31 14:11:11.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.016s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.528e-03, size: 512, ETA: 1:42:34
2025-07-31 14:11:14.802 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 3.522e-03, size: 352, ETA: 1:42:31
2025-07-31 14:11:17.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 3.517e-03, size: 256, ETA: 1:42:28
2025-07-31 14:11:20.729 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 3.511e-03, size: 320, ETA: 1:42:25
2025-07-31 14:11:23.579 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 3.506e-03, size: 480, ETA: 1:42:23
2025-07-31 14:11:26.473 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.021s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.500e-03, size: 512, ETA: 1:42:20
2025-07-31 14:11:27.847 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:11:34.227 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:11:35.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:11:36.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5516
2025-07-31 14:11:36.745 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5201
2025-07-31 14:11:36.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3373
2025-07-31 14:11:36.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4697
2025-07-31 14:11:36.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:11:36.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:11:36.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.552
2025-07-31 14:11:36.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.520
2025-07-31 14:11:36.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.337
2025-07-31 14:11:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.470
2025-07-31 14:11:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:11:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:11:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:11:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:11:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:11:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:11:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:11:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:11:36.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:11:37.989 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:11:39.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:11:40.397 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:11:41.589 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:11:42.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:11:43.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:11:44.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:11:45.884 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:11:46.945 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:11:46.946 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-31 14:11:46.946 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-31 14:11:46.946 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:11:46.954 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.48 ms, Average NMS time: 1.03 ms, Average inference time: 2.51 ms

2025-07-31 14:11:46.957 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:11:46.983 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:11:47.016 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch251
2025-07-31 14:11:49.593 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.122s, data_time: 0.036s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 3.492e-03, size: 544, ETA: 1:42:16
2025-07-31 14:11:52.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.036s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 3.487e-03, size: 448, ETA: 1:42:13
2025-07-31 14:11:55.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.142s, data_time: 0.044s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.482e-03, size: 416, ETA: 1:42:10
2025-07-31 14:11:58.208 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.045s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.476e-03, size: 320, ETA: 1:42:08
2025-07-31 14:12:01.152 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.145s, data_time: 0.040s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.471e-03, size: 448, ETA: 1:42:05
2025-07-31 14:12:04.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.140s, data_time: 0.034s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 3.465e-03, size: 480, ETA: 1:42:02
2025-07-31 14:12:05.372 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:12:05.412 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch252
2025-07-31 14:12:08.312 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.030s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.457e-03, size: 576, ETA: 1:41:59
2025-07-31 14:12:11.232 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.139s, data_time: 0.023s, total_loss: 5.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 3.452e-03, size: 416, ETA: 1:41:56
2025-07-31 14:12:14.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.010s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.2, lr: 3.447e-03, size: 352, ETA: 1:41:53
2025-07-31 14:12:17.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.8, lr: 3.441e-03, size: 512, ETA: 1:41:50
2025-07-31 14:12:19.986 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 3.436e-03, size: 448, ETA: 1:41:47
2025-07-31 14:12:22.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.430e-03, size: 320, ETA: 1:41:45
2025-07-31 14:12:24.091 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:12:24.284 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch253
2025-07-31 14:12:27.115 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 3.422e-03, size: 256, ETA: 1:41:40
2025-07-31 14:12:29.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.049s, total_loss: 6.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 3.417e-03, size: 352, ETA: 1:41:37
2025-07-31 14:12:32.864 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.141s, data_time: 0.050s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 3.412e-03, size: 384, ETA: 1:41:35
2025-07-31 14:12:35.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.151s, data_time: 0.061s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 3.406e-03, size: 384, ETA: 1:41:32
2025-07-31 14:12:38.787 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.055s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.401e-03, size: 448, ETA: 1:41:30
2025-07-31 14:12:41.702 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.042s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.8, lr: 3.395e-03, size: 256, ETA: 1:41:27
2025-07-31 14:12:43.011 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:12:43.053 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch254
2025-07-31 14:12:45.941 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.043s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 3.388e-03, size: 256, ETA: 1:41:23
2025-07-31 14:12:48.868 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.382e-03, size: 448, ETA: 1:41:20
2025-07-31 14:12:51.762 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.377e-03, size: 288, ETA: 1:41:18
2025-07-31 14:12:54.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.021s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.372e-03, size: 352, ETA: 1:41:15
2025-07-31 14:12:57.476 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.043s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 3.366e-03, size: 384, ETA: 1:41:12
2025-07-31 14:13:00.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.056s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 3.361e-03, size: 576, ETA: 1:41:09
2025-07-31 14:13:01.673 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:13:01.821 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch255
2025-07-31 14:13:04.662 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.353e-03, size: 288, ETA: 1:41:05
2025-07-31 14:13:07.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.120s, data_time: 0.009s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.348e-03, size: 384, ETA: 1:41:02
2025-07-31 14:13:10.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.010s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.342e-03, size: 448, ETA: 1:40:59
2025-07-31 14:13:13.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 3.337e-03, size: 576, ETA: 1:40:56
2025-07-31 14:13:16.180 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.120s, data_time: 0.007s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 3.332e-03, size: 256, ETA: 1:40:53
2025-07-31 14:13:19.186 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.147s, data_time: 0.008s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 3.326e-03, size: 512, ETA: 1:40:51
2025-07-31 14:13:20.446 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:13:26.981 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:13:29.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:13:30.757 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5567
2025-07-31 14:13:31.070 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4794
2025-07-31 14:13:31.131 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3225
2025-07-31 14:13:31.131 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4529
2025-07-31 14:13:31.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:13:31.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:13:31.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.557
2025-07-31 14:13:31.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.479
2025-07-31 14:13:31.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.322
2025-07-31 14:13:31.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.453
2025-07-31 14:13:31.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:13:31.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:13:31.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:13:31.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:13:31.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:13:31.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:13:31.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:13:31.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:13:31.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:13:32.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:13:34.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:13:36.282 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:13:38.066 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:13:40.005 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:13:41.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:13:43.785 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:13:45.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:13:47.332 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:13:47.332 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-31 14:13:47.332 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-31 14:13:47.332 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:13:47.359 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 0.99 ms, Average inference time: 2.40 ms

2025-07-31 14:13:47.361 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:13:47.405 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:13:47.454 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch256
2025-07-31 14:13:49.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.121s, data_time: 0.036s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.318e-03, size: 512, ETA: 1:40:46
2025-07-31 14:13:52.851 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.132s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.313e-03, size: 544, ETA: 1:40:44
2025-07-31 14:13:55.932 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 3.308e-03, size: 512, ETA: 1:40:41
2025-07-31 14:13:58.850 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.013s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.302e-03, size: 544, ETA: 1:40:38
2025-07-31 14:14:01.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 3.297e-03, size: 416, ETA: 1:40:35
2025-07-31 14:14:04.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 3.292e-03, size: 448, ETA: 1:40:32
2025-07-31 14:14:05.987 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:14:06.024 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch257
2025-07-31 14:14:08.847 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 3.284e-03, size: 384, ETA: 1:40:29
2025-07-31 14:14:11.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.030s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.279e-03, size: 320, ETA: 1:40:26
2025-07-31 14:14:14.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.148s, data_time: 0.059s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 3.273e-03, size: 384, ETA: 1:40:24
2025-07-31 14:14:17.657 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.143s, data_time: 0.055s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.268e-03, size: 320, ETA: 1:40:21
2025-07-31 14:14:20.592 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.045s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 3.263e-03, size: 448, ETA: 1:40:18
2025-07-31 14:14:23.502 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.142s, data_time: 0.057s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.3, lr: 3.257e-03, size: 320, ETA: 1:40:16
2025-07-31 14:14:24.877 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:14:24.927 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch258
2025-07-31 14:14:27.973 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.250e-03, size: 576, ETA: 1:40:12
2025-07-31 14:14:31.038 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.244e-03, size: 576, ETA: 1:40:09
2025-07-31 14:14:34.058 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.239e-03, size: 256, ETA: 1:40:07
2025-07-31 14:14:36.917 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 3.234e-03, size: 576, ETA: 1:40:04
2025-07-31 14:14:39.841 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.140s, data_time: 0.020s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.228e-03, size: 480, ETA: 1:40:01
2025-07-31 14:14:42.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.012s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 3.223e-03, size: 480, ETA: 1:39:58
2025-07-31 14:14:44.057 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:14:44.114 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch259
2025-07-31 14:14:47.008 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.141s, data_time: 0.020s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 3.215e-03, size: 448, ETA: 1:39:55
2025-07-31 14:14:49.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.043s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 3.210e-03, size: 256, ETA: 1:39:52
2025-07-31 14:14:52.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.132s, data_time: 0.013s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.205e-03, size: 256, ETA: 1:39:49
2025-07-31 14:14:55.698 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.146s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 3.200e-03, size: 512, ETA: 1:39:47
2025-07-31 14:14:58.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.147s, data_time: 0.012s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 3.194e-03, size: 352, ETA: 1:39:44
2025-07-31 14:15:01.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.037s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.189e-03, size: 256, ETA: 1:39:41
2025-07-31 14:15:02.774 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:15:02.878 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch260
2025-07-31 14:15:05.767 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.016s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.181e-03, size: 480, ETA: 1:39:37
2025-07-31 14:15:08.696 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.140s, data_time: 0.042s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 3.176e-03, size: 448, ETA: 1:39:35
2025-07-31 14:15:11.675 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.142s, data_time: 0.044s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.171e-03, size: 544, ETA: 1:39:32
2025-07-31 14:15:14.623 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.005s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.166e-03, size: 512, ETA: 1:39:29
2025-07-31 14:15:17.566 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.160e-03, size: 480, ETA: 1:39:27
2025-07-31 14:15:20.611 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 3.155e-03, size: 352, ETA: 1:39:24
2025-07-31 14:15:21.982 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:15:28.371 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:15:31.937 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:15:34.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5712
2025-07-31 14:15:34.767 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5025
2025-07-31 14:15:34.818 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3157
2025-07-31 14:15:34.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4631
2025-07-31 14:15:34.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:15:34.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:15:34.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.571
2025-07-31 14:15:34.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.502
2025-07-31 14:15:34.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.316
2025-07-31 14:15:34.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.463
2025-07-31 14:15:34.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:15:34.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:15:34.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:15:34.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:15:34.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:15:34.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:15:34.821 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:15:34.821 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:15:34.821 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:15:37.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:15:40.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:15:43.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:15:46.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:15:48.786 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:15:51.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:15:54.320 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:15:57.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:15:59.919 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:15:59.920 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-31 14:15:59.920 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-31 14:15:59.921 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:15:59.951 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 1.01 ms, Average inference time: 2.43 ms

2025-07-31 14:15:59.952 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:15:59.988 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:16:00.046 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch261
2025-07-31 14:16:02.563 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.122s, data_time: 0.037s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 3.147e-03, size: 512, ETA: 1:39:20
2025-07-31 14:16:05.537 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.2Gb, iter_time: 0.143s, data_time: 0.020s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 3.142e-03, size: 320, ETA: 1:39:17
2025-07-31 14:16:08.496 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.010s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.137e-03, size: 416, ETA: 1:39:14
2025-07-31 14:16:11.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.140s, data_time: 0.041s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 3.132e-03, size: 576, ETA: 1:39:12
2025-07-31 14:16:14.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.142s, data_time: 0.049s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 3.126e-03, size: 352, ETA: 1:39:09
2025-07-31 14:16:17.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.147s, data_time: 0.021s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.121e-03, size: 448, ETA: 1:39:07
2025-07-31 14:16:18.764 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:16:18.912 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch262
2025-07-31 14:16:21.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.042s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 3.114e-03, size: 256, ETA: 1:39:03
2025-07-31 14:16:24.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.145s, data_time: 0.056s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 3.108e-03, size: 448, ETA: 1:39:00
2025-07-31 14:16:27.541 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.143s, data_time: 0.044s, total_loss: 8.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.0, lr: 3.103e-03, size: 512, ETA: 1:38:58
2025-07-31 14:16:30.531 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.141s, data_time: 0.015s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.098e-03, size: 384, ETA: 1:38:55
2025-07-31 14:16:33.447 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.093e-03, size: 512, ETA: 1:38:53
2025-07-31 14:16:36.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.038s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 3.087e-03, size: 416, ETA: 1:38:50
2025-07-31 14:16:37.482 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:16:37.658 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch263
2025-07-31 14:16:40.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.045s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 3.080e-03, size: 544, ETA: 1:38:46
2025-07-31 14:16:43.383 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.042s, total_loss: 4.7, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 3.075e-03, size: 352, ETA: 1:38:43
2025-07-31 14:16:46.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 3.070e-03, size: 544, ETA: 1:38:40
2025-07-31 14:16:49.328 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.064e-03, size: 320, ETA: 1:38:38
2025-07-31 14:16:52.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.005s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 3.059e-03, size: 448, ETA: 1:38:35
2025-07-31 14:16:55.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.144s, data_time: 0.018s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 3.054e-03, size: 288, ETA: 1:38:32
2025-07-31 14:16:56.405 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:16:56.510 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch264
2025-07-31 14:16:59.298 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 3.046e-03, size: 512, ETA: 1:38:28
2025-07-31 14:17:02.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.9, lr: 3.041e-03, size: 352, ETA: 1:38:26
2025-07-31 14:17:05.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 3.036e-03, size: 288, ETA: 1:38:23
2025-07-31 14:17:08.272 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 4.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 3.031e-03, size: 352, ETA: 1:38:20
2025-07-31 14:17:11.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 3.026e-03, size: 576, ETA: 1:38:18
2025-07-31 14:17:14.232 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 3.020e-03, size: 352, ETA: 1:38:15
2025-07-31 14:17:15.518 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:17:15.579 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch265
2025-07-31 14:17:18.465 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.142s, data_time: 0.005s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 3.013e-03, size: 512, ETA: 1:38:11
2025-07-31 14:17:21.358 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.142s, data_time: 0.025s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 3.008e-03, size: 320, ETA: 1:38:09
2025-07-31 14:17:24.296 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.143s, data_time: 0.052s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.003e-03, size: 544, ETA: 1:38:06
2025-07-31 14:17:27.286 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.148s, data_time: 0.057s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.998e-03, size: 288, ETA: 1:38:04
2025-07-31 14:17:30.228 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.145s, data_time: 0.061s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 2.992e-03, size: 352, ETA: 1:38:01
2025-07-31 14:17:33.190 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.145s, data_time: 0.060s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.987e-03, size: 256, ETA: 1:37:59
2025-07-31 14:17:34.516 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:17:41.016 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:17:44.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:17:46.841 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5767
2025-07-31 14:17:47.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5123
2025-07-31 14:17:47.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3020
2025-07-31 14:17:47.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4637
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.577
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.512
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.302
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.464
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:17:47.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:17:47.470 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:17:47.470 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:17:47.470 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:17:47.470 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:17:50.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:17:52.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:17:55.639 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:17:58.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:18:01.026 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:18:04.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:18:06.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:18:09.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:18:12.363 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:18:12.364 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-31 14:18:12.364 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-31 14:18:12.364 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:18:12.390 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.48 ms, Average NMS time: 1.02 ms, Average inference time: 2.50 ms

2025-07-31 14:18:12.391 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:18:12.418 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:18:12.452 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch266
2025-07-31 14:18:14.962 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.121s, data_time: 0.022s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 2.980e-03, size: 544, ETA: 1:37:55
2025-07-31 14:18:17.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 2.975e-03, size: 576, ETA: 1:37:52
2025-07-31 14:18:20.941 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.969e-03, size: 320, ETA: 1:37:49
2025-07-31 14:18:23.795 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 2.964e-03, size: 320, ETA: 1:37:46
2025-07-31 14:18:26.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 2.959e-03, size: 544, ETA: 1:37:43
2025-07-31 14:18:29.564 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.954e-03, size: 320, ETA: 1:37:41
2025-07-31 14:18:30.777 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:18:30.932 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch267
2025-07-31 14:18:33.903 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.034s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.947e-03, size: 576, ETA: 1:37:37
2025-07-31 14:18:36.873 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.047s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 2.942e-03, size: 512, ETA: 1:37:34
2025-07-31 14:18:39.764 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.044s, total_loss: 5.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 2.936e-03, size: 288, ETA: 1:37:31
2025-07-31 14:18:42.828 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.152s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.931e-03, size: 512, ETA: 1:37:29
2025-07-31 14:18:45.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.146s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.926e-03, size: 384, ETA: 1:37:26
2025-07-31 14:18:48.727 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.921e-03, size: 384, ETA: 1:37:24
2025-07-31 14:18:49.970 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:18:50.024 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch268
2025-07-31 14:18:52.928 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.020s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.914e-03, size: 448, ETA: 1:37:20
2025-07-31 14:18:55.802 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.008s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 2.909e-03, size: 320, ETA: 1:37:17
2025-07-31 14:18:58.795 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.903e-03, size: 544, ETA: 1:37:14
2025-07-31 14:19:01.714 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.898e-03, size: 352, ETA: 1:37:12
2025-07-31 14:19:04.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 2.893e-03, size: 512, ETA: 1:37:09
2025-07-31 14:19:07.587 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.142s, data_time: 0.034s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 2.888e-03, size: 320, ETA: 1:37:07
2025-07-31 14:19:08.913 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:19:08.981 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch269
2025-07-31 14:19:11.876 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.143s, data_time: 0.043s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.881e-03, size: 384, ETA: 1:37:03
2025-07-31 14:19:14.910 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.147s, data_time: 0.013s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.876e-03, size: 288, ETA: 1:37:00
2025-07-31 14:19:17.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 2.871e-03, size: 576, ETA: 1:36:58
2025-07-31 14:19:20.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.866e-03, size: 512, ETA: 1:36:55
2025-07-31 14:19:23.818 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.004s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.861e-03, size: 288, ETA: 1:36:52
2025-07-31 14:19:26.679 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.005s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 2.855e-03, size: 320, ETA: 1:36:50
2025-07-31 14:19:27.978 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:19:28.139 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch270
2025-07-31 14:19:30.814 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.013s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.848e-03, size: 480, ETA: 1:36:45
2025-07-31 14:19:33.736 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.026s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 2.843e-03, size: 448, ETA: 1:36:43
2025-07-31 14:19:36.605 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.010s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.838e-03, size: 384, ETA: 1:36:40
2025-07-31 14:19:39.591 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.007s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.833e-03, size: 480, ETA: 1:36:37
2025-07-31 14:19:42.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 5.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 2.828e-03, size: 352, ETA: 1:36:34
2025-07-31 14:19:45.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.141s, data_time: 0.038s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 2.823e-03, size: 256, ETA: 1:36:32
2025-07-31 14:19:46.627 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:19:53.314 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:19:57.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:20:00.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5673
2025-07-31 14:20:01.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5260
2025-07-31 14:20:01.099 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3488
2025-07-31 14:20:01.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4807
2025-07-31 14:20:01.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:20:01.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:20:01.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.567
2025-07-31 14:20:01.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.526
2025-07-31 14:20:01.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.349
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.481
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:20:01.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:20:04.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:20:07.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:20:11.261 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:20:14.541 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:20:17.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:20:21.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:20:24.540 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:20:27.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:20:31.097 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:20:31.097 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-31 14:20:31.097 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-31 14:20:31.097 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:20:31.123 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 1.01 ms, Average inference time: 2.45 ms

2025-07-31 14:20:31.124 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:20:31.154 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:20:31.187 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch271
2025-07-31 14:20:33.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.129s, data_time: 0.045s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.816e-03, size: 544, ETA: 1:36:28
2025-07-31 14:20:36.698 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.145s, data_time: 0.052s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.811e-03, size: 480, ETA: 1:36:25
2025-07-31 14:20:39.614 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.143s, data_time: 0.033s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 2.806e-03, size: 384, ETA: 1:36:23
2025-07-31 14:20:42.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.144s, data_time: 0.049s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 2.801e-03, size: 384, ETA: 1:36:20
2025-07-31 14:20:45.565 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.147s, data_time: 0.005s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.796e-03, size: 576, ETA: 1:36:18
2025-07-31 14:20:48.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 2.791e-03, size: 384, ETA: 1:36:15
2025-07-31 14:20:49.765 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:20:49.898 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch272
2025-07-31 14:20:52.811 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.783e-03, size: 352, ETA: 1:36:11
2025-07-31 14:20:55.693 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 2.778e-03, size: 352, ETA: 1:36:09
2025-07-31 14:20:58.699 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.145s, data_time: 0.043s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 2.773e-03, size: 416, ETA: 1:36:06
2025-07-31 14:21:01.657 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.147s, data_time: 0.064s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 2.768e-03, size: 576, ETA: 1:36:04
2025-07-31 14:21:04.593 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.043s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 2.763e-03, size: 416, ETA: 1:36:01
2025-07-31 14:21:07.498 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.039s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.758e-03, size: 480, ETA: 1:35:58
2025-07-31 14:21:08.794 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:21:08.834 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch273
2025-07-31 14:21:11.651 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.025s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.9, lr: 2.751e-03, size: 448, ETA: 1:35:54
2025-07-31 14:21:14.551 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.141s, data_time: 0.014s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.746e-03, size: 416, ETA: 1:35:52
2025-07-31 14:21:17.459 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.141s, data_time: 0.042s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 2.741e-03, size: 448, ETA: 1:35:49
2025-07-31 14:21:20.330 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 6.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.736e-03, size: 320, ETA: 1:35:46
2025-07-31 14:21:23.266 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.143s, data_time: 0.007s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 2.731e-03, size: 352, ETA: 1:35:44
2025-07-31 14:21:26.206 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.028s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 2.726e-03, size: 384, ETA: 1:35:41
2025-07-31 14:21:27.490 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:21:27.527 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch274
2025-07-31 14:21:30.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.719e-03, size: 352, ETA: 1:35:37
2025-07-31 14:21:33.440 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.143s, data_time: 0.060s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 2.714e-03, size: 320, ETA: 1:35:35
2025-07-31 14:21:36.461 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.145s, data_time: 0.062s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 2.709e-03, size: 512, ETA: 1:35:32
2025-07-31 14:21:39.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.147s, data_time: 0.058s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 2.704e-03, size: 352, ETA: 1:35:30
2025-07-31 14:21:42.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.140s, data_time: 0.033s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.699e-03, size: 480, ETA: 1:35:27
2025-07-31 14:21:45.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 2.694e-03, size: 544, ETA: 1:35:24
2025-07-31 14:21:46.482 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:21:46.523 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch275
2025-07-31 14:21:49.440 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.142s, data_time: 0.030s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.687e-03, size: 416, ETA: 1:35:20
2025-07-31 14:21:52.400 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.051s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.682e-03, size: 448, ETA: 1:35:18
2025-07-31 14:21:55.356 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.050s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.677e-03, size: 512, ETA: 1:35:15
2025-07-31 14:21:58.336 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.009s, total_loss: 7.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.672e-03, size: 352, ETA: 1:35:12
2025-07-31 14:22:01.217 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.141s, data_time: 0.029s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.667e-03, size: 320, ETA: 1:35:10
2025-07-31 14:22:04.224 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.147s, data_time: 0.033s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 2.663e-03, size: 448, ETA: 1:35:07
2025-07-31 14:22:05.557 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:22:12.086 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:22:14.283 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:22:15.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5618
2025-07-31 14:22:16.035 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5093
2025-07-31 14:22:16.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3201
2025-07-31 14:22:16.096 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4637
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.562
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.509
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.320
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.464
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:22:16.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:22:16.098 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:22:16.098 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:22:16.098 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:22:17.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:22:19.668 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:22:21.443 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:22:23.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:22:24.989 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:22:26.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:22:28.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:22:30.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:22:32.092 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:22:32.092 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-31 14:22:32.093 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-31 14:22:32.093 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:22:32.123 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.48 ms, Average NMS time: 1.04 ms, Average inference time: 2.52 ms

2025-07-31 14:22:32.124 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:22:32.161 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:22:32.209 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch276
2025-07-31 14:22:34.754 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.120s, data_time: 0.020s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.655e-03, size: 416, ETA: 1:35:03
2025-07-31 14:22:37.651 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.018s, total_loss: 5.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 2.651e-03, size: 448, ETA: 1:35:00
2025-07-31 14:22:40.621 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.008s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.646e-03, size: 544, ETA: 1:34:58
2025-07-31 14:22:43.541 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.641e-03, size: 320, ETA: 1:34:55
2025-07-31 14:22:46.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 2.636e-03, size: 480, ETA: 1:34:52
2025-07-31 14:22:49.482 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.029s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.631e-03, size: 576, ETA: 1:34:50
2025-07-31 14:22:50.747 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:22:50.822 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch277
2025-07-31 14:22:53.790 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.147s, data_time: 0.060s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.624e-03, size: 320, ETA: 1:34:46
2025-07-31 14:22:56.783 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.147s, data_time: 0.068s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 2.619e-03, size: 576, ETA: 1:34:44
2025-07-31 14:22:59.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.155s, data_time: 0.064s, total_loss: 6.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.614e-03, size: 448, ETA: 1:34:41
2025-07-31 14:23:02.843 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.145s, data_time: 0.052s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 2.609e-03, size: 448, ETA: 1:34:39
2025-07-31 14:23:05.796 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.145s, data_time: 0.036s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.604e-03, size: 576, ETA: 1:34:36
2025-07-31 14:23:08.721 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.144s, data_time: 0.006s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.600e-03, size: 416, ETA: 1:34:34
2025-07-31 14:23:10.008 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:23:10.120 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch278
2025-07-31 14:23:13.081 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.010s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 2.592e-03, size: 576, ETA: 1:34:30
2025-07-31 14:23:16.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.020s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 2.588e-03, size: 544, ETA: 1:34:27
2025-07-31 14:23:18.943 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.033s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 2.583e-03, size: 576, ETA: 1:34:25
2025-07-31 14:23:21.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.006s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.578e-03, size: 288, ETA: 1:34:22
2025-07-31 14:23:24.705 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 2.573e-03, size: 256, ETA: 1:34:19
2025-07-31 14:23:27.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.568e-03, size: 352, ETA: 1:34:16
2025-07-31 14:23:28.936 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:23:28.981 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch279
2025-07-31 14:23:31.846 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.010s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 2.561e-03, size: 352, ETA: 1:34:13
2025-07-31 14:23:34.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.140s, data_time: 0.019s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.556e-03, size: 448, ETA: 1:34:10
2025-07-31 14:23:37.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.148s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.552e-03, size: 384, ETA: 1:34:08
2025-07-31 14:23:40.691 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.547e-03, size: 480, ETA: 1:34:05
2025-07-31 14:23:43.569 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.014s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 2.542e-03, size: 256, ETA: 1:34:02
2025-07-31 14:23:46.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.147s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 2.537e-03, size: 544, ETA: 1:34:00
2025-07-31 14:23:47.953 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:23:48.014 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch280
2025-07-31 14:23:50.844 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.022s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.530e-03, size: 480, ETA: 1:33:56
2025-07-31 14:23:53.781 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.024s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 2.525e-03, size: 256, ETA: 1:33:53
2025-07-31 14:23:56.790 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.008s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.521e-03, size: 256, ETA: 1:33:50
2025-07-31 14:23:59.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.516e-03, size: 448, ETA: 1:33:48
2025-07-31 14:24:02.590 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.131s, data_time: 0.027s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.511e-03, size: 480, ETA: 1:33:45
2025-07-31 14:24:05.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.506e-03, size: 544, ETA: 1:33:42
2025-07-31 14:24:06.929 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:24:13.351 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:24:14.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:24:15.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5942
2025-07-31 14:24:15.566 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5299
2025-07-31 14:24:15.617 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3707
2025-07-31 14:24:15.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4983
2025-07-31 14:24:15.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:24:15.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:24:15.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.594
2025-07-31 14:24:15.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.530
2025-07-31 14:24:15.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.371
2025-07-31 14:24:15.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.498
2025-07-31 14:24:15.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:24:15.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:24:15.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:24:15.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:24:15.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:24:15.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:24:15.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:24:15.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:24:15.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:24:16.613 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:24:17.589 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:24:18.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:24:19.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:24:20.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:24:21.397 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:24:22.336 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:24:23.331 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:24:24.343 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:24:24.343 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 14:24:24.343 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-31 14:24:24.343 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:24:24.351 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 0.96 ms, Average inference time: 2.42 ms

2025-07-31 14:24:24.353 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:24:24.381 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:24:24.414 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch281
2025-07-31 14:24:26.951 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.120s, data_time: 0.011s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.499e-03, size: 480, ETA: 1:33:38
2025-07-31 14:24:29.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.495e-03, size: 544, ETA: 1:33:35
2025-07-31 14:24:32.716 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 2.490e-03, size: 576, ETA: 1:33:32
2025-07-31 14:24:35.586 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.010s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 2.485e-03, size: 448, ETA: 1:33:30
2025-07-31 14:24:38.624 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.148s, data_time: 0.007s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.480e-03, size: 416, ETA: 1:33:27
2025-07-31 14:24:41.647 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.150s, data_time: 0.003s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.475e-03, size: 384, ETA: 1:33:25
2025-07-31 14:24:42.997 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:24:43.057 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch282
2025-07-31 14:24:45.897 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.469e-03, size: 384, ETA: 1:33:21
2025-07-31 14:24:48.835 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.015s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.6, lr: 2.464e-03, size: 352, ETA: 1:33:18
2025-07-31 14:24:51.749 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.005s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 2.459e-03, size: 576, ETA: 1:33:16
2025-07-31 14:24:54.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.011s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 1.0, lr: 2.454e-03, size: 384, ETA: 1:33:13
2025-07-31 14:24:57.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 2.450e-03, size: 416, ETA: 1:33:11
2025-07-31 14:25:00.546 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.445e-03, size: 544, ETA: 1:33:08
2025-07-31 14:25:01.824 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:25:01.864 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch283
2025-07-31 14:25:04.850 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.148s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 2.438e-03, size: 448, ETA: 1:33:04
2025-07-31 14:25:07.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.146s, data_time: 0.037s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.433e-03, size: 320, ETA: 1:33:02
2025-07-31 14:25:10.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.146s, data_time: 0.041s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.429e-03, size: 352, ETA: 1:32:59
2025-07-31 14:25:13.839 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.150s, data_time: 0.065s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 2.424e-03, size: 256, ETA: 1:32:57
2025-07-31 14:25:16.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.144s, data_time: 0.059s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.419e-03, size: 448, ETA: 1:32:54
2025-07-31 14:25:19.701 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.144s, data_time: 0.057s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 2.414e-03, size: 512, ETA: 1:32:52
2025-07-31 14:25:21.030 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:25:21.071 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch284
2025-07-31 14:25:24.060 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.022s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 2.408e-03, size: 512, ETA: 1:32:48
2025-07-31 14:25:26.937 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.016s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 2.403e-03, size: 448, ETA: 1:32:45
2025-07-31 14:25:30.018 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.153s, data_time: 0.068s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.398e-03, size: 480, ETA: 1:32:43
2025-07-31 14:25:32.961 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.144s, data_time: 0.057s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.394e-03, size: 480, ETA: 1:32:40
2025-07-31 14:25:35.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.045s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.389e-03, size: 544, ETA: 1:32:37
2025-07-31 14:25:38.694 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.042s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.384e-03, size: 384, ETA: 1:32:34
2025-07-31 14:25:39.972 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:25:40.149 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch285
2025-07-31 14:25:43.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.021s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 2.378e-03, size: 576, ETA: 1:32:30
2025-07-31 14:25:45.940 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.373e-03, size: 416, ETA: 1:32:27
2025-07-31 14:25:48.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.004s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.368e-03, size: 544, ETA: 1:32:25
2025-07-31 14:25:51.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.007s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 2.364e-03, size: 416, ETA: 1:32:22
2025-07-31 14:25:54.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.045s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 2.359e-03, size: 416, ETA: 1:32:19
2025-07-31 14:25:57.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.019s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 2.354e-03, size: 448, ETA: 1:32:16
2025-07-31 14:25:59.014 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:26:05.239 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:26:07.508 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:26:08.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5945
2025-07-31 14:26:09.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5529
2025-07-31 14:26:09.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3502
2025-07-31 14:26:09.363 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4992
2025-07-31 14:26:09.363 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.595
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.553
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.350
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.499
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:26:09.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:26:09.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:26:09.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:26:09.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:26:09.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:26:11.203 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:26:13.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:26:14.879 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:26:16.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:26:18.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:26:20.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:26:21.987 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:26:23.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:26:25.612 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:26:25.612 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 14:26:25.613 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-31 14:26:25.613 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:26:25.638 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 1.03 ms, Average inference time: 2.47 ms

2025-07-31 14:26:25.639 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:26:25.671 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:26:25.704 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch286
2025-07-31 14:26:28.267 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.122s, data_time: 0.038s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.348e-03, size: 384, ETA: 1:32:12
2025-07-31 14:26:31.333 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.3Gb, iter_time: 0.152s, data_time: 0.063s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 2.343e-03, size: 352, ETA: 1:32:10
2025-07-31 14:26:34.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.050s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 2.338e-03, size: 416, ETA: 1:32:07
2025-07-31 14:26:37.143 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.027s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.334e-03, size: 480, ETA: 1:32:04
2025-07-31 14:26:40.063 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.025s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 2.329e-03, size: 256, ETA: 1:32:02
2025-07-31 14:26:42.973 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.144s, data_time: 0.034s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 2.324e-03, size: 576, ETA: 1:31:59
2025-07-31 14:26:44.239 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:26:44.306 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch287
2025-07-31 14:26:47.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.015s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.318e-03, size: 544, ETA: 1:31:55
2025-07-31 14:26:50.248 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 2.313e-03, size: 544, ETA: 1:31:52
2025-07-31 14:26:53.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.308e-03, size: 352, ETA: 1:31:49
2025-07-31 14:26:56.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.009s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.304e-03, size: 320, ETA: 1:31:46
2025-07-31 14:26:58.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.035s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.6, lr: 2.299e-03, size: 448, ETA: 1:31:43
2025-07-31 14:27:01.897 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.027s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.295e-03, size: 544, ETA: 1:31:40
2025-07-31 14:27:03.153 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:27:03.247 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch288
2025-07-31 14:27:06.165 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.022s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.288e-03, size: 544, ETA: 1:31:36
2025-07-31 14:27:09.098 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.022s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 2.283e-03, size: 416, ETA: 1:31:34
2025-07-31 14:27:12.077 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 2.279e-03, size: 480, ETA: 1:31:31
2025-07-31 14:27:15.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 2.274e-03, size: 512, ETA: 1:31:28
2025-07-31 14:27:18.042 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.270e-03, size: 320, ETA: 1:31:25
2025-07-31 14:27:20.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 2.265e-03, size: 448, ETA: 1:31:22
2025-07-31 14:27:22.211 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:27:22.328 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch289
2025-07-31 14:27:25.183 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.028s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.6, lr: 2.259e-03, size: 416, ETA: 1:31:18
2025-07-31 14:27:28.048 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.254e-03, size: 512, ETA: 1:31:15
2025-07-31 14:27:30.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.011s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.250e-03, size: 576, ETA: 1:31:12
2025-07-31 14:27:33.898 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 2.245e-03, size: 544, ETA: 1:31:10
2025-07-31 14:27:36.968 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.240e-03, size: 544, ETA: 1:31:07
2025-07-31 14:27:40.040 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 2.236e-03, size: 320, ETA: 1:31:04
2025-07-31 14:27:41.374 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:27:41.415 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch290
2025-07-31 14:27:44.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 2.229e-03, size: 448, ETA: 1:31:00
2025-07-31 14:27:47.317 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.225e-03, size: 576, ETA: 1:30:57
2025-07-31 14:27:50.301 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.220e-03, size: 448, ETA: 1:30:54
2025-07-31 14:27:53.257 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 2.216e-03, size: 256, ETA: 1:30:52
2025-07-31 14:27:56.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.038s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.211e-03, size: 384, ETA: 1:30:49
2025-07-31 14:27:59.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.032s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.207e-03, size: 416, ETA: 1:30:46
2025-07-31 14:28:00.457 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:28:06.892 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:28:08.305 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:28:09.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5776
2025-07-31 14:28:09.422 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5155
2025-07-31 14:28:09.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3332
2025-07-31 14:28:09.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4754
2025-07-31 14:28:09.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:28:09.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:28:09.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.578
2025-07-31 14:28:09.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.516
2025-07-31 14:28:09.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.333
2025-07-31 14:28:09.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.475
2025-07-31 14:28:09.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:28:09.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:28:09.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:28:09.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:28:09.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:28:09.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:28:09.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:28:09.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:28:09.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:28:10.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:28:11.593 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:28:12.620 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:28:13.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:28:14.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:28:15.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:28:16.784 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:28:17.849 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:28:18.960 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:28:18.960 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-31 14:28:18.961 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-31 14:28:18.961 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:28:18.971 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.99 ms, Average inference time: 2.40 ms

2025-07-31 14:28:18.974 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:28:19.000 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:28:19.033 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch291
2025-07-31 14:28:21.585 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.119s, data_time: 0.022s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.200e-03, size: 288, ETA: 1:30:42
2025-07-31 14:28:24.509 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.196e-03, size: 416, ETA: 1:30:39
2025-07-31 14:28:27.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.191e-03, size: 256, ETA: 1:30:37
2025-07-31 14:28:30.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.142s, data_time: 0.004s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 2.187e-03, size: 512, ETA: 1:30:34
2025-07-31 14:28:33.269 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.144s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 2.182e-03, size: 320, ETA: 1:30:32
2025-07-31 14:28:36.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.148s, data_time: 0.033s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 2.178e-03, size: 448, ETA: 1:30:29
2025-07-31 14:28:37.577 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:28:37.769 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch292
2025-07-31 14:28:40.656 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.048s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 2.171e-03, size: 352, ETA: 1:30:25
2025-07-31 14:28:43.697 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.142s, data_time: 0.020s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 2.167e-03, size: 256, ETA: 1:30:23
2025-07-31 14:28:46.686 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.163e-03, size: 288, ETA: 1:30:20
2025-07-31 14:28:49.666 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.039s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.158e-03, size: 320, ETA: 1:30:17
2025-07-31 14:28:52.470 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.041s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.154e-03, size: 416, ETA: 1:30:15
2025-07-31 14:28:55.411 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.146s, data_time: 0.057s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.149e-03, size: 512, ETA: 1:30:12
2025-07-31 14:28:56.611 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:28:56.759 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch293
2025-07-31 14:28:59.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.018s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 2.143e-03, size: 256, ETA: 1:30:08
2025-07-31 14:29:02.445 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.050s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.138e-03, size: 544, ETA: 1:30:05
2025-07-31 14:29:05.414 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.144s, data_time: 0.014s, total_loss: 6.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.134e-03, size: 480, ETA: 1:30:03
2025-07-31 14:29:08.412 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.053s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.130e-03, size: 544, ETA: 1:30:00
2025-07-31 14:29:11.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.020s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 2.125e-03, size: 416, ETA: 1:29:57
2025-07-31 14:29:14.277 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.036s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 2.121e-03, size: 288, ETA: 1:29:54
2025-07-31 14:29:15.581 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:29:15.732 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch294
2025-07-31 14:29:18.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.047s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 2.114e-03, size: 352, ETA: 1:29:50
2025-07-31 14:29:21.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.029s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.110e-03, size: 320, ETA: 1:29:48
2025-07-31 14:29:24.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.106e-03, size: 352, ETA: 1:29:45
2025-07-31 14:29:27.419 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.008s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.101e-03, size: 416, ETA: 1:29:42
2025-07-31 14:29:30.399 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.097e-03, size: 320, ETA: 1:29:39
2025-07-31 14:29:33.331 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 2.092e-03, size: 256, ETA: 1:29:36
2025-07-31 14:29:34.561 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:29:34.730 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch295
2025-07-31 14:29:37.705 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 2.086e-03, size: 416, ETA: 1:29:32
2025-07-31 14:29:40.619 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.004s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.082e-03, size: 352, ETA: 1:29:29
2025-07-31 14:29:43.727 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.007s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.077e-03, size: 544, ETA: 1:29:27
2025-07-31 14:29:46.719 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.130s, data_time: 0.013s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.073e-03, size: 576, ETA: 1:29:24
2025-07-31 14:29:49.647 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.043s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.069e-03, size: 544, ETA: 1:29:21
2025-07-31 14:29:52.537 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.046s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 2.064e-03, size: 352, ETA: 1:29:18
2025-07-31 14:29:53.876 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:30:00.299 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:30:03.395 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:30:05.516 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5658
2025-07-31 14:30:05.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5300
2025-07-31 14:30:06.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3128
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4695
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.566
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.530
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.313
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.470
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:30:06.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:30:06.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:30:06.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:30:06.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:30:06.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:30:06.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:30:08.539 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:30:11.239 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:30:13.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:30:16.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:30:18.600 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:30:21.026 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:30:23.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:30:25.937 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:30:28.408 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:30:28.408 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-31 14:30:28.408 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-31 14:30:28.409 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:30:28.434 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 1.01 ms, Average inference time: 2.48 ms

2025-07-31 14:30:28.435 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:30:28.461 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:30:28.506 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch296
2025-07-31 14:30:31.059 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.039s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 2.058e-03, size: 480, ETA: 1:29:14
2025-07-31 14:30:34.030 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.017s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 2.054e-03, size: 512, ETA: 1:29:11
2025-07-31 14:30:36.959 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.029s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.049e-03, size: 544, ETA: 1:29:09
2025-07-31 14:30:39.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.040s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 2.045e-03, size: 320, ETA: 1:29:06
2025-07-31 14:30:43.010 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.024s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 2.041e-03, size: 544, ETA: 1:29:03
2025-07-31 14:30:45.904 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.014s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.036e-03, size: 320, ETA: 1:29:01
2025-07-31 14:30:47.286 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:30:47.428 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch297
2025-07-31 14:30:50.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.122s, data_time: 0.018s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 2.030e-03, size: 448, ETA: 1:28:56
2025-07-31 14:30:53.255 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.043s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 2.026e-03, size: 416, ETA: 1:28:54
2025-07-31 14:30:56.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.051s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.021e-03, size: 352, ETA: 1:28:51
2025-07-31 14:30:59.103 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.053s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 2.017e-03, size: 288, ETA: 1:28:48
2025-07-31 14:31:02.129 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.040s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 2.013e-03, size: 288, ETA: 1:28:46
2025-07-31 14:31:05.038 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.033s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 2.009e-03, size: 544, ETA: 1:28:43
2025-07-31 14:31:06.419 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:31:06.448 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch298
2025-07-31 14:31:09.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.142s, data_time: 0.062s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.002e-03, size: 448, ETA: 1:28:39
2025-07-31 14:31:12.309 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.148s, data_time: 0.062s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 1.998e-03, size: 544, ETA: 1:28:37
2025-07-31 14:31:15.216 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.053s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 1.994e-03, size: 256, ETA: 1:28:34
2025-07-31 14:31:18.115 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.036s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 1.990e-03, size: 256, ETA: 1:28:31
2025-07-31 14:31:21.010 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.985e-03, size: 512, ETA: 1:28:29
2025-07-31 14:31:24.108 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.2, lr: 1.981e-03, size: 288, ETA: 1:28:26
2025-07-31 14:31:25.378 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:31:25.510 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch299
2025-07-31 14:31:28.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 1.975e-03, size: 544, ETA: 1:28:22
2025-07-31 14:31:31.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.971e-03, size: 512, ETA: 1:28:19
2025-07-31 14:31:34.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 1.966e-03, size: 416, ETA: 1:28:16
2025-07-31 14:31:37.172 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 5.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 1.962e-03, size: 352, ETA: 1:28:13
2025-07-31 14:31:40.206 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.958e-03, size: 448, ETA: 1:28:10
2025-07-31 14:31:43.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.954e-03, size: 480, ETA: 1:28:07
2025-07-31 14:31:44.533 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:31:44.576 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch300
2025-07-31 14:31:47.414 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.948e-03, size: 256, ETA: 1:28:03
2025-07-31 14:31:50.305 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.130s, data_time: 0.036s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 1.943e-03, size: 256, ETA: 1:28:01
2025-07-31 14:31:53.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.013s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.9, lr: 1.939e-03, size: 320, ETA: 1:27:58
2025-07-31 14:31:56.274 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.935e-03, size: 480, ETA: 1:27:55
2025-07-31 14:31:59.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.6, lr: 1.931e-03, size: 512, ETA: 1:27:52
2025-07-31 14:32:02.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.927e-03, size: 512, ETA: 1:27:49
2025-07-31 14:32:03.427 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:32:09.879 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:32:11.674 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:32:12.622 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5509
2025-07-31 14:32:12.886 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5257
2025-07-31 14:32:12.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2903
2025-07-31 14:32:12.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4556
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.551
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.526
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.290
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.456
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:32:12.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:32:12.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:32:12.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:32:12.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:32:14.241 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:32:15.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:32:16.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:32:18.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:32:19.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:32:20.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:32:21.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:32:23.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:32:24.358 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:32:24.358 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-31 14:32:24.358 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-31 14:32:24.358 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:32:24.366 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 1.01 ms, Average inference time: 2.46 ms

2025-07-31 14:32:24.367 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:32:24.393 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:32:24.426 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch301
2025-07-31 14:32:26.969 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.126s, data_time: 0.040s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.921e-03, size: 288, ETA: 1:27:45
2025-07-31 14:32:29.928 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.049s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.916e-03, size: 544, ETA: 1:27:43
2025-07-31 14:32:32.791 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.912e-03, size: 480, ETA: 1:27:40
2025-07-31 14:32:35.795 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.147s, data_time: 0.005s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 1.908e-03, size: 288, ETA: 1:27:37
2025-07-31 14:32:38.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.148s, data_time: 0.007s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.9, lr: 1.904e-03, size: 352, ETA: 1:27:35
2025-07-31 14:32:41.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.145s, data_time: 0.003s, total_loss: 5.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 1.900e-03, size: 544, ETA: 1:27:32
2025-07-31 14:32:42.986 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:32:43.067 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch302
2025-07-31 14:32:45.934 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.024s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.894e-03, size: 512, ETA: 1:27:28
2025-07-31 14:32:48.903 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.004s, total_loss: 4.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 1.890e-03, size: 480, ETA: 1:27:26
2025-07-31 14:32:51.821 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.886e-03, size: 544, ETA: 1:27:23
2025-07-31 14:32:54.707 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.020s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.881e-03, size: 480, ETA: 1:27:20
2025-07-31 14:32:57.675 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.041s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.877e-03, size: 320, ETA: 1:27:17
2025-07-31 14:33:00.631 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.028s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.873e-03, size: 480, ETA: 1:27:15
2025-07-31 14:33:01.854 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:33:01.983 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch303
2025-07-31 14:33:04.976 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 1.867e-03, size: 288, ETA: 1:27:11
2025-07-31 14:33:07.959 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.863e-03, size: 352, ETA: 1:27:08
2025-07-31 14:33:10.873 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.024s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.859e-03, size: 256, ETA: 1:27:05
2025-07-31 14:33:13.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.017s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.855e-03, size: 256, ETA: 1:27:02
2025-07-31 14:33:16.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 1.851e-03, size: 448, ETA: 1:26:59
2025-07-31 14:33:19.714 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.5, lr: 1.847e-03, size: 416, ETA: 1:26:57
2025-07-31 14:33:21.002 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:33:21.163 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch304
2025-07-31 14:33:24.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.841e-03, size: 352, ETA: 1:26:53
2025-07-31 14:33:27.047 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.037s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.837e-03, size: 544, ETA: 1:26:50
2025-07-31 14:33:30.157 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.151s, data_time: 0.065s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 1.833e-03, size: 416, ETA: 1:26:48
2025-07-31 14:33:33.018 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.829e-03, size: 256, ETA: 1:26:45
2025-07-31 14:33:35.995 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.027s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.824e-03, size: 288, ETA: 1:26:42
2025-07-31 14:33:38.818 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.008s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 1.820e-03, size: 288, ETA: 1:26:40
2025-07-31 14:33:40.161 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:33:40.313 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch305
2025-07-31 14:33:43.108 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.037s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.815e-03, size: 288, ETA: 1:26:35
2025-07-31 14:33:46.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.020s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.811e-03, size: 384, ETA: 1:26:33
2025-07-31 14:33:49.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.806e-03, size: 576, ETA: 1:26:30
2025-07-31 14:33:52.171 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 1.802e-03, size: 384, ETA: 1:26:27
2025-07-31 14:33:55.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.007s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.798e-03, size: 256, ETA: 1:26:24
2025-07-31 14:33:57.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.041s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.1, lr: 1.794e-03, size: 256, ETA: 1:26:21
2025-07-31 14:33:59.225 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:34:05.756 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:34:07.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:34:09.203 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5604
2025-07-31 14:34:09.496 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5198
2025-07-31 14:34:09.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3476
2025-07-31 14:34:09.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4759
2025-07-31 14:34:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:34:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:34:09.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.560
2025-07-31 14:34:09.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.520
2025-07-31 14:34:09.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.348
2025-07-31 14:34:09.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.476
2025-07-31 14:34:09.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:34:09.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:34:09.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:34:09.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:34:09.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:34:09.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:34:09.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:34:09.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:34:09.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:34:11.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:34:12.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:34:14.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:34:16.577 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:34:18.233 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:34:19.868 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:34:21.519 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:34:23.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:34:24.773 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:34:24.773 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-31 14:34:24.773 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-31 14:34:24.773 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:34:24.801 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.98 ms, Average inference time: 2.42 ms

2025-07-31 14:34:24.803 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:34:24.835 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:34:24.871 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch306
2025-07-31 14:34:27.313 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.114s, data_time: 0.029s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.789e-03, size: 544, ETA: 1:26:17
2025-07-31 14:34:30.306 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 1.785e-03, size: 384, ETA: 1:26:14
2025-07-31 14:34:33.297 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.024s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.781e-03, size: 576, ETA: 1:26:12
2025-07-31 14:34:36.197 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.023s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 1.777e-03, size: 352, ETA: 1:26:09
2025-07-31 14:34:39.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.773e-03, size: 480, ETA: 1:26:06
2025-07-31 14:34:42.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.769e-03, size: 544, ETA: 1:26:03
2025-07-31 14:34:43.358 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:34:43.469 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch307
2025-07-31 14:34:46.434 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 1.763e-03, size: 256, ETA: 1:25:59
2025-07-31 14:34:49.472 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 1.759e-03, size: 544, ETA: 1:25:56
2025-07-31 14:34:52.432 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.026s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.755e-03, size: 288, ETA: 1:25:54
2025-07-31 14:34:55.333 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.010s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.751e-03, size: 512, ETA: 1:25:51
2025-07-31 14:34:58.366 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.747e-03, size: 544, ETA: 1:25:48
2025-07-31 14:35:01.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.010s, total_loss: 5.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 1.743e-03, size: 352, ETA: 1:25:45
2025-07-31 14:35:02.633 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:35:02.677 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch308
2025-07-31 14:35:05.688 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.142s, data_time: 0.022s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.737e-03, size: 576, ETA: 1:25:41
2025-07-31 14:35:08.523 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.016s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 1.733e-03, size: 576, ETA: 1:25:39
2025-07-31 14:35:11.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.006s, total_loss: 7.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.729e-03, size: 256, ETA: 1:25:36
2025-07-31 14:35:14.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.6, lr: 1.725e-03, size: 416, ETA: 1:25:33
2025-07-31 14:35:17.470 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.137s, data_time: 0.032s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.722e-03, size: 480, ETA: 1:25:31
2025-07-31 14:35:20.412 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.718e-03, size: 416, ETA: 1:25:28
2025-07-31 14:35:21.745 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:35:21.856 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch309
2025-07-31 14:35:24.732 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.008s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.712e-03, size: 480, ETA: 1:25:24
2025-07-31 14:35:27.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.022s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.708e-03, size: 384, ETA: 1:25:21
2025-07-31 14:35:30.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.026s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 1.704e-03, size: 448, ETA: 1:25:18
2025-07-31 14:35:33.531 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.148s, data_time: 0.032s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.700e-03, size: 256, ETA: 1:25:16
2025-07-31 14:35:36.495 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.145s, data_time: 0.008s, total_loss: 6.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.6, lr: 1.696e-03, size: 384, ETA: 1:25:13
2025-07-31 14:35:39.549 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.149s, data_time: 0.054s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 1.692e-03, size: 544, ETA: 1:25:11
2025-07-31 14:35:40.820 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:35:40.875 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch310
2025-07-31 14:35:43.787 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.137s, data_time: 0.024s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.687e-03, size: 448, ETA: 1:25:07
2025-07-31 14:35:46.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.029s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.683e-03, size: 480, ETA: 1:25:04
2025-07-31 14:35:49.675 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.679e-03, size: 480, ETA: 1:25:01
2025-07-31 14:35:52.510 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.124s, data_time: 0.014s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.675e-03, size: 320, ETA: 1:24:58
2025-07-31 14:35:55.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.010s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.671e-03, size: 576, ETA: 1:24:56
2025-07-31 14:35:58.447 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.014s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.668e-03, size: 544, ETA: 1:24:53
2025-07-31 14:35:59.795 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:36:06.353 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:36:07.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:36:08.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5894
2025-07-31 14:36:08.857 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5304
2025-07-31 14:36:08.908 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3345
2025-07-31 14:36:08.908 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4848
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.589
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.530
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.335
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.485
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:36:08.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:36:08.910 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:36:08.910 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:36:08.910 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:36:08.910 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:36:09.986 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:36:11.065 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:36:12.131 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:36:13.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:36:14.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:36:15.406 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:36:16.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:36:17.588 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:36:18.669 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:36:18.669 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 14:36:18.669 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-31 14:36:18.670 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:36:18.683 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.98 ms, Average inference time: 2.42 ms

2025-07-31 14:36:18.684 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:36:18.721 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:36:18.765 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch311
2025-07-31 14:36:21.524 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.048s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.662e-03, size: 416, ETA: 1:24:49
2025-07-31 14:36:24.400 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.056s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.658e-03, size: 288, ETA: 1:24:47
2025-07-31 14:36:27.393 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.149s, data_time: 0.060s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.654e-03, size: 480, ETA: 1:24:44
2025-07-31 14:36:30.509 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.155s, data_time: 0.062s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.650e-03, size: 320, ETA: 1:24:42
2025-07-31 14:36:33.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.148s, data_time: 0.057s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.647e-03, size: 576, ETA: 1:24:39
2025-07-31 14:36:36.522 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.151s, data_time: 0.063s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.643e-03, size: 448, ETA: 1:24:37
2025-07-31 14:36:37.764 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:36:37.828 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch312
2025-07-31 14:36:40.793 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.147s, data_time: 0.055s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.637e-03, size: 352, ETA: 1:24:33
2025-07-31 14:36:43.852 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.151s, data_time: 0.065s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.634e-03, size: 288, ETA: 1:24:31
2025-07-31 14:36:47.012 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.157s, data_time: 0.069s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.630e-03, size: 352, ETA: 1:24:28
2025-07-31 14:36:49.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.039s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.626e-03, size: 416, ETA: 1:24:26
2025-07-31 14:36:52.899 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.622e-03, size: 544, ETA: 1:24:23
2025-07-31 14:36:55.656 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.618e-03, size: 544, ETA: 1:24:20
2025-07-31 14:36:56.921 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:36:56.971 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch313
2025-07-31 14:36:59.852 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.613e-03, size: 288, ETA: 1:24:16
2025-07-31 14:37:02.883 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.008s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.609e-03, size: 544, ETA: 1:24:14
2025-07-31 14:37:05.835 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.024s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.8, lr: 1.605e-03, size: 512, ETA: 1:24:11
2025-07-31 14:37:08.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.602e-03, size: 352, ETA: 1:24:08
2025-07-31 14:37:11.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.598e-03, size: 576, ETA: 1:24:05
2025-07-31 14:37:14.629 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.8, lr: 1.594e-03, size: 384, ETA: 1:24:03
2025-07-31 14:37:15.828 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:37:15.904 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch314
2025-07-31 14:37:18.922 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.014s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.589e-03, size: 512, ETA: 1:23:59
2025-07-31 14:37:21.854 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.142s, data_time: 0.054s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.585e-03, size: 512, ETA: 1:23:56
2025-07-31 14:37:24.845 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.038s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.1, lr: 1.581e-03, size: 320, ETA: 1:23:54
2025-07-31 14:37:27.796 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.145s, data_time: 0.052s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.578e-03, size: 512, ETA: 1:23:51
2025-07-31 14:37:30.701 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.058s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.574e-03, size: 512, ETA: 1:23:48
2025-07-31 14:37:33.749 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.151s, data_time: 0.058s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 1.570e-03, size: 288, ETA: 1:23:46
2025-07-31 14:37:35.038 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:37:35.081 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch315
2025-07-31 14:37:37.940 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.142s, data_time: 0.057s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 1.565e-03, size: 384, ETA: 1:23:42
2025-07-31 14:37:40.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.145s, data_time: 0.047s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.561e-03, size: 544, ETA: 1:23:40
2025-07-31 14:37:43.860 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.557e-03, size: 384, ETA: 1:23:37
2025-07-31 14:37:46.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.057s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.554e-03, size: 352, ETA: 1:23:34
2025-07-31 14:37:49.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.020s, total_loss: 5.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 1.550e-03, size: 416, ETA: 1:23:31
2025-07-31 14:37:52.751 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.124s, data_time: 0.006s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.546e-03, size: 544, ETA: 1:23:29
2025-07-31 14:37:53.989 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:38:00.508 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:38:02.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:38:04.267 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5922
2025-07-31 14:38:04.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5476
2025-07-31 14:38:04.668 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3258
2025-07-31 14:38:04.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4885
2025-07-31 14:38:04.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:38:04.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:38:04.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.592
2025-07-31 14:38:04.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.548
2025-07-31 14:38:04.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.326
2025-07-31 14:38:04.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.489
2025-07-31 14:38:04.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:38:04.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:38:04.670 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:38:04.670 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:38:04.670 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:38:04.670 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:38:04.670 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:38:04.670 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:38:04.670 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:38:06.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:38:08.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:38:10.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:38:12.264 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:38:14.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:38:16.134 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:38:18.049 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:38:19.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:38:21.896 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:38:21.896 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 14:38:21.896 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-07-31 14:38:21.896 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:38:21.926 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 1.05 ms, Average inference time: 2.52 ms

2025-07-31 14:38:21.928 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:38:21.959 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:38:21.992 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch316
2025-07-31 14:38:24.519 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.122s, data_time: 0.043s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 1.0, lr: 1.541e-03, size: 288, ETA: 1:23:24
2025-07-31 14:38:27.384 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.041s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.537e-03, size: 416, ETA: 1:23:21
2025-07-31 14:38:30.257 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.015s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.534e-03, size: 512, ETA: 1:23:19
2025-07-31 14:38:33.147 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.039s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.530e-03, size: 416, ETA: 1:23:16
2025-07-31 14:38:36.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.014s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.526e-03, size: 256, ETA: 1:23:13
2025-07-31 14:38:39.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.523e-03, size: 384, ETA: 1:23:11
2025-07-31 14:38:40.601 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:38:40.737 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch317
2025-07-31 14:38:43.705 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.518e-03, size: 480, ETA: 1:23:07
2025-07-31 14:38:46.595 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.514e-03, size: 352, ETA: 1:23:04
2025-07-31 14:38:49.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.510e-03, size: 544, ETA: 1:23:01
2025-07-31 14:38:52.545 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.021s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.507e-03, size: 320, ETA: 1:22:58
2025-07-31 14:38:55.504 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.004s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.503e-03, size: 544, ETA: 1:22:56
2025-07-31 14:38:58.397 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.008s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.500e-03, size: 256, ETA: 1:22:53
2025-07-31 14:38:59.674 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:38:59.812 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch318
2025-07-31 14:39:02.740 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.006s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.494e-03, size: 384, ETA: 1:22:49
2025-07-31 14:39:05.707 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.144s, data_time: 0.021s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.491e-03, size: 320, ETA: 1:22:47
2025-07-31 14:39:08.591 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.487e-03, size: 288, ETA: 1:22:44
2025-07-31 14:39:11.546 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.147s, data_time: 0.060s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 1.484e-03, size: 480, ETA: 1:22:41
2025-07-31 14:39:14.438 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.480e-03, size: 480, ETA: 1:22:39
2025-07-31 14:39:17.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.020s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 1.476e-03, size: 384, ETA: 1:22:36
2025-07-31 14:39:18.608 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:39:18.712 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch319
2025-07-31 14:39:21.658 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.046s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.471e-03, size: 576, ETA: 1:22:32
2025-07-31 14:39:24.591 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.021s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.468e-03, size: 480, ETA: 1:22:29
2025-07-31 14:39:27.491 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.125s, data_time: 0.012s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.464e-03, size: 480, ETA: 1:22:26
2025-07-31 14:39:30.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.051s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.461e-03, size: 544, ETA: 1:22:24
2025-07-31 14:39:33.356 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.044s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.457e-03, size: 384, ETA: 1:22:21
2025-07-31 14:39:36.253 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.142s, data_time: 0.058s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.454e-03, size: 288, ETA: 1:22:18
2025-07-31 14:39:37.656 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:39:37.707 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch320
2025-07-31 14:39:40.559 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.051s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 1.449e-03, size: 288, ETA: 1:22:14
2025-07-31 14:39:43.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 5.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.6, lr: 1.445e-03, size: 256, ETA: 1:22:12
2025-07-31 14:39:46.493 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.146s, data_time: 0.059s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 1.442e-03, size: 544, ETA: 1:22:09
2025-07-31 14:39:49.552 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.151s, data_time: 0.062s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.438e-03, size: 320, ETA: 1:22:07
2025-07-31 14:39:52.400 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.051s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.435e-03, size: 544, ETA: 1:22:04
2025-07-31 14:39:55.363 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.142s, data_time: 0.024s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.431e-03, size: 576, ETA: 1:22:02
2025-07-31 14:39:56.605 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:40:03.164 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:40:05.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:40:06.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5974
2025-07-31 14:40:06.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5528
2025-07-31 14:40:06.824 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3587
2025-07-31 14:40:06.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5030
2025-07-31 14:40:06.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:40:06.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:40:06.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.597
2025-07-31 14:40:06.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.553
2025-07-31 14:40:06.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.359
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.503
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:40:06.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:40:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:40:10.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:40:11.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:40:13.419 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:40:14.984 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:40:16.675 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:40:18.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:40:19.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:40:21.639 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:40:21.639 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 14:40:21.639 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-31 14:40:21.639 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:40:21.667 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 1.01 ms, Average inference time: 2.48 ms

2025-07-31 14:40:21.668 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:40:21.700 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:40:21.734 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch321
2025-07-31 14:40:24.252 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.122s, data_time: 0.028s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 1.426e-03, size: 352, ETA: 1:21:57
2025-07-31 14:40:27.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.050s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.423e-03, size: 416, ETA: 1:21:55
2025-07-31 14:40:30.211 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.031s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.419e-03, size: 416, ETA: 1:21:52
2025-07-31 14:40:33.235 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.019s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.416e-03, size: 384, ETA: 1:21:49
2025-07-31 14:40:36.224 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.412e-03, size: 320, ETA: 1:21:47
2025-07-31 14:40:39.156 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.015s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 1.409e-03, size: 416, ETA: 1:21:44
2025-07-31 14:40:40.385 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:40:40.511 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch322
2025-07-31 14:40:43.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.039s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.404e-03, size: 576, ETA: 1:21:40
2025-07-31 14:40:46.492 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.150s, data_time: 0.063s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 1.400e-03, size: 384, ETA: 1:21:37
2025-07-31 14:40:49.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.050s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.397e-03, size: 512, ETA: 1:21:35
2025-07-31 14:40:52.273 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.131s, data_time: 0.022s, total_loss: 6.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.393e-03, size: 480, ETA: 1:21:32
2025-07-31 14:40:55.253 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.6, lr: 1.390e-03, size: 416, ETA: 1:21:29
2025-07-31 14:40:58.222 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 1.387e-03, size: 288, ETA: 1:21:27
2025-07-31 14:40:59.523 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:40:59.569 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch323
2025-07-31 14:41:02.484 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.023s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.382e-03, size: 256, ETA: 1:21:23
2025-07-31 14:41:05.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.045s, total_loss: 6.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 1.378e-03, size: 512, ETA: 1:21:20
2025-07-31 14:41:08.244 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.056s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.9, lr: 1.375e-03, size: 256, ETA: 1:21:17
2025-07-31 14:41:11.183 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 1.372e-03, size: 320, ETA: 1:21:14
2025-07-31 14:41:14.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.050s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 1.368e-03, size: 576, ETA: 1:21:12
2025-07-31 14:41:17.136 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.150s, data_time: 0.064s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.365e-03, size: 512, ETA: 1:21:09
2025-07-31 14:41:18.528 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:41:18.566 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch324
2025-07-31 14:41:21.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.058s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 1.360e-03, size: 288, ETA: 1:21:06
2025-07-31 14:41:24.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.149s, data_time: 0.068s, total_loss: 6.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.357e-03, size: 288, ETA: 1:21:03
2025-07-31 14:41:27.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.143s, data_time: 0.061s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.353e-03, size: 480, ETA: 1:21:00
2025-07-31 14:41:30.476 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.152s, data_time: 0.067s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 1.350e-03, size: 480, ETA: 1:20:58
2025-07-31 14:41:33.495 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.025s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 1.346e-03, size: 384, ETA: 1:20:55
2025-07-31 14:41:36.442 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.343e-03, size: 576, ETA: 1:20:53
2025-07-31 14:41:37.769 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:41:37.810 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch325
2025-07-31 14:41:40.759 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.145s, data_time: 0.011s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 1.338e-03, size: 352, ETA: 1:20:49
2025-07-31 14:41:43.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.146s, data_time: 0.007s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.335e-03, size: 352, ETA: 1:20:46
2025-07-31 14:41:46.727 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.147s, data_time: 0.031s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.332e-03, size: 320, ETA: 1:20:44
2025-07-31 14:41:49.645 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.025s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 1.328e-03, size: 416, ETA: 1:20:41
2025-07-31 14:41:52.702 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.151s, data_time: 0.062s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 1.325e-03, size: 576, ETA: 1:20:39
2025-07-31 14:41:55.687 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.148s, data_time: 0.061s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 1.322e-03, size: 320, ETA: 1:20:36
2025-07-31 14:41:57.105 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:42:03.775 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:42:06.264 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:42:07.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5934
2025-07-31 14:42:08.271 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5247
2025-07-31 14:42:08.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3496
2025-07-31 14:42:08.363 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4892
2025-07-31 14:42:08.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:42:08.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:42:08.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.593
2025-07-31 14:42:08.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.525
2025-07-31 14:42:08.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.350
2025-07-31 14:42:08.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.489
2025-07-31 14:42:08.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:42:08.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:42:08.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:42:08.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:42:08.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:42:08.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:42:08.366 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:42:08.366 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:42:08.366 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:42:10.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:42:12.332 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:42:14.255 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:42:16.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:42:18.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:42:20.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:42:21.942 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:42:23.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:42:25.793 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:42:25.794 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 14:42:25.794 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-07-31 14:42:25.794 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:42:25.819 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 1.00 ms, Average inference time: 2.45 ms

2025-07-31 14:42:25.820 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:42:25.848 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:42:25.881 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch326
2025-07-31 14:42:28.484 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.122s, data_time: 0.025s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 1.317e-03, size: 576, ETA: 1:20:32
2025-07-31 14:42:31.305 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.018s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 1.314e-03, size: 288, ETA: 1:20:29
2025-07-31 14:42:34.239 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.046s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 1.310e-03, size: 448, ETA: 1:20:27
2025-07-31 14:42:37.249 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.047s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.307e-03, size: 544, ETA: 1:20:24
2025-07-31 14:42:40.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.054s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.304e-03, size: 448, ETA: 1:20:21
2025-07-31 14:42:43.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.023s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 1.301e-03, size: 352, ETA: 1:20:19
2025-07-31 14:42:44.309 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:42:44.442 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch327
2025-07-31 14:42:47.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.035s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 1.296e-03, size: 512, ETA: 1:20:15
2025-07-31 14:42:50.404 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.130s, data_time: 0.007s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.293e-03, size: 480, ETA: 1:20:12
2025-07-31 14:42:53.267 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.011s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 1.289e-03, size: 256, ETA: 1:20:09
2025-07-31 14:42:56.193 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.054s, total_loss: 4.6, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 1.286e-03, size: 448, ETA: 1:20:06
2025-07-31 14:42:59.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.146s, data_time: 0.059s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.283e-03, size: 256, ETA: 1:20:04
2025-07-31 14:43:02.039 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.137s, data_time: 0.044s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.280e-03, size: 544, ETA: 1:20:01
2025-07-31 14:43:03.348 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:43:03.409 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch328
2025-07-31 14:43:06.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.010s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.275e-03, size: 384, ETA: 1:19:57
2025-07-31 14:43:09.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.006s, total_loss: 9.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 5.2, cls_loss: 0.9, lr: 1.272e-03, size: 544, ETA: 1:19:54
2025-07-31 14:43:12.241 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.269e-03, size: 480, ETA: 1:19:51
2025-07-31 14:43:15.198 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.011s, total_loss: 6.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.266e-03, size: 352, ETA: 1:19:49
2025-07-31 14:43:18.143 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.146s, data_time: 0.056s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 1.262e-03, size: 256, ETA: 1:19:46
2025-07-31 14:43:21.103 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.146s, data_time: 0.046s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.259e-03, size: 576, ETA: 1:19:43
2025-07-31 14:43:22.532 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:43:22.635 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch329
2025-07-31 14:43:25.501 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.255e-03, size: 544, ETA: 1:19:39
2025-07-31 14:43:28.523 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 1.251e-03, size: 352, ETA: 1:19:37
2025-07-31 14:43:31.421 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.130s, data_time: 0.009s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 1.248e-03, size: 512, ETA: 1:19:34
2025-07-31 14:43:34.336 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.026s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.245e-03, size: 352, ETA: 1:19:31
2025-07-31 14:43:37.486 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.155s, data_time: 0.066s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 1.242e-03, size: 576, ETA: 1:19:29
2025-07-31 14:43:40.339 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.052s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.239e-03, size: 448, ETA: 1:19:26
2025-07-31 14:43:41.552 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:43:41.645 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch330
2025-07-31 14:43:44.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.034s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 1.234e-03, size: 352, ETA: 1:19:22
2025-07-31 14:43:47.697 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.231e-03, size: 448, ETA: 1:19:19
2025-07-31 14:43:50.625 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.137s, data_time: 0.019s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.228e-03, size: 416, ETA: 1:19:17
2025-07-31 14:43:53.587 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.035s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 1.225e-03, size: 480, ETA: 1:19:14
2025-07-31 14:43:56.440 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.049s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.222e-03, size: 256, ETA: 1:19:11
2025-07-31 14:43:59.443 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.149s, data_time: 0.067s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 1.219e-03, size: 480, ETA: 1:19:09
2025-07-31 14:44:00.787 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:44:07.339 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:44:08.680 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:44:09.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6017
2025-07-31 14:44:09.638 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5255
2025-07-31 14:44:09.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3355
2025-07-31 14:44:09.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4876
2025-07-31 14:44:09.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:44:09.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:44:09.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.602
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.525
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.336
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.488
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:44:09.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:44:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:44:11.824 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:44:12.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:44:13.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:44:14.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:44:16.005 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:44:17.049 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:44:18.081 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:44:19.121 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:44:19.121 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 14:44:19.121 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-07-31 14:44:19.121 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:44:19.131 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 1.02 ms, Average inference time: 2.47 ms

2025-07-31 14:44:19.132 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:44:19.177 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:44:19.226 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch331
2025-07-31 14:44:21.750 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.125s, data_time: 0.038s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.214e-03, size: 544, ETA: 1:19:05
2025-07-31 14:44:24.702 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.146s, data_time: 0.027s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 1.211e-03, size: 320, ETA: 1:19:02
2025-07-31 14:44:27.664 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.146s, data_time: 0.011s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.208e-03, size: 544, ETA: 1:19:00
2025-07-31 14:44:30.627 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.145s, data_time: 0.018s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.205e-03, size: 480, ETA: 1:18:57
2025-07-31 14:44:33.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.009s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 1.202e-03, size: 384, ETA: 1:18:54
2025-07-31 14:44:36.457 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.149s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.199e-03, size: 512, ETA: 1:18:52
2025-07-31 14:44:37.740 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:44:37.843 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch332
2025-07-31 14:44:40.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.142s, data_time: 0.005s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.194e-03, size: 544, ETA: 1:18:48
2025-07-31 14:44:43.764 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 1.191e-03, size: 480, ETA: 1:18:45
2025-07-31 14:44:46.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.188e-03, size: 480, ETA: 1:18:42
2025-07-31 14:44:49.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.185e-03, size: 352, ETA: 1:18:40
2025-07-31 14:44:52.491 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.182e-03, size: 384, ETA: 1:18:37
2025-07-31 14:44:55.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.006s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.179e-03, size: 544, ETA: 1:18:34
2025-07-31 14:44:56.652 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:44:56.713 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch333
2025-07-31 14:44:59.716 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.146s, data_time: 0.027s, total_loss: 5.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 1.175e-03, size: 416, ETA: 1:18:30
2025-07-31 14:45:02.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 1.172e-03, size: 256, ETA: 1:18:28
2025-07-31 14:45:05.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.031s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 1.169e-03, size: 384, ETA: 1:18:25
2025-07-31 14:45:08.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.148s, data_time: 0.010s, total_loss: 5.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 1.166e-03, size: 448, ETA: 1:18:22
2025-07-31 14:45:11.414 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.019s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.163e-03, size: 480, ETA: 1:18:20
2025-07-31 14:45:14.397 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.017s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 1.160e-03, size: 544, ETA: 1:18:17
2025-07-31 14:45:15.656 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:45:15.753 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch334
2025-07-31 14:45:18.740 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.156e-03, size: 352, ETA: 1:18:13
2025-07-31 14:45:21.654 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.041s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.153e-03, size: 480, ETA: 1:18:10
2025-07-31 14:45:24.732 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.011s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.150e-03, size: 480, ETA: 1:18:08
2025-07-31 14:45:27.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.147e-03, size: 352, ETA: 1:18:05
2025-07-31 14:45:30.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.144e-03, size: 448, ETA: 1:18:02
2025-07-31 14:45:33.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.141e-03, size: 512, ETA: 1:18:00
2025-07-31 14:45:34.867 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:45:34.927 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch335
2025-07-31 14:45:37.938 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.148s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 1.137e-03, size: 384, ETA: 1:17:56
2025-07-31 14:45:40.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.134e-03, size: 544, ETA: 1:17:53
2025-07-31 14:45:43.760 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.131e-03, size: 256, ETA: 1:17:50
2025-07-31 14:45:46.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.140s, data_time: 0.019s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.128e-03, size: 320, ETA: 1:17:48
2025-07-31 14:45:49.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.009s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 1.125e-03, size: 544, ETA: 1:17:45
2025-07-31 14:45:52.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.148s, data_time: 0.022s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.122e-03, size: 320, ETA: 1:17:43
2025-07-31 14:45:54.029 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:46:00.699 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:46:03.179 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:46:04.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5945
2025-07-31 14:46:05.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5445
2025-07-31 14:46:05.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3521
2025-07-31 14:46:05.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4970
2025-07-31 14:46:05.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:46:05.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:46:05.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.594
2025-07-31 14:46:05.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.545
2025-07-31 14:46:05.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.352
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.497
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:46:05.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:46:07.444 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:46:09.601 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:46:11.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:46:13.892 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:46:16.034 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:46:18.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:46:20.318 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:46:22.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:46:24.632 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:46:24.633 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 14:46:24.633 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-31 14:46:24.633 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:46:24.662 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 1.01 ms, Average inference time: 2.46 ms

2025-07-31 14:46:24.664 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:46:24.695 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:46:24.730 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch336
2025-07-31 14:46:27.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.121s, data_time: 0.033s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.118e-03, size: 544, ETA: 1:17:38
2025-07-31 14:46:30.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.039s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 1.115e-03, size: 544, ETA: 1:17:36
2025-07-31 14:46:33.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.015s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.112e-03, size: 352, ETA: 1:17:33
2025-07-31 14:46:36.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.109e-03, size: 544, ETA: 1:17:30
2025-07-31 14:46:39.051 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.106e-03, size: 544, ETA: 1:17:27
2025-07-31 14:46:42.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.103e-03, size: 544, ETA: 1:17:25
2025-07-31 14:46:43.292 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:46:43.504 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch337
2025-07-31 14:46:46.408 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.011s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.099e-03, size: 480, ETA: 1:17:21
2025-07-31 14:46:49.299 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.142s, data_time: 0.038s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.096e-03, size: 288, ETA: 1:17:18
2025-07-31 14:46:52.267 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.146s, data_time: 0.005s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.094e-03, size: 288, ETA: 1:17:15
2025-07-31 14:46:55.247 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.146s, data_time: 0.010s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 1.091e-03, size: 480, ETA: 1:17:13
2025-07-31 14:46:58.226 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.146s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 1.088e-03, size: 256, ETA: 1:17:10
2025-07-31 14:47:01.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 1.085e-03, size: 288, ETA: 1:17:08
2025-07-31 14:47:02.371 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:47:02.485 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch338
2025-07-31 14:47:05.414 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.035s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.081e-03, size: 352, ETA: 1:17:04
2025-07-31 14:47:08.387 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.034s, total_loss: 5.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.7, lr: 1.078e-03, size: 256, ETA: 1:17:01
2025-07-31 14:47:11.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.148s, data_time: 0.057s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 1.075e-03, size: 384, ETA: 1:16:59
2025-07-31 14:47:14.423 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.053s, total_loss: 5.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 1.073e-03, size: 448, ETA: 1:16:56
2025-07-31 14:47:17.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.021s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.070e-03, size: 416, ETA: 1:16:53
2025-07-31 14:47:20.355 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.014s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 1.067e-03, size: 448, ETA: 1:16:51
2025-07-31 14:47:21.678 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:47:21.720 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch339
2025-07-31 14:47:24.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.145s, data_time: 0.005s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.063e-03, size: 320, ETA: 1:16:47
2025-07-31 14:47:27.606 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.146s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 1.060e-03, size: 576, ETA: 1:16:44
2025-07-31 14:47:30.682 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.153s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 1.058e-03, size: 576, ETA: 1:16:42
2025-07-31 14:47:33.735 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.151s, data_time: 0.020s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.055e-03, size: 480, ETA: 1:16:39
2025-07-31 14:47:36.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.144s, data_time: 0.035s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.052e-03, size: 576, ETA: 1:16:37
2025-07-31 14:47:39.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.150s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 1.049e-03, size: 480, ETA: 1:16:34
2025-07-31 14:47:41.044 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:47:41.103 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch340
2025-07-31 14:47:44.098 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.148s, data_time: 0.063s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 1.045e-03, size: 480, ETA: 1:16:30
2025-07-31 14:47:47.030 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.045s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.043e-03, size: 384, ETA: 1:16:28
2025-07-31 14:47:49.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.140s, data_time: 0.009s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.040e-03, size: 576, ETA: 1:16:25
2025-07-31 14:47:52.888 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.140s, data_time: 0.007s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.037e-03, size: 512, ETA: 1:16:22
2025-07-31 14:47:55.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.013s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.035e-03, size: 512, ETA: 1:16:20
2025-07-31 14:47:58.785 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.009s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.032e-03, size: 544, ETA: 1:16:17
2025-07-31 14:48:00.034 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:48:06.623 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:48:08.220 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:48:09.147 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5964
2025-07-31 14:48:09.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5334
2025-07-31 14:48:09.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3704
2025-07-31 14:48:09.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5001
2025-07-31 14:48:09.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:48:09.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:48:09.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.596
2025-07-31 14:48:09.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.533
2025-07-31 14:48:09.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.370
2025-07-31 14:48:09.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.500
2025-07-31 14:48:09.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:48:09.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:48:09.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:48:09.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:48:09.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:48:09.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:48:09.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:48:09.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:48:09.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:48:10.611 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:48:11.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:48:12.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:48:14.181 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:48:15.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:48:16.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:48:17.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:48:19.049 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:48:20.305 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:48:20.306 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 14:48:20.306 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-31 14:48:20.306 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:48:20.313 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.99 ms, Average inference time: 2.41 ms

2025-07-31 14:48:20.315 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:48:20.354 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:48:20.397 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch341
2025-07-31 14:48:23.012 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.039s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.028e-03, size: 384, ETA: 1:16:13
2025-07-31 14:48:25.951 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.029s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 1.025e-03, size: 448, ETA: 1:16:10
2025-07-31 14:48:28.987 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.023e-03, size: 448, ETA: 1:16:07
2025-07-31 14:48:32.047 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.3, lr: 1.020e-03, size: 416, ETA: 1:16:05
2025-07-31 14:48:34.916 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.017e-03, size: 352, ETA: 1:16:02
2025-07-31 14:48:37.938 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.148s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.015e-03, size: 384, ETA: 1:16:00
2025-07-31 14:48:39.224 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:48:39.368 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch342
2025-07-31 14:48:42.223 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.011s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 1.011e-03, size: 352, ETA: 1:15:56
2025-07-31 14:48:45.211 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.016s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.008e-03, size: 448, ETA: 1:15:53
2025-07-31 14:48:48.269 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 5.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 1.006e-03, size: 256, ETA: 1:15:50
2025-07-31 14:48:51.305 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.003e-03, size: 288, ETA: 1:15:48
2025-07-31 14:48:54.197 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.008s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.000e-03, size: 320, ETA: 1:15:45
2025-07-31 14:48:57.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.977e-04, size: 512, ETA: 1:15:42
2025-07-31 14:48:58.400 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:48:58.451 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch343
2025-07-31 14:49:01.406 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.128s, data_time: 0.005s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.939e-04, size: 352, ETA: 1:15:38
2025-07-31 14:49:04.328 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.913e-04, size: 544, ETA: 1:15:35
2025-07-31 14:49:07.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.014s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.887e-04, size: 384, ETA: 1:15:32
2025-07-31 14:49:10.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.005s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 9.861e-04, size: 256, ETA: 1:15:30
2025-07-31 14:49:13.153 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.021s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.835e-04, size: 384, ETA: 1:15:27
2025-07-31 14:49:16.145 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.810e-04, size: 576, ETA: 1:15:24
2025-07-31 14:49:17.364 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:49:17.524 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch344
2025-07-31 14:49:20.338 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.5Gb, iter_time: 0.137s, data_time: 0.021s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.772e-04, size: 480, ETA: 1:15:20
2025-07-31 14:49:23.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.146s, data_time: 0.034s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.747e-04, size: 480, ETA: 1:15:18
2025-07-31 14:49:26.330 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.021s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 9.721e-04, size: 256, ETA: 1:15:15
2025-07-31 14:49:29.377 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.150s, data_time: 0.065s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.696e-04, size: 448, ETA: 1:15:12
2025-07-31 14:49:32.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.037s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 9.671e-04, size: 256, ETA: 1:15:10
2025-07-31 14:49:35.272 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.147s, data_time: 0.043s, total_loss: 7.4, iou_loss: 3.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.645e-04, size: 256, ETA: 1:15:07
2025-07-31 14:49:36.571 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:49:36.631 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch345
2025-07-31 14:49:39.536 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.014s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.609e-04, size: 416, ETA: 1:15:03
2025-07-31 14:49:42.624 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.037s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.584e-04, size: 448, ETA: 1:15:00
2025-07-31 14:49:45.573 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.559e-04, size: 256, ETA: 1:14:58
2025-07-31 14:49:48.550 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.010s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.534e-04, size: 384, ETA: 1:14:55
2025-07-31 14:49:51.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.142s, data_time: 0.058s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.509e-04, size: 544, ETA: 1:14:52
2025-07-31 14:49:54.443 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.012s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.484e-04, size: 448, ETA: 1:14:49
2025-07-31 14:49:55.670 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:50:02.288 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:50:04.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:50:05.576 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5967
2025-07-31 14:50:05.842 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5500
2025-07-31 14:50:05.891 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3574
2025-07-31 14:50:05.892 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5014
2025-07-31 14:50:05.892 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:50:05.892 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.597
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.550
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.357
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.501
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:50:05.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:50:05.894 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:50:07.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:50:09.357 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:50:10.993 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:50:12.588 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:50:14.160 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:50:15.791 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:50:17.407 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:50:18.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:50:20.553 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:50:20.553 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-31 14:50:20.553 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-31 14:50:20.554 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:50:20.578 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 1.00 ms, Average inference time: 2.44 ms

2025-07-31 14:50:20.582 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:50:20.609 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:50:20.642 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch346
2025-07-31 14:50:23.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.115s, data_time: 0.010s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.448e-04, size: 512, ETA: 1:14:45
2025-07-31 14:50:26.185 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.011s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.9, lr: 9.423e-04, size: 320, ETA: 1:14:42
2025-07-31 14:50:29.110 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.004s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.398e-04, size: 288, ETA: 1:14:40
2025-07-31 14:50:32.082 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.051s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 9.374e-04, size: 448, ETA: 1:14:37
2025-07-31 14:50:35.028 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.047s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 9.349e-04, size: 416, ETA: 1:14:34
2025-07-31 14:50:38.083 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.140s, data_time: 0.023s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.325e-04, size: 352, ETA: 1:14:32
2025-07-31 14:50:39.242 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:50:39.432 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch347
2025-07-31 14:50:42.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.040s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.290e-04, size: 576, ETA: 1:14:27
2025-07-31 14:50:45.347 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.128s, data_time: 0.020s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 9.265e-04, size: 384, ETA: 1:14:25
2025-07-31 14:50:48.302 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.124s, data_time: 0.007s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.241e-04, size: 544, ETA: 1:14:22
2025-07-31 14:50:51.388 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.217e-04, size: 384, ETA: 1:14:19
2025-07-31 14:50:54.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.193e-04, size: 384, ETA: 1:14:16
2025-07-31 14:50:57.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.169e-04, size: 480, ETA: 1:14:13
2025-07-31 14:50:58.459 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:50:58.560 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch348
2025-07-31 14:51:01.525 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.134e-04, size: 448, ETA: 1:14:09
2025-07-31 14:51:04.531 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.142s, data_time: 0.004s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.110e-04, size: 576, ETA: 1:14:07
2025-07-31 14:51:07.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.031s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.086e-04, size: 576, ETA: 1:14:04
2025-07-31 14:51:10.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.017s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.063e-04, size: 480, ETA: 1:14:01
2025-07-31 14:51:13.248 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.035s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 9.039e-04, size: 448, ETA: 1:13:58
2025-07-31 14:51:16.196 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.027s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.015e-04, size: 384, ETA: 1:13:56
2025-07-31 14:51:17.426 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:51:17.528 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch349
2025-07-31 14:51:20.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 8.981e-04, size: 576, ETA: 1:13:52
2025-07-31 14:51:23.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.142s, data_time: 0.023s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.958e-04, size: 320, ETA: 1:13:49
2025-07-31 14:51:26.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.149s, data_time: 0.022s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.934e-04, size: 416, ETA: 1:13:46
2025-07-31 14:51:29.273 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.008s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 8.911e-04, size: 288, ETA: 1:13:44
2025-07-31 14:51:32.222 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.007s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 8.888e-04, size: 384, ETA: 1:13:41
2025-07-31 14:51:35.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.143s, data_time: 0.018s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 8.865e-04, size: 448, ETA: 1:13:39
2025-07-31 14:51:36.507 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:51:36.552 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch350
2025-07-31 14:51:39.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.054s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.8, lr: 8.831e-04, size: 352, ETA: 1:13:35
2025-07-31 14:51:42.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.146s, data_time: 0.058s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 8.808e-04, size: 512, ETA: 1:13:32
2025-07-31 14:51:45.424 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.140s, data_time: 0.053s, total_loss: 4.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 8.785e-04, size: 576, ETA: 1:13:30
2025-07-31 14:51:48.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.048s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 8.762e-04, size: 352, ETA: 1:13:27
2025-07-31 14:51:51.427 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.151s, data_time: 0.063s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.740e-04, size: 352, ETA: 1:13:24
2025-07-31 14:51:54.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.058s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 8.717e-04, size: 512, ETA: 1:13:22
2025-07-31 14:51:55.608 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:52:02.056 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:52:03.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:52:04.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6102
2025-07-31 14:52:05.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5401
2025-07-31 14:52:05.221 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3579
2025-07-31 14:52:05.222 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5028
2025-07-31 14:52:05.222 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:52:05.222 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:52:05.222 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.610
2025-07-31 14:52:05.222 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.540
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.358
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.503
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:52:05.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:52:05.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:52:06.663 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:52:08.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:52:09.359 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:52:10.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:52:12.104 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:52:13.496 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:52:14.841 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:52:16.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:52:17.560 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:52:17.560 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 14:52:17.560 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-31 14:52:17.560 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:52:17.570 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 1.03 ms, Average inference time: 2.51 ms

2025-07-31 14:52:17.571 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:52:17.592 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:52:17.624 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch351
2025-07-31 14:52:20.281 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.019s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.684e-04, size: 416, ETA: 1:13:18
2025-07-31 14:52:23.099 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.007s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 8.661e-04, size: 384, ETA: 1:13:15
2025-07-31 14:52:26.047 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.056s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 8.639e-04, size: 576, ETA: 1:13:12
2025-07-31 14:52:28.936 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.142s, data_time: 0.048s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 8.616e-04, size: 384, ETA: 1:13:10
2025-07-31 14:52:31.955 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.140s, data_time: 0.008s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 8.594e-04, size: 416, ETA: 1:13:07
2025-07-31 14:52:34.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 8.572e-04, size: 576, ETA: 1:13:04
2025-07-31 14:52:36.181 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:52:36.315 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch352
2025-07-31 14:52:39.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.008s, total_loss: 6.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 8.539e-04, size: 256, ETA: 1:13:00
2025-07-31 14:52:42.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.033s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.517e-04, size: 512, ETA: 1:12:58
2025-07-31 14:52:44.929 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.039s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.9, lr: 8.495e-04, size: 288, ETA: 1:12:55
2025-07-31 14:52:47.881 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.021s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.473e-04, size: 256, ETA: 1:12:52
2025-07-31 14:52:50.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.035s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 8.451e-04, size: 352, ETA: 1:12:49
2025-07-31 14:52:53.764 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.143s, data_time: 0.028s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 8.429e-04, size: 256, ETA: 1:12:47
2025-07-31 14:52:55.024 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:52:55.109 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch353
2025-07-31 14:52:58.058 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 8.398e-04, size: 576, ETA: 1:12:43
2025-07-31 14:53:01.097 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.149s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.376e-04, size: 352, ETA: 1:12:40
2025-07-31 14:53:04.146 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.151s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.354e-04, size: 512, ETA: 1:12:38
2025-07-31 14:53:07.059 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.004s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 8.333e-04, size: 256, ETA: 1:12:35
2025-07-31 14:53:10.018 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.145s, data_time: 0.023s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.3, lr: 8.311e-04, size: 320, ETA: 1:12:33
2025-07-31 14:53:12.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.145s, data_time: 0.061s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.290e-04, size: 256, ETA: 1:12:30
2025-07-31 14:53:14.444 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:53:14.481 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch354
2025-07-31 14:53:17.443 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.058s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 8.259e-04, size: 448, ETA: 1:12:26
2025-07-31 14:53:20.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.147s, data_time: 0.005s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.238e-04, size: 416, ETA: 1:12:24
2025-07-31 14:53:23.550 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.216e-04, size: 576, ETA: 1:12:21
2025-07-31 14:53:26.469 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.195e-04, size: 288, ETA: 1:12:18
2025-07-31 14:53:29.386 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 8.174e-04, size: 512, ETA: 1:12:16
2025-07-31 14:53:32.311 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.153e-04, size: 320, ETA: 1:12:13
2025-07-31 14:53:33.653 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:53:33.777 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch355
2025-07-31 14:53:36.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.010s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 8.123e-04, size: 288, ETA: 1:12:09
2025-07-31 14:53:39.557 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.128s, data_time: 0.011s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.102e-04, size: 448, ETA: 1:12:06
2025-07-31 14:53:42.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.144s, data_time: 0.054s, total_loss: 7.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 8.081e-04, size: 256, ETA: 1:12:03
2025-07-31 14:53:45.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.049s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.060e-04, size: 320, ETA: 1:12:01
2025-07-31 14:53:48.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.153s, data_time: 0.070s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.040e-04, size: 544, ETA: 1:11:58
2025-07-31 14:53:51.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.144s, data_time: 0.043s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.019e-04, size: 448, ETA: 1:11:56
2025-07-31 14:53:52.837 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:53:59.326 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:54:01.531 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:54:03.072 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6104
2025-07-31 14:54:03.363 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5639
2025-07-31 14:54:03.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3669
2025-07-31 14:54:03.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5137
2025-07-31 14:54:03.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:54:03.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:54:03.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.610
2025-07-31 14:54:03.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-07-31 14:54:03.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.367
2025-07-31 14:54:03.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.514
2025-07-31 14:54:03.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:54:03.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:54:03.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:54:03.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:54:03.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:54:03.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:54:03.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:54:03.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:54:03.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:54:05.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:54:07.063 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:54:08.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:54:10.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:54:12.408 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:54:14.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:54:15.864 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:54:17.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:54:19.384 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:54:19.384 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 14:54:19.384 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-31 14:54:19.384 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:54:19.412 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 1.02 ms, Average inference time: 2.46 ms

2025-07-31 14:54:19.413 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:54:19.448 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:54:19.481 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch356
2025-07-31 14:54:22.075 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.128s, data_time: 0.041s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.989e-04, size: 448, ETA: 1:11:52
2025-07-31 14:54:25.047 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.148s, data_time: 0.057s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 7.969e-04, size: 256, ETA: 1:11:49
2025-07-31 14:54:28.026 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.146s, data_time: 0.058s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.949e-04, size: 512, ETA: 1:11:46
2025-07-31 14:54:30.974 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.018s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 7.928e-04, size: 288, ETA: 1:11:44
2025-07-31 14:54:33.857 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.025s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 7.908e-04, size: 320, ETA: 1:11:41
2025-07-31 14:54:36.900 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.151s, data_time: 0.056s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.888e-04, size: 288, ETA: 1:11:38
2025-07-31 14:54:38.143 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:54:38.194 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch357
2025-07-31 14:54:41.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 7.859e-04, size: 384, ETA: 1:11:34
2025-07-31 14:54:44.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.005s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.839e-04, size: 448, ETA: 1:11:32
2025-07-31 14:54:46.999 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.147s, data_time: 0.012s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 7.819e-04, size: 384, ETA: 1:11:29
2025-07-31 14:54:49.969 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.799e-04, size: 544, ETA: 1:11:26
2025-07-31 14:54:52.962 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.146s, data_time: 0.004s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.779e-04, size: 288, ETA: 1:11:24
2025-07-31 14:54:55.941 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 7.760e-04, size: 576, ETA: 1:11:21
2025-07-31 14:54:57.251 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:54:57.301 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch358
2025-07-31 14:55:00.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.008s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 7.731e-04, size: 256, ETA: 1:11:17
2025-07-31 14:55:03.066 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.132s, data_time: 0.012s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 7.712e-04, size: 352, ETA: 1:11:15
2025-07-31 14:55:05.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.034s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 7.692e-04, size: 384, ETA: 1:11:12
2025-07-31 14:55:09.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.015s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.673e-04, size: 352, ETA: 1:11:09
2025-07-31 14:55:11.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.653e-04, size: 512, ETA: 1:11:06
2025-07-31 14:55:14.963 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 7.634e-04, size: 448, ETA: 1:11:04
2025-07-31 14:55:16.209 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:55:16.256 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch359
2025-07-31 14:55:19.209 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.606e-04, size: 416, ETA: 1:10:59
2025-07-31 14:55:22.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.144s, data_time: 0.015s, total_loss: 8.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 7.587e-04, size: 448, ETA: 1:10:57
2025-07-31 14:55:25.103 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.568e-04, size: 320, ETA: 1:10:54
2025-07-31 14:55:28.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.549e-04, size: 480, ETA: 1:10:52
2025-07-31 14:55:31.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.2, lr: 7.530e-04, size: 544, ETA: 1:10:49
2025-07-31 14:55:33.983 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.021s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.512e-04, size: 448, ETA: 1:10:46
2025-07-31 14:55:35.313 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:55:35.461 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch360
2025-07-31 14:55:38.356 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.041s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.6, lr: 7.484e-04, size: 576, ETA: 1:10:42
2025-07-31 14:55:41.383 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.008s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.466e-04, size: 320, ETA: 1:10:39
2025-07-31 14:55:44.308 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.447e-04, size: 544, ETA: 1:10:37
2025-07-31 14:55:47.318 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.429e-04, size: 576, ETA: 1:10:34
2025-07-31 14:55:50.294 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.410e-04, size: 256, ETA: 1:10:31
2025-07-31 14:55:53.152 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.018s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.392e-04, size: 448, ETA: 1:10:28
2025-07-31 14:55:54.507 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:56:00.980 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:56:02.815 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:56:03.999 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5885
2025-07-31 14:56:04.181 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5435
2025-07-31 14:56:04.290 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2985
2025-07-31 14:56:04.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4768
2025-07-31 14:56:04.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:56:04.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:56:04.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.588
2025-07-31 14:56:04.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.544
2025-07-31 14:56:04.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.299
2025-07-31 14:56:04.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.477
2025-07-31 14:56:04.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:56:04.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:56:04.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:56:04.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:56:04.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:56:04.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:56:04.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:56:04.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:56:04.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:56:05.680 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:56:07.020 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:56:08.526 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:56:10.079 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:56:11.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:56:13.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:56:14.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:56:16.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:56:17.657 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:56:17.658 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-31 14:56:17.658 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-31 14:56:17.658 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:56:17.668 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 1.01 ms, Average inference time: 2.48 ms

2025-07-31 14:56:17.669 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:56:17.691 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:56:17.723 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch361
2025-07-31 14:56:20.264 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.124s, data_time: 0.029s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 1.0, lr: 7.365e-04, size: 288, ETA: 1:10:24
2025-07-31 14:56:23.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.144s, data_time: 0.008s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.347e-04, size: 576, ETA: 1:10:22
2025-07-31 14:56:26.451 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.329e-04, size: 352, ETA: 1:10:19
2025-07-31 14:56:29.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.015s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.311e-04, size: 352, ETA: 1:10:16
2025-07-31 14:56:32.415 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.152s, data_time: 0.060s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 7.293e-04, size: 544, ETA: 1:10:14
2025-07-31 14:56:35.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.035s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.275e-04, size: 288, ETA: 1:10:11
2025-07-31 14:56:36.638 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:56:36.697 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch362
2025-07-31 14:56:39.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.148s, data_time: 0.058s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.249e-04, size: 512, ETA: 1:10:07
2025-07-31 14:56:42.586 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.231e-04, size: 512, ETA: 1:10:05
2025-07-31 14:56:45.589 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.005s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 7.213e-04, size: 256, ETA: 1:10:02
2025-07-31 14:56:48.616 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 7.196e-04, size: 352, ETA: 1:09:59
2025-07-31 14:56:51.653 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.142s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 7.178e-04, size: 416, ETA: 1:09:57
2025-07-31 14:56:54.520 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.015s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 7.161e-04, size: 320, ETA: 1:09:54
2025-07-31 14:56:55.818 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:56:55.862 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch363
2025-07-31 14:56:58.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.148s, data_time: 0.006s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.136e-04, size: 288, ETA: 1:09:50
2025-07-31 14:57:01.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.150s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 7.118e-04, size: 352, ETA: 1:09:47
2025-07-31 14:57:04.868 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.143s, data_time: 0.030s, total_loss: 6.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.101e-04, size: 256, ETA: 1:09:45
2025-07-31 14:57:07.791 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.142s, data_time: 0.011s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.084e-04, size: 544, ETA: 1:09:42
2025-07-31 14:57:10.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.146s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.067e-04, size: 416, ETA: 1:09:39
2025-07-31 14:57:13.855 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.050e-04, size: 512, ETA: 1:09:37
2025-07-31 14:57:15.154 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:57:15.290 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch364
2025-07-31 14:57:18.318 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.145s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 7.025e-04, size: 576, ETA: 1:09:33
2025-07-31 14:57:21.336 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.145s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.008e-04, size: 480, ETA: 1:09:30
2025-07-31 14:57:24.360 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.142s, data_time: 0.021s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.991e-04, size: 512, ETA: 1:09:28
2025-07-31 14:57:27.396 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.145s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 6.975e-04, size: 352, ETA: 1:09:25
2025-07-31 14:57:30.545 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.150s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 6.958e-04, size: 448, ETA: 1:09:23
2025-07-31 14:57:33.474 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.143s, data_time: 0.031s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 6.941e-04, size: 512, ETA: 1:09:20
2025-07-31 14:57:34.797 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:57:34.835 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch365
2025-07-31 14:57:37.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.145s, data_time: 0.048s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 6.917e-04, size: 480, ETA: 1:09:16
2025-07-31 14:57:40.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.150s, data_time: 0.006s, total_loss: 7.5, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.901e-04, size: 320, ETA: 1:09:14
2025-07-31 14:57:43.760 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.145s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.884e-04, size: 544, ETA: 1:09:11
2025-07-31 14:57:46.694 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.145s, data_time: 0.016s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.868e-04, size: 544, ETA: 1:09:08
2025-07-31 14:57:49.687 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.146s, data_time: 0.040s, total_loss: 4.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.7, lr: 6.852e-04, size: 480, ETA: 1:09:06
2025-07-31 14:57:52.691 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.147s, data_time: 0.004s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.836e-04, size: 416, ETA: 1:09:03
2025-07-31 14:57:53.952 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:58:00.392 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 14:58:02.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 14:58:03.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6086
2025-07-31 14:58:04.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5607
2025-07-31 14:58:04.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3647
2025-07-31 14:58:04.230 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5113
2025-07-31 14:58:04.230 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.609
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.561
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.365
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.511
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 14:58:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 14:58:04.232 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 14:58:04.232 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 14:58:04.232 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 14:58:05.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 14:58:07.358 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 14:58:08.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 14:58:10.561 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 14:58:12.090 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 14:58:13.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 14:58:15.298 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 14:58:16.859 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 14:58:18.447 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 14:58:18.448 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 14:58:18.448 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-31 14:58:18.448 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 14:58:18.477 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 1.02 ms, Average inference time: 2.49 ms

2025-07-31 14:58:18.478 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:58:18.510 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:58:18.546 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch366
2025-07-31 14:58:21.149 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.043s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.812e-04, size: 576, ETA: 1:08:59
2025-07-31 14:58:24.064 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.142s, data_time: 0.049s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.796e-04, size: 352, ETA: 1:08:56
2025-07-31 14:58:27.105 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.147s, data_time: 0.051s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 1.1, lr: 6.781e-04, size: 448, ETA: 1:08:54
2025-07-31 14:58:30.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.019s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 6.765e-04, size: 448, ETA: 1:08:51
2025-07-31 14:58:33.137 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.146s, data_time: 0.058s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.749e-04, size: 256, ETA: 1:08:48
2025-07-31 14:58:36.186 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.025s, total_loss: 4.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 6.733e-04, size: 480, ETA: 1:08:46
2025-07-31 14:58:37.491 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:58:37.543 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch367
2025-07-31 14:58:40.635 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.144s, data_time: 0.013s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 6.711e-04, size: 448, ETA: 1:08:42
2025-07-31 14:58:43.639 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.143s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.695e-04, size: 416, ETA: 1:08:39
2025-07-31 14:58:46.707 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.151s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 6.680e-04, size: 576, ETA: 1:08:37
2025-07-31 14:58:49.595 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.142s, data_time: 0.019s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 6.664e-04, size: 320, ETA: 1:08:34
2025-07-31 14:58:52.648 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.151s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.649e-04, size: 320, ETA: 1:08:31
2025-07-31 14:58:55.792 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.6Gb, iter_time: 0.155s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.634e-04, size: 256, ETA: 1:08:29
2025-07-31 14:58:57.083 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:58:57.191 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch368
2025-07-31 14:59:00.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 6.612e-04, size: 384, ETA: 1:08:25
2025-07-31 14:59:03.105 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.037s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 6.596e-04, size: 544, ETA: 1:08:22
2025-07-31 14:59:05.979 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.043s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 6.581e-04, size: 256, ETA: 1:08:20
2025-07-31 14:59:08.992 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.014s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.566e-04, size: 480, ETA: 1:08:17
2025-07-31 14:59:11.994 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.018s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 6.552e-04, size: 256, ETA: 1:08:14
2025-07-31 14:59:15.057 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.145s, data_time: 0.006s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.537e-04, size: 480, ETA: 1:08:12
2025-07-31 14:59:16.315 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:59:16.374 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch369
2025-07-31 14:59:19.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.142s, data_time: 0.025s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.515e-04, size: 544, ETA: 1:08:08
2025-07-31 14:59:22.236 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.142s, data_time: 0.033s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 6.501e-04, size: 384, ETA: 1:08:05
2025-07-31 14:59:25.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.147s, data_time: 0.012s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 6.486e-04, size: 352, ETA: 1:08:02
2025-07-31 14:59:28.158 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.049s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 6.472e-04, size: 448, ETA: 1:08:00
2025-07-31 14:59:31.153 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.146s, data_time: 0.043s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.457e-04, size: 448, ETA: 1:07:57
2025-07-31 14:59:34.233 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.021s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 6.443e-04, size: 448, ETA: 1:07:54
2025-07-31 14:59:35.569 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 14:59:35.627 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch370
2025-07-31 14:59:38.519 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.029s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 6.422e-04, size: 448, ETA: 1:07:50
2025-07-31 14:59:41.516 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.026s, total_loss: 5.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.5, lr: 6.408e-04, size: 384, ETA: 1:07:48
2025-07-31 14:59:44.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 6.394e-04, size: 320, ETA: 1:07:45
2025-07-31 14:59:47.389 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.009s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.380e-04, size: 448, ETA: 1:07:42
2025-07-31 14:59:50.352 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.031s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 6.366e-04, size: 448, ETA: 1:07:39
2025-07-31 14:59:53.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 6.352e-04, size: 288, ETA: 1:07:37
2025-07-31 14:59:54.614 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:00:01.152 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:00:04.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:00:06.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6192
2025-07-31 15:00:06.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5632
2025-07-31 15:00:06.527 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3405
2025-07-31 15:00:06.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5076
2025-07-31 15:00:06.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:00:06.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:00:06.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.619
2025-07-31 15:00:06.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.563
2025-07-31 15:00:06.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.340
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.508
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:00:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:00:08.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:00:11.244 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:00:13.496 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:00:15.864 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:00:18.193 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:00:20.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:00:22.796 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:00:25.080 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:00:27.420 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:00:27.420 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-31 15:00:27.420 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-31 15:00:27.420 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:00:27.445 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.51 ms, Average NMS time: 1.06 ms, Average inference time: 2.57 ms

2025-07-31 15:00:27.447 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:00:27.479 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:00:27.514 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch371
2025-07-31 15:00:30.045 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.126s, data_time: 0.041s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.332e-04, size: 448, ETA: 1:07:33
2025-07-31 15:00:33.058 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.146s, data_time: 0.061s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 6.318e-04, size: 448, ETA: 1:07:30
2025-07-31 15:00:36.062 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.149s, data_time: 0.060s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 6.304e-04, size: 448, ETA: 1:07:27
2025-07-31 15:00:39.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.146s, data_time: 0.061s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.291e-04, size: 352, ETA: 1:07:25
2025-07-31 15:00:41.972 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.147s, data_time: 0.055s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.277e-04, size: 320, ETA: 1:07:22
2025-07-31 15:00:44.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.038s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 6.264e-04, size: 544, ETA: 1:07:19
2025-07-31 15:00:46.021 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:00:46.191 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch372
2025-07-31 15:00:49.142 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.140s, data_time: 0.004s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.245e-04, size: 480, ETA: 1:07:16
2025-07-31 15:00:52.113 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.144s, data_time: 0.017s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.231e-04, size: 256, ETA: 1:07:13
2025-07-31 15:00:55.192 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.144s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 6.218e-04, size: 448, ETA: 1:07:10
2025-07-31 15:00:58.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 6.205e-04, size: 480, ETA: 1:07:08
2025-07-31 15:01:01.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.023s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 6.192e-04, size: 512, ETA: 1:07:05
2025-07-31 15:01:04.025 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.015s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.6, lr: 6.179e-04, size: 288, ETA: 1:07:02
2025-07-31 15:01:05.234 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:01:05.380 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch373
2025-07-31 15:01:08.390 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.022s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 6.160e-04, size: 544, ETA: 1:06:58
2025-07-31 15:01:11.389 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.025s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.147e-04, size: 256, ETA: 1:06:55
2025-07-31 15:01:14.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.027s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 6.134e-04, size: 448, ETA: 1:06:52
2025-07-31 15:01:17.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.124s, data_time: 0.009s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 6.122e-04, size: 544, ETA: 1:06:50
2025-07-31 15:01:20.132 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.013s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.109e-04, size: 448, ETA: 1:06:47
2025-07-31 15:01:23.013 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.026s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 6.097e-04, size: 448, ETA: 1:06:44
2025-07-31 15:01:24.310 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:01:24.378 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch374
2025-07-31 15:01:27.294 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.079e-04, size: 576, ETA: 1:06:40
2025-07-31 15:01:30.329 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.011s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 6.066e-04, size: 384, ETA: 1:06:37
2025-07-31 15:01:33.230 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.008s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 6.054e-04, size: 480, ETA: 1:06:35
2025-07-31 15:01:36.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.010s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.042e-04, size: 448, ETA: 1:06:32
2025-07-31 15:01:39.303 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 6.029e-04, size: 352, ETA: 1:06:29
2025-07-31 15:01:42.298 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.013s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.017e-04, size: 352, ETA: 1:06:26
2025-07-31 15:01:43.547 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:01:43.705 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch375
2025-07-31 15:01:46.527 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.126s, data_time: 0.015s, total_loss: 5.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 6.000e-04, size: 256, ETA: 1:06:22
2025-07-31 15:01:49.652 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 5.988e-04, size: 256, ETA: 1:06:20
2025-07-31 15:01:52.508 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.976e-04, size: 544, ETA: 1:06:17
2025-07-31 15:01:55.528 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.964e-04, size: 448, ETA: 1:06:14
2025-07-31 15:01:58.522 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.127s, data_time: 0.015s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 5.953e-04, size: 576, ETA: 1:06:11
2025-07-31 15:02:01.512 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.941e-04, size: 256, ETA: 1:06:08
2025-07-31 15:02:02.888 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:02:09.408 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:02:12.138 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:02:13.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6142
2025-07-31 15:02:14.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5609
2025-07-31 15:02:14.268 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3505
2025-07-31 15:02:14.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5085
2025-07-31 15:02:14.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:02:14.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:02:14.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.614
2025-07-31 15:02:14.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.561
2025-07-31 15:02:14.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.351
2025-07-31 15:02:14.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.509
2025-07-31 15:02:14.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:02:14.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:02:14.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:02:14.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:02:14.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:02:14.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:02:14.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:02:14.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:02:14.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:02:16.342 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:02:18.419 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:02:20.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:02:22.543 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:02:24.754 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:02:26.823 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:02:28.939 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:02:31.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:02:33.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:02:33.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 15:02:33.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-31 15:02:33.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:02:33.156 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 1.01 ms, Average inference time: 2.48 ms

2025-07-31 15:02:33.157 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:02:33.188 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:02:33.222 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch376
2025-07-31 15:02:35.783 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.122s, data_time: 0.023s, total_loss: 4.5, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.924e-04, size: 480, ETA: 1:06:04
2025-07-31 15:02:38.776 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.007s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.913e-04, size: 320, ETA: 1:06:01
2025-07-31 15:02:41.678 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.014s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.901e-04, size: 320, ETA: 1:05:59
2025-07-31 15:02:44.716 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.890e-04, size: 416, ETA: 1:05:56
2025-07-31 15:02:47.689 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.879e-04, size: 256, ETA: 1:05:53
2025-07-31 15:02:50.725 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.010s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 5.868e-04, size: 544, ETA: 1:05:50
2025-07-31 15:02:51.994 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:02:52.162 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch377
2025-07-31 15:02:55.213 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.852e-04, size: 320, ETA: 1:05:46
2025-07-31 15:02:58.198 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.004s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.841e-04, size: 352, ETA: 1:05:43
2025-07-31 15:03:01.122 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.127s, data_time: 0.020s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.830e-04, size: 544, ETA: 1:05:41
2025-07-31 15:03:04.111 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.025s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.819e-04, size: 576, ETA: 1:05:38
2025-07-31 15:03:07.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.808e-04, size: 384, ETA: 1:05:35
2025-07-31 15:03:10.013 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.144s, data_time: 0.056s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.797e-04, size: 256, ETA: 1:05:32
2025-07-31 15:03:11.336 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:03:11.401 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch378
2025-07-31 15:03:14.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.140s, data_time: 0.036s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.782e-04, size: 288, ETA: 1:05:29
2025-07-31 15:03:17.251 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.051s, total_loss: 5.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.771e-04, size: 256, ETA: 1:05:26
2025-07-31 15:03:20.167 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.046s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.761e-04, size: 352, ETA: 1:05:23
2025-07-31 15:03:23.214 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.146s, data_time: 0.049s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.750e-04, size: 544, ETA: 1:05:20
2025-07-31 15:03:26.179 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.146s, data_time: 0.054s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.740e-04, size: 512, ETA: 1:05:18
2025-07-31 15:03:29.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.730e-04, size: 448, ETA: 1:05:15
2025-07-31 15:03:30.441 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:03:30.479 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch379
2025-07-31 15:03:33.317 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.052s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.715e-04, size: 512, ETA: 1:05:11
2025-07-31 15:03:36.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.149s, data_time: 0.061s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 5.705e-04, size: 576, ETA: 1:05:09
2025-07-31 15:03:39.215 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.030s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.695e-04, size: 352, ETA: 1:05:06
2025-07-31 15:03:42.273 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.051s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.685e-04, size: 544, ETA: 1:05:03
2025-07-31 15:03:45.399 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.011s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.675e-04, size: 512, ETA: 1:05:01
2025-07-31 15:03:48.387 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.665e-04, size: 448, ETA: 1:04:58
2025-07-31 15:03:49.704 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:03:49.758 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch380
2025-07-31 15:03:52.664 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.017s, total_loss: 6.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.651e-04, size: 256, ETA: 1:04:54
2025-07-31 15:03:55.681 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.143s, data_time: 0.006s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.642e-04, size: 352, ETA: 1:04:51
2025-07-31 15:03:58.609 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.632e-04, size: 576, ETA: 1:04:48
2025-07-31 15:04:01.550 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.623e-04, size: 544, ETA: 1:04:45
2025-07-31 15:04:04.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.022s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.8, lr: 5.613e-04, size: 448, ETA: 1:04:43
2025-07-31 15:04:07.465 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.051s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.604e-04, size: 576, ETA: 1:04:40
2025-07-31 15:04:08.977 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:04:15.538 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:04:17.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:04:19.397 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6036
2025-07-31 15:04:19.732 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5631
2025-07-31 15:04:19.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3362
2025-07-31 15:04:19.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5009
2025-07-31 15:04:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:04:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:04:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.604
2025-07-31 15:04:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.563
2025-07-31 15:04:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.336
2025-07-31 15:04:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.501
2025-07-31 15:04:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:04:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:04:19.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:04:19.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:04:19.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:04:19.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:04:19.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:04:19.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:04:19.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:04:21.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:04:23.219 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:04:24.888 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:04:26.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:04:28.260 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:04:29.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:04:31.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:04:33.351 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:04:34.999 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:04:35.000 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 15:04:35.000 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-31 15:04:35.000 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:04:35.028 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.48 ms, Average NMS time: 1.00 ms, Average inference time: 2.48 ms

2025-07-31 15:04:35.029 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:04:35.058 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:04:35.089 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch381
2025-07-31 15:04:37.657 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.019s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.590e-04, size: 320, ETA: 1:04:36
2025-07-31 15:04:40.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.007s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.581e-04, size: 512, ETA: 1:04:33
2025-07-31 15:04:43.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.572e-04, size: 448, ETA: 1:04:31
2025-07-31 15:04:46.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.563e-04, size: 256, ETA: 1:04:28
2025-07-31 15:04:49.708 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.014s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.6, lr: 5.554e-04, size: 544, ETA: 1:04:25
2025-07-31 15:04:52.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.142s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.545e-04, size: 256, ETA: 1:04:22
2025-07-31 15:04:53.932 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:04:53.989 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch382
2025-07-31 15:04:57.057 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.533e-04, size: 448, ETA: 1:04:19
2025-07-31 15:04:59.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.524e-04, size: 320, ETA: 1:04:16
2025-07-31 15:05:02.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 5.515e-04, size: 544, ETA: 1:04:13
2025-07-31 15:05:05.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.507e-04, size: 384, ETA: 1:04:10
2025-07-31 15:05:08.873 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.011s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 5.498e-04, size: 384, ETA: 1:04:07
2025-07-31 15:05:11.858 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.490e-04, size: 256, ETA: 1:04:05
2025-07-31 15:05:13.102 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:05:13.208 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch383
2025-07-31 15:05:16.268 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 5.478e-04, size: 544, ETA: 1:04:01
2025-07-31 15:05:19.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.128s, data_time: 0.004s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.469e-04, size: 448, ETA: 1:03:58
2025-07-31 15:05:22.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.461e-04, size: 576, ETA: 1:03:55
2025-07-31 15:05:24.997 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.128s, data_time: 0.013s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.453e-04, size: 288, ETA: 1:03:52
2025-07-31 15:05:27.988 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.445e-04, size: 576, ETA: 1:03:49
2025-07-31 15:05:30.925 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.010s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.437e-04, size: 288, ETA: 1:03:47
2025-07-31 15:05:32.262 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:05:32.325 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch384
2025-07-31 15:05:35.273 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.426e-04, size: 384, ETA: 1:03:43
2025-07-31 15:05:38.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.138s, data_time: 0.011s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.418e-04, size: 576, ETA: 1:03:40
2025-07-31 15:05:41.217 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.027s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 5.410e-04, size: 576, ETA: 1:03:37
2025-07-31 15:05:44.196 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.403e-04, size: 320, ETA: 1:03:34
2025-07-31 15:05:47.182 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.395e-04, size: 576, ETA: 1:03:32
2025-07-31 15:05:50.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.387e-04, size: 384, ETA: 1:03:29
2025-07-31 15:05:51.429 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:05:51.586 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch385
2025-07-31 15:05:54.445 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.128s, data_time: 0.025s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.377e-04, size: 544, ETA: 1:03:25
2025-07-31 15:05:57.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.009s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.369e-04, size: 352, ETA: 1:03:22
2025-07-31 15:06:00.404 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.148s, data_time: 0.008s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.362e-04, size: 320, ETA: 1:03:20
2025-07-31 15:06:03.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.004s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.355e-04, size: 384, ETA: 1:03:17
2025-07-31 15:06:06.294 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.147s, data_time: 0.014s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.348e-04, size: 384, ETA: 1:03:14
2025-07-31 15:06:09.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.143s, data_time: 0.015s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.341e-04, size: 512, ETA: 1:03:12
2025-07-31 15:06:10.452 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:06:16.900 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:06:19.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:06:20.188 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6219
2025-07-31 15:06:20.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5642
2025-07-31 15:06:20.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3760
2025-07-31 15:06:20.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5207
2025-07-31 15:06:20.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.622
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.376
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.521
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:06:20.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:06:20.516 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:06:20.516 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:06:20.516 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:06:22.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:06:23.567 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:06:25.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:06:26.566 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:06:28.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:06:29.568 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:06:31.080 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:06:32.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:06:34.090 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:06:34.090 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-31 15:06:34.090 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:06:34.090 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:06:34.114 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.49 ms, Average NMS time: 1.05 ms, Average inference time: 2.54 ms

2025-07-31 15:06:34.115 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:06:34.148 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:06:34.181 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch386
2025-07-31 15:06:36.944 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.050s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 5.331e-04, size: 480, ETA: 1:03:08
2025-07-31 15:06:39.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.134s, data_time: 0.043s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 5.324e-04, size: 576, ETA: 1:03:05
2025-07-31 15:06:42.781 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.135s, data_time: 0.024s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.317e-04, size: 288, ETA: 1:03:02
2025-07-31 15:06:45.716 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.310e-04, size: 256, ETA: 1:02:59
2025-07-31 15:06:48.780 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.011s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 5.304e-04, size: 544, ETA: 1:02:57
2025-07-31 15:06:51.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.297e-04, size: 288, ETA: 1:02:54
2025-07-31 15:06:53.055 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:06:53.264 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch387
2025-07-31 15:06:56.142 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.288e-04, size: 544, ETA: 1:02:50
2025-07-31 15:06:59.079 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.281e-04, size: 576, ETA: 1:02:47
2025-07-31 15:07:01.974 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.275e-04, size: 352, ETA: 1:02:44
2025-07-31 15:07:04.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.269e-04, size: 512, ETA: 1:02:41
2025-07-31 15:07:07.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.141s, data_time: 0.006s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.263e-04, size: 352, ETA: 1:02:39
2025-07-31 15:07:10.737 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.135s, data_time: 0.009s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 5.256e-04, size: 320, ETA: 1:02:36
2025-07-31 15:07:11.960 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:07:12.032 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch388
2025-07-31 15:07:15.004 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.248e-04, size: 576, ETA: 1:02:32
2025-07-31 15:07:17.933 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.242e-04, size: 384, ETA: 1:02:29
2025-07-31 15:07:20.771 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.128s, data_time: 0.005s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.236e-04, size: 256, ETA: 1:02:26
2025-07-31 15:07:23.786 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.7, lr: 5.230e-04, size: 544, ETA: 1:02:24
2025-07-31 15:07:26.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.134s, data_time: 0.004s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.224e-04, size: 384, ETA: 1:02:21
2025-07-31 15:07:29.678 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.219e-04, size: 544, ETA: 1:02:18
2025-07-31 15:07:31.094 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:07:31.157 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch389
2025-07-31 15:07:34.234 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.211e-04, size: 288, ETA: 1:02:14
2025-07-31 15:07:37.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 5.205e-04, size: 256, ETA: 1:02:11
2025-07-31 15:07:40.040 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.136s, data_time: 0.022s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 5.200e-04, size: 256, ETA: 1:02:09
2025-07-31 15:07:43.220 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.156s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.194e-04, size: 256, ETA: 1:02:06
2025-07-31 15:07:46.288 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.149s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.189e-04, size: 448, ETA: 1:02:03
2025-07-31 15:07:49.175 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.184e-04, size: 320, ETA: 1:02:01
2025-07-31 15:07:50.513 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:07:50.648 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch390
2025-07-31 15:07:53.508 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 5.177e-04, size: 576, ETA: 1:01:57
2025-07-31 15:07:56.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.028s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.172e-04, size: 288, ETA: 1:01:54
2025-07-31 15:07:59.311 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.140s, data_time: 0.051s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.5, lr: 5.167e-04, size: 480, ETA: 1:01:51
2025-07-31 15:08:02.318 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.149s, data_time: 0.062s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 5.162e-04, size: 544, ETA: 1:01:49
2025-07-31 15:08:05.264 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.144s, data_time: 0.055s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.157e-04, size: 256, ETA: 1:01:46
2025-07-31 15:08:08.194 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.138s, data_time: 0.033s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.152e-04, size: 480, ETA: 1:01:43
2025-07-31 15:08:09.567 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:08:16.135 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:08:17.923 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:08:19.019 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6077
2025-07-31 15:08:19.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5512
2025-07-31 15:08:19.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3566
2025-07-31 15:08:19.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5052
2025-07-31 15:08:19.329 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:08:19.329 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:08:19.329 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.608
2025-07-31 15:08:19.329 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.551
2025-07-31 15:08:19.329 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.357
2025-07-31 15:08:19.329 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.505
2025-07-31 15:08:19.329 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:08:19.329 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:08:19.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:08:19.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:08:19.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:08:19.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:08:19.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:08:19.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:08:19.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:08:20.943 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:08:22.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:08:23.728 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:08:25.099 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:08:26.507 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:08:27.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:08:29.246 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:08:30.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:08:32.171 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:08:32.171 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 15:08:32.172 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-31 15:08:32.172 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:08:32.184 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 0.97 ms, Average inference time: 2.45 ms

2025-07-31 15:08:32.185 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:08:32.218 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:08:32.266 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch391
2025-07-31 15:08:34.762 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.121s, data_time: 0.031s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.146e-04, size: 416, ETA: 1:01:39
2025-07-31 15:08:37.725 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.137s, data_time: 0.027s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.141e-04, size: 512, ETA: 1:01:37
2025-07-31 15:08:40.764 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.145s, data_time: 0.053s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 5.137e-04, size: 352, ETA: 1:01:34
2025-07-31 15:08:43.703 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.142s, data_time: 0.051s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.132e-04, size: 384, ETA: 1:01:31
2025-07-31 15:08:46.702 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.143s, data_time: 0.058s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.128e-04, size: 480, ETA: 1:01:29
2025-07-31 15:08:49.653 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.144s, data_time: 0.027s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.124e-04, size: 416, ETA: 1:01:26
2025-07-31 15:08:50.905 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:08:50.989 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch392
2025-07-31 15:08:53.920 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.008s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.117e-04, size: 288, ETA: 1:01:22
2025-07-31 15:08:56.903 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.113e-04, size: 320, ETA: 1:01:19
2025-07-31 15:08:59.829 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.109e-04, size: 512, ETA: 1:01:16
2025-07-31 15:09:02.797 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.105e-04, size: 448, ETA: 1:01:14
2025-07-31 15:09:05.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.005s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.102e-04, size: 512, ETA: 1:01:11
2025-07-31 15:09:08.806 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.141s, data_time: 0.005s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.098e-04, size: 512, ETA: 1:01:08
2025-07-31 15:09:10.008 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:09:10.188 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch393
2025-07-31 15:09:13.279 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.010s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.092e-04, size: 544, ETA: 1:01:04
2025-07-31 15:09:16.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 5.089e-04, size: 512, ETA: 1:01:02
2025-07-31 15:09:19.062 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.085e-04, size: 352, ETA: 1:00:59
2025-07-31 15:09:22.063 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.132s, data_time: 0.013s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.6, lr: 5.082e-04, size: 512, ETA: 1:00:56
2025-07-31 15:09:25.024 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.140s, data_time: 0.004s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.078e-04, size: 544, ETA: 1:00:53
2025-07-31 15:09:28.029 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.147s, data_time: 0.012s, total_loss: 3.7, iou_loss: 1.8, l1_loss: 0.0, conf_loss: 1.3, cls_loss: 0.5, lr: 5.075e-04, size: 256, ETA: 1:00:51
2025-07-31 15:09:29.304 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:09:29.455 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch394
2025-07-31 15:09:32.312 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.140s, data_time: 0.045s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.070e-04, size: 416, ETA: 1:00:47
2025-07-31 15:09:35.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.152s, data_time: 0.063s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 5.067e-04, size: 448, ETA: 1:00:44
2025-07-31 15:09:38.288 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.144s, data_time: 0.057s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.064e-04, size: 576, ETA: 1:00:41
2025-07-31 15:09:41.284 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.147s, data_time: 0.060s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.061e-04, size: 320, ETA: 1:00:39
2025-07-31 15:09:44.196 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.137s, data_time: 0.029s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.058e-04, size: 416, ETA: 1:00:36
2025-07-31 15:09:47.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.143s, data_time: 0.013s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.055e-04, size: 544, ETA: 1:00:33
2025-07-31 15:09:48.423 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:09:48.557 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch395
2025-07-31 15:09:51.532 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.132s, data_time: 0.012s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.051e-04, size: 416, ETA: 1:00:29
2025-07-31 15:09:54.553 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.049e-04, size: 256, ETA: 1:00:27
2025-07-31 15:09:57.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.132s, data_time: 0.005s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.046e-04, size: 256, ETA: 1:00:24
2025-07-31 15:10:00.399 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.013s, total_loss: 4.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.6, cls_loss: 0.7, lr: 5.043e-04, size: 256, ETA: 1:00:21
2025-07-31 15:10:03.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.141s, data_time: 0.038s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.041e-04, size: 544, ETA: 1:00:18
2025-07-31 15:10:06.294 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.141s, data_time: 0.034s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 5.039e-04, size: 352, ETA: 1:00:16
2025-07-31 15:10:07.524 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:10:14.239 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:10:16.612 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:10:18.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6195
2025-07-31 15:10:18.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5619
2025-07-31 15:10:18.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3666
2025-07-31 15:10:18.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5160
2025-07-31 15:10:18.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:10:18.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:10:18.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.619
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.562
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.367
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.516
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:10:18.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:10:18.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:10:18.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:10:20.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:10:22.233 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:10:24.091 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:10:25.885 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:10:27.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:10:29.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:10:31.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:10:33.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:10:34.833 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:10:34.833 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-31 15:10:34.834 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:10:34.834 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:10:34.860 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 0.96 ms, Average inference time: 2.39 ms

2025-07-31 15:10:34.866 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:10:34.893 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:10:34.928 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch396
2025-07-31 15:10:37.519 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.127s, data_time: 0.044s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.035e-04, size: 448, ETA: 1:00:12
2025-07-31 15:10:40.574 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.151s, data_time: 0.063s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.1, lr: 5.033e-04, size: 544, ETA: 1:00:09
2025-07-31 15:10:43.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.143s, data_time: 0.057s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.6, lr: 5.031e-04, size: 448, ETA: 1:00:06
2025-07-31 15:10:46.480 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.150s, data_time: 0.061s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 5.029e-04, size: 576, ETA: 1:00:04
2025-07-31 15:10:49.459 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.141s, data_time: 0.013s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.027e-04, size: 416, ETA: 1:00:01
2025-07-31 15:10:52.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.135s, data_time: 0.022s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.025e-04, size: 576, ETA: 0:59:58
2025-07-31 15:10:53.731 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:10:53.872 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch397
2025-07-31 15:10:56.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.022e-04, size: 448, ETA: 0:59:54
2025-07-31 15:10:59.729 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.148s, data_time: 0.024s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 5.020e-04, size: 384, ETA: 0:59:52
2025-07-31 15:11:02.644 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 5.019e-04, size: 448, ETA: 0:59:49
2025-07-31 15:11:05.736 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.152s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.017e-04, size: 288, ETA: 0:59:46
2025-07-31 15:11:08.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.142s, data_time: 0.040s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.016e-04, size: 544, ETA: 0:59:44
2025-07-31 15:11:11.521 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.140s, data_time: 0.042s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 5.014e-04, size: 320, ETA: 0:59:41
2025-07-31 15:11:12.828 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:11:12.982 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch398
2025-07-31 15:11:15.956 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.012e-04, size: 480, ETA: 0:59:37
2025-07-31 15:11:18.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.011e-04, size: 384, ETA: 0:59:34
2025-07-31 15:11:21.735 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.025s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.010e-04, size: 384, ETA: 0:59:32
2025-07-31 15:11:24.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.138s, data_time: 0.048s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.009e-04, size: 320, ETA: 0:59:29
2025-07-31 15:11:27.538 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.140s, data_time: 0.049s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 5.007e-04, size: 352, ETA: 0:59:26
2025-07-31 15:11:30.496 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.144s, data_time: 0.055s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.006e-04, size: 288, ETA: 0:59:23
2025-07-31 15:11:31.774 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:11:31.875 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch399
2025-07-31 15:11:34.857 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.143s, data_time: 0.052s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.005e-04, size: 288, ETA: 0:59:20
2025-07-31 15:11:37.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.145s, data_time: 0.059s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.004e-04, size: 256, ETA: 0:59:17
2025-07-31 15:11:40.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.144s, data_time: 0.058s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 5.004e-04, size: 448, ETA: 0:59:14
2025-07-31 15:11:43.597 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.144s, data_time: 0.056s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.003e-04, size: 416, ETA: 0:59:12
2025-07-31 15:11:46.585 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.146s, data_time: 0.048s, total_loss: 7.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 5.002e-04, size: 288, ETA: 0:59:09
2025-07-31 15:11:49.559 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.148s, data_time: 0.061s, total_loss: 6.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.002e-04, size: 416, ETA: 0:59:06
2025-07-31 15:11:50.893 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:11:50.958 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch400
2025-07-31 15:11:50.959 | INFO     | yolox_microbt.core.trainer:before_epoch:208 - --->No mosaic aug now!
2025-07-31 15:11:50.960 | INFO     | yolox_microbt.core.trainer:before_epoch:210 - --->Add additional L1 loss now!
2025-07-31 15:11:50.960 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:11:52.973 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.096s, data_time: 0.007s, total_loss: 9.7, iou_loss: 2.4, l1_loss: 1.4, conf_loss: 4.8, cls_loss: 1.1, lr: 5.001e-04, size: 576, ETA: 0:59:02
2025-07-31 15:11:54.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.001e-04, size: 256, ETA: 0:58:59
2025-07-31 15:11:56.679 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:58:55
2025-07-31 15:11:58.512 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:58:52
2025-07-31 15:12:00.244 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:58:49
2025-07-31 15:12:02.010 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.1, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 4.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:58:46
2025-07-31 15:12:02.779 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:12:09.297 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:12:10.072 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:12:10.537 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5905
2025-07-31 15:12:10.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5436
2025-07-31 15:12:10.716 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3258
2025-07-31 15:12:10.716 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4866
2025-07-31 15:12:10.716 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.590
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.544
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.326
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.487
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:12:10.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:12:10.718 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:12:10.718 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:12:10.718 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:12:10.718 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:12:11.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:12:11.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:12:12.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:12:13.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:12:13.637 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:12:14.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:12:14.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:12:15.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:12:15.973 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:12:15.973 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 15:12:15.973 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-07-31 15:12:15.973 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:12:15.980 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 0.96 ms, Average inference time: 2.37 ms

2025-07-31 15:12:15.981 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:12:16.011 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:12:16.045 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch401
2025-07-31 15:12:17.898 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:58:41
2025-07-31 15:12:19.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:58:38
2025-07-31 15:12:21.544 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:58:35
2025-07-31 15:12:23.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:58:31
2025-07-31 15:12:25.213 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:58:28
2025-07-31 15:12:27.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:58:25
2025-07-31 15:12:27.915 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:12:27.955 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch402
2025-07-31 15:12:29.829 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 5.2, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:58:20
2025-07-31 15:12:31.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 1.0, lr: 5.000e-04, size: 416, ETA: 0:58:17
2025-07-31 15:12:33.513 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.4, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 1.0, lr: 5.000e-04, size: 576, ETA: 0:58:14
2025-07-31 15:12:35.357 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:58:11
2025-07-31 15:12:37.152 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:58:08
2025-07-31 15:12:38.965 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 3.4, cls_loss: 1.1, lr: 5.000e-04, size: 320, ETA: 0:58:04
2025-07-31 15:12:39.790 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:12:39.831 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch403
2025-07-31 15:12:41.686 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.007s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:58:00
2025-07-31 15:12:43.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:57:57
2025-07-31 15:12:45.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:57:53
2025-07-31 15:12:47.207 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:57:50
2025-07-31 15:12:48.983 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:57:47
2025-07-31 15:12:50.821 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:57:44
2025-07-31 15:12:51.606 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:12:51.653 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch404
2025-07-31 15:12:53.422 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:57:39
2025-07-31 15:12:55.274 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:57:36
2025-07-31 15:12:57.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:57:33
2025-07-31 15:12:58.877 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 3.4, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:57:30
2025-07-31 15:13:00.681 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:57:26
2025-07-31 15:13:02.498 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:57:23
2025-07-31 15:13:03.319 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:13:03.384 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch405
2025-07-31 15:13:05.228 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:57:19
2025-07-31 15:13:07.041 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 1.3, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:57:15
2025-07-31 15:13:08.855 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 1.4, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:57:12
2025-07-31 15:13:10.754 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:57:09
2025-07-31 15:13:12.597 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:57:06
2025-07-31 15:13:14.349 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:57:03
2025-07-31 15:13:15.160 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:13:21.674 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:13:22.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:13:22.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6099
2025-07-31 15:13:23.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5506
2025-07-31 15:13:23.082 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3999
2025-07-31 15:13:23.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5201
2025-07-31 15:13:23.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:13:23.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:13:23.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.610
2025-07-31 15:13:23.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.551
2025-07-31 15:13:23.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.400
2025-07-31 15:13:23.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.520
2025-07-31 15:13:23.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:13:23.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:13:23.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:13:23.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:13:23.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:13:23.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:13:23.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:13:23.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:13:23.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:13:23.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:13:24.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:13:24.821 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:13:25.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:13:26.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:13:26.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:13:27.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:13:28.099 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:13:28.742 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:13:28.743 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-31 15:13:28.743 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:13:28.743 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:13:28.751 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 0.95 ms, Average inference time: 2.40 ms

2025-07-31 15:13:28.752 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:13:28.797 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:13:28.866 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch406
2025-07-31 15:13:30.737 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 8.5, iou_loss: 2.9, l1_loss: 1.5, conf_loss: 3.2, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:56:58
2025-07-31 15:13:32.539 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.7, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:56:55
2025-07-31 15:13:34.389 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:56:52
2025-07-31 15:13:36.186 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:56:48
2025-07-31 15:13:38.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:56:45
2025-07-31 15:13:39.889 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:56:42
2025-07-31 15:13:40.714 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:13:40.752 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch407
2025-07-31 15:13:42.540 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 4.0, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:56:38
2025-07-31 15:13:44.332 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:56:34
2025-07-31 15:13:46.147 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:56:31
2025-07-31 15:13:47.887 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:56:28
2025-07-31 15:13:49.656 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:56:25
2025-07-31 15:13:51.475 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 9.1, iou_loss: 3.0, l1_loss: 1.3, conf_loss: 3.8, cls_loss: 1.0, lr: 5.000e-04, size: 512, ETA: 0:56:22
2025-07-31 15:13:52.304 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:13:52.353 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch408
2025-07-31 15:13:54.191 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:56:17
2025-07-31 15:13:55.997 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.5, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 8.5, cls_loss: 0.0, lr: 5.000e-04, size: 352, ETA: 0:56:14
2025-07-31 15:13:57.794 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:56:11
2025-07-31 15:13:59.524 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:56:07
2025-07-31 15:14:01.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:56:04
2025-07-31 15:14:03.220 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:56:01
2025-07-31 15:14:04.055 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:14:04.096 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch409
2025-07-31 15:14:05.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 7.8, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 3.5, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:55:57
2025-07-31 15:14:07.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:55:53
2025-07-31 15:14:09.602 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:55:50
2025-07-31 15:14:11.397 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.5, l1_loss: 1.4, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:55:47
2025-07-31 15:14:13.351 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:55:44
2025-07-31 15:14:15.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:55:41
2025-07-31 15:14:15.921 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:14:15.975 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch410
2025-07-31 15:14:17.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.007s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:55:36
2025-07-31 15:14:19.627 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:55:33
2025-07-31 15:14:21.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:55:30
2025-07-31 15:14:23.285 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:55:27
2025-07-31 15:14:25.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:55:24
2025-07-31 15:14:26.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:55:20
2025-07-31 15:14:27.727 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:14:34.149 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:14:34.985 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:14:35.454 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6214
2025-07-31 15:14:35.565 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5466
2025-07-31 15:14:35.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4033
2025-07-31 15:14:35.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5238
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.621
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.547
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.403
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.524
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:14:35.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:14:35.605 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:14:35.605 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:14:35.605 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:14:35.605 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:14:36.241 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:14:36.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:14:37.485 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:14:38.152 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:14:38.762 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:14:39.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:14:40.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:14:40.689 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:14:41.289 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:14:41.289 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:14:41.290 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:14:41.290 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:14:41.299 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.92 ms, Average inference time: 2.31 ms

2025-07-31 15:14:41.300 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:14:41.328 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:14:41.362 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch411
2025-07-31 15:14:43.110 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:55:16
2025-07-31 15:14:44.976 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:55:13
2025-07-31 15:14:46.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:55:10
2025-07-31 15:14:48.651 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:55:06
2025-07-31 15:14:50.412 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:55:03
2025-07-31 15:14:52.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:55:00
2025-07-31 15:14:53.054 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:14:53.100 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch412
2025-07-31 15:14:54.929 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:54:56
2025-07-31 15:14:56.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:54:52
2025-07-31 15:14:58.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:54:49
2025-07-31 15:15:00.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.5, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:54:46
2025-07-31 15:15:02.118 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:54:43
2025-07-31 15:15:03.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:54:40
2025-07-31 15:15:04.778 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:15:04.821 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch413
2025-07-31 15:15:06.587 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.6, iou_loss: 1.8, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:54:35
2025-07-31 15:15:08.433 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.0, l1_loss: 1.3, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:54:32
2025-07-31 15:15:10.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:54:29
2025-07-31 15:15:11.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:54:26
2025-07-31 15:15:13.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:54:23
2025-07-31 15:15:15.614 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:54:20
2025-07-31 15:15:16.449 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:15:16.485 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch414
2025-07-31 15:15:18.330 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.006s, total_loss: 6.8, iou_loss: 2.1, l1_loss: 1.3, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:54:15
2025-07-31 15:15:20.138 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.4, l1_loss: 1.4, conf_loss: 3.2, cls_loss: 1.1, lr: 5.000e-04, size: 576, ETA: 0:54:12
2025-07-31 15:15:21.992 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:54:09
2025-07-31 15:15:23.885 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:54:06
2025-07-31 15:15:25.783 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.3, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:54:03
2025-07-31 15:15:27.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:53:59
2025-07-31 15:15:28.415 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:15:28.456 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch415
2025-07-31 15:15:30.266 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:53:55
2025-07-31 15:15:32.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.4, iou_loss: 2.9, l1_loss: 1.9, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:53:52
2025-07-31 15:15:33.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:53:49
2025-07-31 15:15:35.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:53:46
2025-07-31 15:15:37.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:53:42
2025-07-31 15:15:39.232 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.6, l1_loss: 1.6, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:53:39
2025-07-31 15:15:40.081 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:15:46.517 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:15:47.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:15:47.695 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6073
2025-07-31 15:15:47.816 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5592
2025-07-31 15:15:47.849 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3662
2025-07-31 15:15:47.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5109
2025-07-31 15:15:47.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:15:47.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:15:47.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.607
2025-07-31 15:15:47.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.559
2025-07-31 15:15:47.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.366
2025-07-31 15:15:47.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.511
2025-07-31 15:15:47.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:15:47.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:15:47.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:15:47.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:15:47.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:15:47.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:15:47.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:15:47.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:15:47.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:15:48.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:15:49.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:15:49.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:15:50.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:15:50.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:15:51.346 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:15:51.917 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:15:52.530 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:15:53.141 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:15:53.141 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-31 15:15:53.141 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-31 15:15:53.141 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:15:53.150 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.49 ms, Average NMS time: 1.01 ms, Average inference time: 2.50 ms

2025-07-31 15:15:53.151 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:15:53.178 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:15:53.211 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch416
2025-07-31 15:15:54.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 1.3, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:53:35
2025-07-31 15:15:56.880 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:53:32
2025-07-31 15:15:58.610 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:53:28
2025-07-31 15:16:00.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:53:25
2025-07-31 15:16:02.256 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:53:22
2025-07-31 15:16:04.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:53:19
2025-07-31 15:16:04.969 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:16:05.013 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch417
2025-07-31 15:16:06.885 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 3.8, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:53:15
2025-07-31 15:16:08.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:53:12
2025-07-31 15:16:10.553 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:53:09
2025-07-31 15:16:12.401 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 9.2, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 4.1, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:53:05
2025-07-31 15:16:14.288 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.4, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:53:02
2025-07-31 15:16:16.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:52:59
2025-07-31 15:16:16.976 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:16:17.016 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch418
2025-07-31 15:16:18.906 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:52:55
2025-07-31 15:16:20.798 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 1.2, lr: 5.000e-04, size: 256, ETA: 0:52:52
2025-07-31 15:16:22.739 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:52:49
2025-07-31 15:16:24.594 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 1.5, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:52:46
2025-07-31 15:16:26.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:52:42
2025-07-31 15:16:28.141 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:52:39
2025-07-31 15:16:28.974 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:16:29.020 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch419
2025-07-31 15:16:30.798 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:52:35
2025-07-31 15:16:32.638 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 1.1, lr: 5.000e-04, size: 288, ETA: 0:52:32
2025-07-31 15:16:34.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:52:29
2025-07-31 15:16:36.260 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.3, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:52:26
2025-07-31 15:16:38.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:52:22
2025-07-31 15:16:39.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:52:19
2025-07-31 15:16:40.651 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:16:40.704 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch420
2025-07-31 15:16:42.511 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.0, cls_loss: 1.0, lr: 5.000e-04, size: 288, ETA: 0:52:15
2025-07-31 15:16:44.375 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:52:12
2025-07-31 15:16:46.199 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:52:09
2025-07-31 15:16:47.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 4.9, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:52:06
2025-07-31 15:16:49.831 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:52:02
2025-07-31 15:16:51.621 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.4, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.4, lr: 5.000e-04, size: 480, ETA: 0:51:59
2025-07-31 15:16:52.436 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:16:58.807 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:16:59.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:17:00.188 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6149
2025-07-31 15:17:00.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5408
2025-07-31 15:17:00.323 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4162
2025-07-31 15:17:00.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5240
2025-07-31 15:17:00.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:17:00.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:17:00.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.615
2025-07-31 15:17:00.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.541
2025-07-31 15:17:00.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.416
2025-07-31 15:17:00.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.524
2025-07-31 15:17:00.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:17:00.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:17:00.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:17:00.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:17:00.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:17:00.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:17:00.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:17:00.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:17:00.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:17:00.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:17:01.638 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:17:02.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:17:02.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:17:03.569 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:17:04.192 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:17:04.848 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:17:05.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:17:06.086 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:17:06.086 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:17:06.086 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:17:06.086 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:17:06.093 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.52 ms, Average NMS time: 1.05 ms, Average inference time: 2.57 ms

2025-07-31 15:17:06.094 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:17:06.122 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:17:06.155 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch421
2025-07-31 15:17:07.914 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:51:55
2025-07-31 15:17:09.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:51:52
2025-07-31 15:17:11.524 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:51:49
2025-07-31 15:17:13.374 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:51:46
2025-07-31 15:17:15.327 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.095s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:51:43
2025-07-31 15:17:17.175 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:51:40
2025-07-31 15:17:17.956 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:17:18.085 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch422
2025-07-31 15:17:19.925 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:51:35
2025-07-31 15:17:21.794 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.9, iou_loss: 1.0, l1_loss: 0.5, conf_loss: 3.3, cls_loss: 1.1, lr: 5.000e-04, size: 288, ETA: 0:51:32
2025-07-31 15:17:23.605 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:51:29
2025-07-31 15:17:25.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:51:26
2025-07-31 15:17:27.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:51:23
2025-07-31 15:17:28.999 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:51:20
2025-07-31 15:17:29.813 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:17:29.870 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch423
2025-07-31 15:17:31.711 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:51:15
2025-07-31 15:17:33.545 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:51:12
2025-07-31 15:17:35.346 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 9.3, iou_loss: 3.3, l1_loss: 1.3, conf_loss: 4.0, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:51:09
2025-07-31 15:17:37.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:51:06
2025-07-31 15:17:38.953 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 4.4, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:51:03
2025-07-31 15:17:40.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:51:00
2025-07-31 15:17:41.601 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:17:41.661 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch424
2025-07-31 15:17:43.549 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:50:56
2025-07-31 15:17:45.335 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:50:52
2025-07-31 15:17:47.089 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:50:49
2025-07-31 15:17:48.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:50:46
2025-07-31 15:17:50.661 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:50:43
2025-07-31 15:17:52.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:50:40
2025-07-31 15:17:53.271 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:17:53.337 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch425
2025-07-31 15:17:55.124 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:50:36
2025-07-31 15:17:56.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 11.9, iou_loss: 3.8, l1_loss: 1.5, conf_loss: 5.8, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:50:33
2025-07-31 15:17:58.790 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:50:30
2025-07-31 15:18:00.726 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:50:27
2025-07-31 15:18:02.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:50:23
2025-07-31 15:18:04.317 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:50:20
2025-07-31 15:18:05.180 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:18:11.691 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:18:12.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:18:13.127 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6231
2025-07-31 15:18:13.298 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5495
2025-07-31 15:18:13.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4077
2025-07-31 15:18:13.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5268
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.623
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.549
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.408
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.527
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:18:13.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:18:13.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:18:13.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:18:13.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:18:13.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:18:13.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:18:14.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:18:14.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:18:15.488 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:18:16.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:18:16.675 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:18:17.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:18:17.897 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:18:18.486 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:18:19.113 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:18:19.114 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:18:19.114 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:18:19.114 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:18:19.121 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 0.99 ms, Average inference time: 2.41 ms

2025-07-31 15:18:19.122 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:18:19.145 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:18:19.179 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch426
2025-07-31 15:18:20.985 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:50:16
2025-07-31 15:18:22.773 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:50:13
2025-07-31 15:18:24.553 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:50:10
2025-07-31 15:18:26.403 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:50:07
2025-07-31 15:18:28.268 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:50:04
2025-07-31 15:18:30.138 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:50:01
2025-07-31 15:18:30.965 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:18:31.017 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch427
2025-07-31 15:18:32.839 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 11.2, iou_loss: 3.2, l1_loss: 1.5, conf_loss: 5.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:49:56
2025-07-31 15:18:34.585 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:49:53
2025-07-31 15:18:36.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:49:50
2025-07-31 15:18:38.267 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:49:47
2025-07-31 15:18:40.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:49:44
2025-07-31 15:18:41.887 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:49:41
2025-07-31 15:18:42.776 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:18:42.814 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch428
2025-07-31 15:18:44.648 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:49:37
2025-07-31 15:18:46.504 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:49:34
2025-07-31 15:18:48.335 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:49:31
2025-07-31 15:18:50.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:49:28
2025-07-31 15:18:52.006 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:49:25
2025-07-31 15:18:53.885 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:49:22
2025-07-31 15:18:54.703 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:18:54.743 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch429
2025-07-31 15:18:56.648 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:49:17
2025-07-31 15:18:58.551 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:49:14
2025-07-31 15:19:00.483 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.094s, data_time: 0.004s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:49:11
2025-07-31 15:19:02.295 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:49:08
2025-07-31 15:19:04.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.9, l1_loss: 1.2, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:49:05
2025-07-31 15:19:06.064 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:49:02
2025-07-31 15:19:06.995 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:19:07.036 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch430
2025-07-31 15:19:08.795 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 1.2, lr: 5.000e-04, size: 352, ETA: 0:48:58
2025-07-31 15:19:10.684 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.004s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:48:55
2025-07-31 15:19:12.729 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.099s, data_time: 0.005s, total_loss: 7.7, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 3.7, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:48:52
2025-07-31 15:19:14.684 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.4, l1_loss: 1.3, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:48:49
2025-07-31 15:19:16.517 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:48:46
2025-07-31 15:19:18.511 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.098s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:48:43
2025-07-31 15:19:19.353 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:19:26.058 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:19:26.842 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:19:27.268 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6156
2025-07-31 15:19:27.420 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5615
2025-07-31 15:19:27.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3950
2025-07-31 15:19:27.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5240
2025-07-31 15:19:27.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:19:27.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:19:27.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.616
2025-07-31 15:19:27.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.562
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.395
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.524
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:19:27.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:19:28.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:19:28.726 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:19:29.332 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:19:29.987 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:19:30.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:19:31.254 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:19:31.857 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:19:32.494 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:19:33.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:19:33.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:19:33.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:19:33.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:19:33.106 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.89 ms, Average inference time: 2.25 ms

2025-07-31 15:19:33.107 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:19:33.133 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:19:33.165 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch431
2025-07-31 15:19:34.985 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.4, lr: 5.000e-04, size: 352, ETA: 0:48:39
2025-07-31 15:19:36.696 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.1, iou_loss: 1.1, l1_loss: 0.3, conf_loss: 1.3, cls_loss: 0.4, lr: 5.000e-04, size: 352, ETA: 0:48:36
2025-07-31 15:19:38.452 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:48:32
2025-07-31 15:19:40.325 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:48:29
2025-07-31 15:19:42.187 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:48:26
2025-07-31 15:19:43.965 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:48:23
2025-07-31 15:19:44.818 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:19:44.869 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch432
2025-07-31 15:19:46.708 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:48:19
2025-07-31 15:19:48.444 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:48:16
2025-07-31 15:19:50.302 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:48:13
2025-07-31 15:19:52.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.4, l1_loss: 0.6, conf_loss: 4.0, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:48:10
2025-07-31 15:19:53.933 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:48:07
2025-07-31 15:19:55.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:48:04
2025-07-31 15:19:56.585 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:19:56.638 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch433
2025-07-31 15:19:58.442 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:48:00
2025-07-31 15:20:00.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.8, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:47:57
2025-07-31 15:20:02.294 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:47:54
2025-07-31 15:20:04.135 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.1, l1_loss: 0.3, conf_loss: 2.9, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:47:51
2025-07-31 15:20:06.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:47:48
2025-07-31 15:20:07.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:47:45
2025-07-31 15:20:08.700 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:20:08.739 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch434
2025-07-31 15:20:10.508 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:47:40
2025-07-31 15:20:12.263 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:47:37
2025-07-31 15:20:14.171 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.9, iou_loss: 1.8, l1_loss: 1.4, conf_loss: 3.2, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:47:34
2025-07-31 15:20:15.992 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:47:31
2025-07-31 15:20:17.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:47:28
2025-07-31 15:20:19.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.5, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:47:25
2025-07-31 15:20:20.568 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:20:20.612 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch435
2025-07-31 15:20:22.435 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:47:21
2025-07-31 15:20:24.198 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:47:18
2025-07-31 15:20:25.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:47:15
2025-07-31 15:20:27.779 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 2.0, cls_loss: 1.3, lr: 5.000e-04, size: 320, ETA: 0:47:12
2025-07-31 15:20:29.569 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:47:09
2025-07-31 15:20:31.353 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 1.1, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:47:06
2025-07-31 15:20:32.229 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:20:38.535 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:20:39.517 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:20:40.143 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6152
2025-07-31 15:20:40.260 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5563
2025-07-31 15:20:40.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4004
2025-07-31 15:20:40.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5240
2025-07-31 15:20:40.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:20:40.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.615
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.556
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.400
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.524
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:20:40.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:20:40.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:20:41.113 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:20:41.894 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:20:42.716 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:20:43.485 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:20:44.313 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:20:45.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:20:45.936 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:20:46.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:20:47.561 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:20:47.562 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:20:47.562 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:20:47.562 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:20:47.571 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.97 ms, Average inference time: 2.41 ms

2025-07-31 15:20:47.572 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:20:47.598 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:20:47.629 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch436
2025-07-31 15:20:49.357 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:47:02
2025-07-31 15:20:51.156 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:46:59
2025-07-31 15:20:53.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:46:56
2025-07-31 15:20:54.812 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:46:53
2025-07-31 15:20:56.680 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:46:50
2025-07-31 15:20:58.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.5, l1_loss: 0.7, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:46:47
2025-07-31 15:20:59.280 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:20:59.322 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch437
2025-07-31 15:21:01.111 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:46:42
2025-07-31 15:21:02.971 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 2.6, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:46:39
2025-07-31 15:21:04.828 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:46:36
2025-07-31 15:21:06.675 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:46:33
2025-07-31 15:21:08.532 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:46:30
2025-07-31 15:21:10.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:46:27
2025-07-31 15:21:11.232 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:21:11.275 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch438
2025-07-31 15:21:13.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:46:23
2025-07-31 15:21:14.857 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:46:20
2025-07-31 15:21:16.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:46:17
2025-07-31 15:21:18.529 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:46:14
2025-07-31 15:21:20.338 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.5, l1_loss: 1.4, conf_loss: 3.2, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:46:11
2025-07-31 15:21:22.129 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:46:08
2025-07-31 15:21:22.978 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:21:23.031 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch439
2025-07-31 15:21:24.869 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 1.0, lr: 5.000e-04, size: 512, ETA: 0:46:04
2025-07-31 15:21:26.760 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:46:01
2025-07-31 15:21:28.512 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 1.3, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:45:58
2025-07-31 15:21:30.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:45:55
2025-07-31 15:21:32.189 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:45:52
2025-07-31 15:21:34.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:45:49
2025-07-31 15:21:34.898 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:21:34.962 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch440
2025-07-31 15:21:36.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:45:45
2025-07-31 15:21:38.638 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 1.0, lr: 5.000e-04, size: 352, ETA: 0:45:42
2025-07-31 15:21:40.341 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:45:39
2025-07-31 15:21:42.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:45:36
2025-07-31 15:21:43.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:45:33
2025-07-31 15:21:45.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:45:30
2025-07-31 15:21:46.502 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:21:52.787 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:21:53.718 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:21:54.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6108
2025-07-31 15:21:54.389 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5659
2025-07-31 15:21:54.474 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3867
2025-07-31 15:21:54.474 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5211
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.611
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.566
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.387
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.521
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:21:54.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:21:54.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:21:54.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:21:54.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:21:54.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:21:54.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:21:55.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:21:55.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:21:56.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:21:57.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:21:58.107 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:21:58.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:21:59.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:22:00.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:22:00.870 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:22:00.870 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-31 15:22:00.870 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:22:00.871 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:22:00.878 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.98 ms, Average inference time: 2.42 ms

2025-07-31 15:22:00.879 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:22:00.902 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:22:00.935 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch441
2025-07-31 15:22:02.686 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:45:26
2025-07-31 15:22:04.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:45:23
2025-07-31 15:22:06.263 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:45:20
2025-07-31 15:22:08.079 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:45:17
2025-07-31 15:22:09.887 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.4, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 1.1, lr: 5.000e-04, size: 416, ETA: 0:45:14
2025-07-31 15:22:11.804 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.095s, data_time: 0.003s, total_loss: 4.0, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:45:11
2025-07-31 15:22:12.596 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:22:12.737 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch442
2025-07-31 15:22:14.551 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:45:06
2025-07-31 15:22:16.414 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:45:04
2025-07-31 15:22:18.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:45:01
2025-07-31 15:22:19.999 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:44:58
2025-07-31 15:22:21.812 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:44:55
2025-07-31 15:22:23.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.094s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:44:52
2025-07-31 15:22:24.582 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:22:24.647 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch443
2025-07-31 15:22:26.333 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:44:47
2025-07-31 15:22:28.147 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:44:44
2025-07-31 15:22:30.038 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:44:42
2025-07-31 15:22:31.867 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:44:39
2025-07-31 15:22:33.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:44:36
2025-07-31 15:22:35.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.096s, data_time: 0.003s, total_loss: 4.0, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 1.3, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:44:33
2025-07-31 15:22:36.464 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:22:36.513 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch444
2025-07-31 15:22:38.336 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:44:28
2025-07-31 15:22:40.135 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:44:25
2025-07-31 15:22:41.917 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:44:23
2025-07-31 15:22:43.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:44:20
2025-07-31 15:22:45.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 1.3, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:44:17
2025-07-31 15:22:47.382 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:44:14
2025-07-31 15:22:48.233 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:22:48.279 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch445
2025-07-31 15:22:50.097 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 1.1, lr: 5.000e-04, size: 288, ETA: 0:44:09
2025-07-31 15:22:51.879 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 1.5, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:44:06
2025-07-31 15:22:53.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:44:04
2025-07-31 15:22:55.572 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:44:01
2025-07-31 15:22:57.334 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:43:58
2025-07-31 15:22:59.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:43:55
2025-07-31 15:23:00.029 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:23:06.453 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:23:07.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:23:07.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6212
2025-07-31 15:23:07.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5636
2025-07-31 15:23:07.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4020
2025-07-31 15:23:07.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5289
2025-07-31 15:23:07.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:23:07.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:23:07.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.621
2025-07-31 15:23:07.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-07-31 15:23:07.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.402
2025-07-31 15:23:07.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.529
2025-07-31 15:23:07.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:23:07.784 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:23:07.784 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:23:07.784 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:23:07.784 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:23:07.784 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:23:07.784 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:23:07.784 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:23:07.785 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:23:08.338 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:23:08.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:23:09.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:23:09.985 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:23:10.593 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:23:11.160 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:23:11.718 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:23:12.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:23:12.854 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:23:12.854 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:23:12.855 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:23:12.855 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:23:12.869 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.96 ms, Average inference time: 2.38 ms

2025-07-31 15:23:12.870 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:23:12.910 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:23:12.966 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch446
2025-07-31 15:23:14.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:43:50
2025-07-31 15:23:16.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:43:48
2025-07-31 15:23:18.341 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.3, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:43:45
2025-07-31 15:23:20.179 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:43:42
2025-07-31 15:23:22.072 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:43:39
2025-07-31 15:23:23.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:43:36
2025-07-31 15:23:24.770 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:23:24.820 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch447
2025-07-31 15:23:26.633 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:43:32
2025-07-31 15:23:28.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:43:29
2025-07-31 15:23:30.283 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:43:26
2025-07-31 15:23:32.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:43:23
2025-07-31 15:23:34.006 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:43:20
2025-07-31 15:23:35.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:43:17
2025-07-31 15:23:36.641 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:23:36.690 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch448
2025-07-31 15:23:38.570 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:43:13
2025-07-31 15:23:40.316 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:43:10
2025-07-31 15:23:42.184 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:43:07
2025-07-31 15:23:43.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:43:04
2025-07-31 15:23:45.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 12.4, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 12.4, cls_loss: 0.0, lr: 5.000e-04, size: 416, ETA: 0:43:01
2025-07-31 15:23:47.719 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:42:58
2025-07-31 15:23:48.507 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:23:48.574 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch449
2025-07-31 15:23:50.310 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:42:54
2025-07-31 15:23:52.109 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.1, l1_loss: 1.1, conf_loss: 3.8, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:42:51
2025-07-31 15:23:53.978 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:42:48
2025-07-31 15:23:55.889 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:42:45
2025-07-31 15:23:57.649 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:42:42
2025-07-31 15:23:59.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:42:39
2025-07-31 15:24:00.297 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:24:00.352 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch450
2025-07-31 15:24:02.152 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:42:35
2025-07-31 15:24:03.928 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:42:32
2025-07-31 15:24:05.794 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:42:29
2025-07-31 15:24:07.718 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.3, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:42:26
2025-07-31 15:24:09.459 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:42:23
2025-07-31 15:24:11.296 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:42:20
2025-07-31 15:24:12.114 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:24:18.610 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:24:19.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:24:20.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6204
2025-07-31 15:24:20.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5403
2025-07-31 15:24:20.360 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3971
2025-07-31 15:24:20.361 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5193
2025-07-31 15:24:20.361 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:24:20.361 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:24:20.361 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.620
2025-07-31 15:24:20.361 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.540
2025-07-31 15:24:20.361 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.397
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.519
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:24:20.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:24:21.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:24:21.747 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:24:22.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:24:23.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:24:24.000 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:24:24.711 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:24:25.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:24:26.211 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:24:26.919 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:24:26.919 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:24:26.919 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:24:26.919 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:24:26.929 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.49 ms, Average NMS time: 0.99 ms, Average inference time: 2.48 ms

2025-07-31 15:24:26.929 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:24:26.963 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:24:27.000 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch451
2025-07-31 15:24:28.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:42:16
2025-07-31 15:24:30.650 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:42:13
2025-07-31 15:24:32.652 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.095s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.1, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:42:10
2025-07-31 15:24:34.513 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:42:07
2025-07-31 15:24:36.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:42:05
2025-07-31 15:24:38.249 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:42:02
2025-07-31 15:24:39.139 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:24:39.187 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch452
2025-07-31 15:24:41.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:41:58
2025-07-31 15:24:42.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.0, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 0.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:41:55
2025-07-31 15:24:44.847 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:41:52
2025-07-31 15:24:46.640 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:41:49
2025-07-31 15:24:48.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:41:46
2025-07-31 15:24:50.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:41:43
2025-07-31 15:24:51.220 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:24:51.281 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch453
2025-07-31 15:24:53.092 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:41:39
2025-07-31 15:24:54.906 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:41:36
2025-07-31 15:24:56.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.095s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:41:33
2025-07-31 15:24:58.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:41:30
2025-07-31 15:25:00.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 3.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:41:27
2025-07-31 15:25:02.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:41:24
2025-07-31 15:25:03.252 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:25:03.292 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch454
2025-07-31 15:25:05.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 1.0, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:41:20
2025-07-31 15:25:06.932 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:41:17
2025-07-31 15:25:08.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:41:14
2025-07-31 15:25:10.500 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:41:12
2025-07-31 15:25:12.292 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:41:09
2025-07-31 15:25:14.101 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.006s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:41:06
2025-07-31 15:25:14.926 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:25:14.968 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch455
2025-07-31 15:25:16.797 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:41:02
2025-07-31 15:25:18.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:40:59
2025-07-31 15:25:20.471 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:40:56
2025-07-31 15:25:22.290 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 3.2, cls_loss: 1.0, lr: 5.000e-04, size: 512, ETA: 0:40:53
2025-07-31 15:25:24.182 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:40:50
2025-07-31 15:25:26.092 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 3.4, iou_loss: 0.8, l1_loss: 0.3, conf_loss: 2.1, cls_loss: 0.3, lr: 5.000e-04, size: 416, ETA: 0:40:47
2025-07-31 15:25:26.899 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:25:33.236 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:25:33.991 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:25:34.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6085
2025-07-31 15:25:34.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5644
2025-07-31 15:25:34.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3689
2025-07-31 15:25:34.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5139
2025-07-31 15:25:34.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:25:34.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:25:34.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.608
2025-07-31 15:25:34.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-07-31 15:25:34.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.369
2025-07-31 15:25:34.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.514
2025-07-31 15:25:34.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:25:34.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:25:34.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:25:34.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:25:34.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:25:34.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:25:34.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:25:34.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:25:34.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:25:35.099 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:25:35.613 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:25:36.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:25:36.648 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:25:37.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:25:37.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:25:38.225 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:25:38.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:25:39.386 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:25:39.387 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-31 15:25:39.387 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-31 15:25:39.387 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:25:39.395 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.94 ms, Average inference time: 2.38 ms

2025-07-31 15:25:39.396 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:25:39.430 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:25:39.471 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch456
2025-07-31 15:25:41.267 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:40:43
2025-07-31 15:25:43.075 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:40:40
2025-07-31 15:25:44.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.6, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:40:37
2025-07-31 15:25:46.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 1.4, cls_loss: 0.4, lr: 5.000e-04, size: 288, ETA: 0:40:34
2025-07-31 15:25:48.598 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:40:31
2025-07-31 15:25:50.461 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 7.8, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:40:29
2025-07-31 15:25:51.293 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:25:51.350 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch457
2025-07-31 15:25:53.125 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:40:24
2025-07-31 15:25:54.855 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:40:21
2025-07-31 15:25:56.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:40:19
2025-07-31 15:25:58.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:40:16
2025-07-31 15:26:00.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:40:13
2025-07-31 15:26:02.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:40:10
2025-07-31 15:26:02.968 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:26:03.035 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch458
2025-07-31 15:26:04.814 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:40:06
2025-07-31 15:26:06.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:40:03
2025-07-31 15:26:08.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.7, l1_loss: 1.8, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:40:00
2025-07-31 15:26:10.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:39:57
2025-07-31 15:26:12.002 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:39:54
2025-07-31 15:26:13.928 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.094s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:39:51
2025-07-31 15:26:14.678 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:26:14.725 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch459
2025-07-31 15:26:16.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:39:47
2025-07-31 15:26:18.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:39:44
2025-07-31 15:26:20.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:39:41
2025-07-31 15:26:21.877 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:39:38
2025-07-31 15:26:23.725 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:39:36
2025-07-31 15:26:25.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.095s, data_time: 0.007s, total_loss: 7.6, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 3.5, cls_loss: 1.1, lr: 5.000e-04, size: 320, ETA: 0:39:33
2025-07-31 15:26:26.437 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:26:26.479 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch460
2025-07-31 15:26:28.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 1.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:39:29
2025-07-31 15:26:30.062 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:39:26
2025-07-31 15:26:31.922 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:39:23
2025-07-31 15:26:33.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.4, l1_loss: 0.6, conf_loss: 3.0, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:39:20
2025-07-31 15:26:35.567 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:39:17
2025-07-31 15:26:37.426 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:39:14
2025-07-31 15:26:38.288 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:26:44.937 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:26:45.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:26:46.011 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6269
2025-07-31 15:26:46.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5757
2025-07-31 15:26:46.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3995
2025-07-31 15:26:46.142 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5340
2025-07-31 15:26:46.143 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:26:46.143 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:26:46.143 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.627
2025-07-31 15:26:46.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.576
2025-07-31 15:26:46.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.400
2025-07-31 15:26:46.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.534
2025-07-31 15:26:46.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:26:46.146 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:26:46.146 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:26:46.146 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:26:46.147 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:26:46.147 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:26:46.148 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:26:46.148 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:26:46.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:26:46.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:26:47.264 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:26:47.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:26:48.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:26:48.810 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:26:49.332 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:26:49.879 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:26:50.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:26:50.939 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:26:50.940 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:26:50.940 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:26:50.940 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:26:50.950 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.97 ms, Average inference time: 2.41 ms

2025-07-31 15:26:50.951 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:26:50.982 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:26:51.015 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch461
2025-07-31 15:26:52.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:39:10
2025-07-31 15:26:54.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:39:07
2025-07-31 15:26:56.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.3, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:39:04
2025-07-31 15:26:58.470 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:39:02
2025-07-31 15:27:00.329 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:38:59
2025-07-31 15:27:02.096 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 3.7, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:38:56
2025-07-31 15:27:02.908 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:27:02.958 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch462
2025-07-31 15:27:04.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:38:52
2025-07-31 15:27:06.599 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:38:49
2025-07-31 15:27:08.383 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:38:46
2025-07-31 15:27:10.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:38:43
2025-07-31 15:27:12.074 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:38:40
2025-07-31 15:27:13.966 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:38:37
2025-07-31 15:27:14.800 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:27:14.840 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch463
2025-07-31 15:27:16.697 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 1.5, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:38:33
2025-07-31 15:27:18.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 9.1, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 4.5, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:38:31
2025-07-31 15:27:20.461 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 1.3, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:38:28
2025-07-31 15:27:22.312 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.4, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:38:25
2025-07-31 15:27:24.127 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 2.7, iou_loss: 1.1, l1_loss: 0.2, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:38:22
2025-07-31 15:27:25.996 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:38:19
2025-07-31 15:27:26.787 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:27:26.827 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch464
2025-07-31 15:27:28.684 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:38:15
2025-07-31 15:27:30.524 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:38:12
2025-07-31 15:27:32.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:38:09
2025-07-31 15:27:34.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:38:06
2025-07-31 15:27:36.014 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:38:04
2025-07-31 15:27:37.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:38:01
2025-07-31 15:27:38.718 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:27:38.777 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch465
2025-07-31 15:27:40.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:37:57
2025-07-31 15:27:42.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:37:54
2025-07-31 15:27:44.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:37:51
2025-07-31 15:27:45.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:37:48
2025-07-31 15:27:47.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:37:45
2025-07-31 15:27:49.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.006s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:37:42
2025-07-31 15:27:50.367 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:27:56.822 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:27:57.897 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:27:58.486 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5998
2025-07-31 15:27:58.598 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5337
2025-07-31 15:27:58.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3149
2025-07-31 15:27:58.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4828
2025-07-31 15:27:58.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:27:58.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:27:58.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.600
2025-07-31 15:27:58.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.534
2025-07-31 15:27:58.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.315
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.483
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:27:58.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:27:59.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:27:59.919 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:28:00.565 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:28:01.200 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:28:01.817 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:28:02.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:28:03.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:28:03.674 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:28:04.328 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:28:04.328 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 15:28:04.328 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-31 15:28:04.328 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:28:04.336 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 0.98 ms, Average inference time: 2.44 ms

2025-07-31 15:28:04.337 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:28:04.378 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:28:04.424 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch466
2025-07-31 15:28:06.268 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:37:38
2025-07-31 15:28:08.017 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:37:35
2025-07-31 15:28:09.780 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:37:33
2025-07-31 15:28:11.572 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.9, iou_loss: 3.1, l1_loss: 1.0, conf_loss: 3.9, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:37:30
2025-07-31 15:28:13.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:37:27
2025-07-31 15:28:15.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 5.8, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:37:24
2025-07-31 15:28:16.225 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:28:16.267 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch467
2025-07-31 15:28:18.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:37:20
2025-07-31 15:28:19.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:37:17
2025-07-31 15:28:21.656 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:37:14
2025-07-31 15:28:23.466 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:37:11
2025-07-31 15:28:25.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 3.3, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:37:09
2025-07-31 15:28:27.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:37:06
2025-07-31 15:28:27.895 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:28:27.950 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch468
2025-07-31 15:28:29.697 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:37:02
2025-07-31 15:28:31.530 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:36:59
2025-07-31 15:28:33.398 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 1.4, lr: 5.000e-04, size: 480, ETA: 0:36:56
2025-07-31 15:28:35.286 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.5, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:36:53
2025-07-31 15:28:37.071 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:36:50
2025-07-31 15:28:38.924 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:36:48
2025-07-31 15:28:39.755 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:28:39.796 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch469
2025-07-31 15:28:41.594 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:36:43
2025-07-31 15:28:43.452 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:36:41
2025-07-31 15:28:45.295 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 0.7, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:36:38
2025-07-31 15:28:47.152 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:36:35
2025-07-31 15:28:48.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:36:32
2025-07-31 15:28:50.740 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 10.4, iou_loss: 3.2, l1_loss: 1.3, conf_loss: 4.7, cls_loss: 1.2, lr: 5.000e-04, size: 512, ETA: 0:36:29
2025-07-31 15:28:51.629 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:28:51.687 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch470
2025-07-31 15:28:53.437 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.1, l1_loss: 0.3, conf_loss: 3.1, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:36:25
2025-07-31 15:28:55.282 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:36:22
2025-07-31 15:28:57.101 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:36:20
2025-07-31 15:28:58.888 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:36:17
2025-07-31 15:29:00.639 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:36:14
2025-07-31 15:29:02.609 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.096s, data_time: 0.003s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:36:11
2025-07-31 15:29:03.410 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:29:09.901 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:29:10.796 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:29:11.244 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6267
2025-07-31 15:29:11.423 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5931
2025-07-31 15:29:11.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3798
2025-07-31 15:29:11.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5332
2025-07-31 15:29:11.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:29:11.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:29:11.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.627
2025-07-31 15:29:11.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.593
2025-07-31 15:29:11.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.380
2025-07-31 15:29:11.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.533
2025-07-31 15:29:11.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:29:11.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:29:11.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:29:11.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:29:11.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:29:11.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:29:11.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:29:11.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:29:11.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:29:12.180 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:29:12.889 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:29:13.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:29:14.261 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:29:15.035 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:29:15.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:29:16.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:29:17.186 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:29:17.876 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:29:17.876 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:29:17.876 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:29:17.876 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:29:17.883 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.48 ms, Average NMS time: 1.03 ms, Average inference time: 2.51 ms

2025-07-31 15:29:17.884 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:29:17.908 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:29:17.941 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch471
2025-07-31 15:29:19.659 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:36:07
2025-07-31 15:29:21.508 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:36:04
2025-07-31 15:29:23.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:36:01
2025-07-31 15:29:25.162 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:35:59
2025-07-31 15:29:26.984 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:35:56
2025-07-31 15:29:28.877 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:35:53
2025-07-31 15:29:29.753 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:29:29.819 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch472
2025-07-31 15:29:31.614 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:35:49
2025-07-31 15:29:33.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.2, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:35:46
2025-07-31 15:29:35.167 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:35:43
2025-07-31 15:29:36.997 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.8, l1_loss: 1.8, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:35:41
2025-07-31 15:29:38.796 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:35:38
2025-07-31 15:29:40.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:35:35
2025-07-31 15:29:41.458 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:29:41.516 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch473
2025-07-31 15:29:43.241 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 4.1, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:35:31
2025-07-31 15:29:45.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:35:28
2025-07-31 15:29:46.802 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 1.0, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:35:25
2025-07-31 15:29:48.637 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:35:22
2025-07-31 15:29:50.516 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:35:20
2025-07-31 15:29:52.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:35:17
2025-07-31 15:29:53.159 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:29:53.227 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch474
2025-07-31 15:29:54.976 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 4.5, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:35:13
2025-07-31 15:29:56.816 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:35:10
2025-07-31 15:29:58.595 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:35:07
2025-07-31 15:30:00.483 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:35:04
2025-07-31 15:30:02.373 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:35:02
2025-07-31 15:30:04.213 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:34:59
2025-07-31 15:30:05.016 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:30:05.075 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch475
2025-07-31 15:30:06.922 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:34:55
2025-07-31 15:30:08.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:34:52
2025-07-31 15:30:10.633 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.3, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:34:49
2025-07-31 15:30:12.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:34:46
2025-07-31 15:30:14.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 4.1, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:34:43
2025-07-31 15:30:15.994 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:34:41
2025-07-31 15:30:16.811 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:30:23.397 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:30:24.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:30:24.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6230
2025-07-31 15:30:24.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5743
2025-07-31 15:30:24.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3946
2025-07-31 15:30:24.838 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5306
2025-07-31 15:30:24.838 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:30:24.838 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:30:24.838 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.623
2025-07-31 15:30:24.838 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.574
2025-07-31 15:30:24.838 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.395
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.531
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:30:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:30:25.458 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:30:26.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:30:26.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:30:27.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:30:27.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:30:28.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:30:29.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:30:29.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:30:30.347 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:30:30.347 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:30:30.348 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:30:30.348 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:30:30.354 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.48 ms, Average NMS time: 0.99 ms, Average inference time: 2.47 ms

2025-07-31 15:30:30.355 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:30:30.385 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:30:30.419 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch476
2025-07-31 15:30:32.174 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.1, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 0.8, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:34:37
2025-07-31 15:30:34.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:34:34
2025-07-31 15:30:35.827 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 3.4, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:34:31
2025-07-31 15:30:37.661 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:34:28
2025-07-31 15:30:39.502 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:34:25
2025-07-31 15:30:41.347 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:34:23
2025-07-31 15:30:42.160 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:30:42.205 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch477
2025-07-31 15:30:44.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:34:19
2025-07-31 15:30:45.875 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:34:16
2025-07-31 15:30:47.691 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:34:13
2025-07-31 15:30:49.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:34:10
2025-07-31 15:30:51.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.003s, total_loss: 4.4, iou_loss: 2.2, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:34:08
2025-07-31 15:30:53.377 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:34:05
2025-07-31 15:30:54.202 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:30:54.261 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch478
2025-07-31 15:30:56.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:34:01
2025-07-31 15:30:58.034 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:33:58
2025-07-31 15:30:59.870 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:33:55
2025-07-31 15:31:01.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:33:52
2025-07-31 15:31:03.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 3.5, iou_loss: 1.1, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:33:50
2025-07-31 15:31:05.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:33:47
2025-07-31 15:31:06.225 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:31:06.272 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch479
2025-07-31 15:31:08.096 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:33:43
2025-07-31 15:31:09.880 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:33:40
2025-07-31 15:31:11.655 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:33:37
2025-07-31 15:31:13.478 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:33:34
2025-07-31 15:31:15.319 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:33:32
2025-07-31 15:31:17.215 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:33:29
2025-07-31 15:31:17.988 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:31:18.035 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch480
2025-07-31 15:31:19.906 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 1.8, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:33:25
2025-07-31 15:31:21.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:33:22
2025-07-31 15:31:23.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 1.5, lr: 5.000e-04, size: 576, ETA: 0:33:19
2025-07-31 15:31:25.405 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:33:17
2025-07-31 15:31:27.398 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.098s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:33:14
2025-07-31 15:31:29.260 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:33:11
2025-07-31 15:31:30.076 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:31:36.565 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:31:37.241 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:31:37.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6182
2025-07-31 15:31:37.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5790
2025-07-31 15:31:37.776 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4006
2025-07-31 15:31:37.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5326
2025-07-31 15:31:37.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:31:37.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:31:37.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.618
2025-07-31 15:31:37.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.579
2025-07-31 15:31:37.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.401
2025-07-31 15:31:37.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.533
2025-07-31 15:31:37.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:31:37.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:31:37.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:31:37.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:31:37.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:31:37.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:31:37.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:31:37.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:31:37.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:31:38.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:31:38.892 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:31:39.414 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:31:40.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:31:40.539 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:31:41.050 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:31:41.566 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:31:42.078 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:31:42.645 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:31:42.645 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:31:42.646 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:31:42.646 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:31:42.654 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.48 ms, Average NMS time: 0.97 ms, Average inference time: 2.45 ms

2025-07-31 15:31:42.654 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:31:42.689 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:31:42.733 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch481
2025-07-31 15:31:44.559 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:33:07
2025-07-31 15:31:46.384 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:33:04
2025-07-31 15:31:48.204 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:33:01
2025-07-31 15:31:50.074 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:32:59
2025-07-31 15:31:51.891 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:32:56
2025-07-31 15:31:53.679 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:32:53
2025-07-31 15:31:54.475 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:31:54.514 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch482
2025-07-31 15:31:56.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:32:49
2025-07-31 15:31:58.086 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:32:46
2025-07-31 15:31:59.893 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:32:44
2025-07-31 15:32:01.726 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:32:41
2025-07-31 15:32:03.555 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 4.7, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:32:38
2025-07-31 15:32:05.410 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 11.4, iou_loss: 3.6, l1_loss: 1.0, conf_loss: 5.8, cls_loss: 1.0, lr: 5.000e-04, size: 352, ETA: 0:32:35
2025-07-31 15:32:06.191 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:32:06.233 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch483
2025-07-31 15:32:08.036 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:32:31
2025-07-31 15:32:09.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:32:29
2025-07-31 15:32:11.576 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:32:26
2025-07-31 15:32:13.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 9.6, iou_loss: 3.2, l1_loss: 0.9, conf_loss: 4.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:32:23
2025-07-31 15:32:15.345 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.8, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:32:20
2025-07-31 15:32:17.081 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:32:17
2025-07-31 15:32:17.851 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:32:17.896 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch484
2025-07-31 15:32:19.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.4, l1_loss: 0.3, conf_loss: 1.5, cls_loss: 0.4, lr: 5.000e-04, size: 480, ETA: 0:32:13
2025-07-31 15:32:21.471 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:32:11
2025-07-31 15:32:23.319 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:32:08
2025-07-31 15:32:25.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:32:05
2025-07-31 15:32:27.010 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:32:02
2025-07-31 15:32:28.871 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:32:00
2025-07-31 15:32:29.697 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:32:29.749 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch485
2025-07-31 15:32:31.531 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.1, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:31:56
2025-07-31 15:32:33.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:31:53
2025-07-31 15:32:35.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:31:50
2025-07-31 15:32:36.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:31:47
2025-07-31 15:32:38.772 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:31:45
2025-07-31 15:32:40.574 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.9, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:31:42
2025-07-31 15:32:41.333 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:32:47.945 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:32:48.586 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:32:48.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6141
2025-07-31 15:32:49.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4712
2025-07-31 15:32:49.075 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4106
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4986
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.614
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.471
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.411
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.499
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:32:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:32:49.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:32:49.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:32:49.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:32:49.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:32:49.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:32:49.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:32:49.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:32:50.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:32:50.672 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:32:51.160 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:32:51.702 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:32:52.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:32:52.765 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:32:53.246 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:32:53.734 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:32:53.735 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:32:53.735 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-31 15:32:53.735 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:32:53.744 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.93 ms, Average inference time: 2.35 ms

2025-07-31 15:32:53.744 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:32:53.774 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:32:53.809 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch486
2025-07-31 15:32:55.583 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:31:38
2025-07-31 15:32:57.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:31:35
2025-07-31 15:32:59.319 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:31:32
2025-07-31 15:33:01.126 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:31:30
2025-07-31 15:33:03.019 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:31:27
2025-07-31 15:33:04.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:31:24
2025-07-31 15:33:05.694 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:33:05.739 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch487
2025-07-31 15:33:07.483 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:31:20
2025-07-31 15:33:09.318 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:31:17
2025-07-31 15:33:11.108 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:31:15
2025-07-31 15:33:12.915 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:31:12
2025-07-31 15:33:14.841 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:31:09
2025-07-31 15:33:16.680 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:31:06
2025-07-31 15:33:17.486 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:33:17.538 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch488
2025-07-31 15:33:19.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:31:02
2025-07-31 15:33:21.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:31:00
2025-07-31 15:33:23.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.2, l1_loss: 1.3, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:30:57
2025-07-31 15:33:24.972 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:30:54
2025-07-31 15:33:26.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.006s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:30:52
2025-07-31 15:33:28.689 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:30:49
2025-07-31 15:33:29.546 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:33:29.605 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch489
2025-07-31 15:33:31.318 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:30:45
2025-07-31 15:33:33.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:30:42
2025-07-31 15:33:34.959 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:30:39
2025-07-31 15:33:36.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:30:37
2025-07-31 15:33:38.559 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:30:34
2025-07-31 15:33:40.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:30:31
2025-07-31 15:33:41.282 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:33:41.323 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch490
2025-07-31 15:33:43.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:30:27
2025-07-31 15:33:44.873 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.2, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.4, lr: 5.000e-04, size: 448, ETA: 0:30:24
2025-07-31 15:33:46.692 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:30:22
2025-07-31 15:33:48.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:30:19
2025-07-31 15:33:50.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:30:16
2025-07-31 15:33:52.051 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 3.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:30:13
2025-07-31 15:33:52.935 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:33:59.453 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:34:00.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:34:00.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6252
2025-07-31 15:34:00.886 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5705
2025-07-31 15:34:00.961 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3891
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5283
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.625
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.570
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.389
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.528
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:34:00.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:34:00.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:34:00.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:34:00.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:34:00.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:34:00.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:34:00.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:34:01.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:34:02.241 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:34:02.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:34:03.613 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:34:04.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:34:04.990 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:34:05.639 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:34:06.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:34:06.995 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:34:06.996 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:34:06.996 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:34:06.996 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:34:07.004 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 0.93 ms, Average inference time: 2.35 ms

2025-07-31 15:34:07.006 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:34:07.042 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:34:07.106 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch491
2025-07-31 15:34:08.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 1.7, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:30:09
2025-07-31 15:34:10.744 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:30:07
2025-07-31 15:34:12.616 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:30:04
2025-07-31 15:34:14.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:30:01
2025-07-31 15:34:16.268 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:29:59
2025-07-31 15:34:18.146 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:29:56
2025-07-31 15:34:18.959 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:34:19.002 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch492
2025-07-31 15:34:20.796 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:29:52
2025-07-31 15:34:22.649 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:29:49
2025-07-31 15:34:24.496 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:29:46
2025-07-31 15:34:26.362 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.5, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:29:44
2025-07-31 15:34:28.254 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 5.0, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:29:41
2025-07-31 15:34:30.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.4, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:29:38
2025-07-31 15:34:30.823 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:34:30.893 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch493
2025-07-31 15:34:32.634 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:29:34
2025-07-31 15:34:34.498 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:29:32
2025-07-31 15:34:36.328 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:29:29
2025-07-31 15:34:38.189 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.3, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.4, lr: 5.000e-04, size: 576, ETA: 0:29:26
2025-07-31 15:34:40.017 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:29:23
2025-07-31 15:34:41.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:29:21
2025-07-31 15:34:42.713 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:34:42.755 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch494
2025-07-31 15:34:44.521 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:29:17
2025-07-31 15:34:46.343 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:29:14
2025-07-31 15:34:48.179 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:29:11
2025-07-31 15:34:49.956 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:29:09
2025-07-31 15:34:51.753 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 8.3, iou_loss: 2.4, l1_loss: 1.3, conf_loss: 3.3, cls_loss: 1.3, lr: 5.000e-04, size: 512, ETA: 0:29:06
2025-07-31 15:34:53.508 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:29:03
2025-07-31 15:34:54.320 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:34:54.389 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch495
2025-07-31 15:34:56.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 9.0, iou_loss: 1.5, l1_loss: 0.8, conf_loss: 4.8, cls_loss: 2.0, lr: 5.000e-04, size: 320, ETA: 0:28:59
2025-07-31 15:34:57.992 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:28:56
2025-07-31 15:34:59.814 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:28:54
2025-07-31 15:35:01.582 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:28:51
2025-07-31 15:35:03.442 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:28:48
2025-07-31 15:35:05.256 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:28:46
2025-07-31 15:35:06.061 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:35:12.663 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:35:13.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:35:13.735 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5776
2025-07-31 15:35:13.874 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5072
2025-07-31 15:35:13.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3378
2025-07-31 15:35:13.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4742
2025-07-31 15:35:13.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:35:13.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.578
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.507
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.338
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.474
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:35:13.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:35:13.905 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:35:13.905 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:35:14.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:35:14.924 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:35:15.439 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:35:15.985 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:35:16.496 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:35:17.005 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:35:17.508 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:35:18.020 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:35:18.544 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:35:18.545 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-31 15:35:18.545 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-31 15:35:18.545 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:35:18.552 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.88 ms, Average inference time: 2.32 ms

2025-07-31 15:35:18.553 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:35:18.582 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:35:18.624 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch496
2025-07-31 15:35:20.493 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:28:42
2025-07-31 15:35:22.400 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:28:39
2025-07-31 15:35:24.260 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:28:36
2025-07-31 15:35:26.065 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:28:34
2025-07-31 15:35:28.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.094s, data_time: 0.006s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:28:31
2025-07-31 15:35:29.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:28:28
2025-07-31 15:35:30.657 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:35:30.703 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch497
2025-07-31 15:35:32.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:28:24
2025-07-31 15:35:34.457 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:28:22
2025-07-31 15:35:36.267 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:28:19
2025-07-31 15:35:38.082 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:28:16
2025-07-31 15:35:40.010 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.1, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.4, lr: 5.000e-04, size: 480, ETA: 0:28:13
2025-07-31 15:35:41.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:28:11
2025-07-31 15:35:42.601 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:35:42.671 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch498
2025-07-31 15:35:44.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:28:07
2025-07-31 15:35:46.228 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.2, l1_loss: 0.4, conf_loss: 1.7, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:28:04
2025-07-31 15:35:48.052 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:28:01
2025-07-31 15:35:49.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:27:59
2025-07-31 15:35:51.828 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:27:56
2025-07-31 15:35:53.686 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 3.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:27:53
2025-07-31 15:35:54.560 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:35:54.599 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch499
2025-07-31 15:35:56.393 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:27:49
2025-07-31 15:35:58.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:27:47
2025-07-31 15:36:00.097 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 3.1, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:27:44
2025-07-31 15:36:01.972 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 4.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:27:41
2025-07-31 15:36:03.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 3.8, iou_loss: 2.0, l1_loss: 0.4, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:27:39
2025-07-31 15:36:05.562 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 9.3, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 9.3, cls_loss: 0.0, lr: 5.000e-04, size: 384, ETA: 0:27:36
2025-07-31 15:36:06.393 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:36:06.434 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch500
2025-07-31 15:36:08.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.3, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:27:32
2025-07-31 15:36:10.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:27:29
2025-07-31 15:36:11.771 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.4, lr: 5.000e-04, size: 256, ETA: 0:27:27
2025-07-31 15:36:13.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 1.3, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:27:24
2025-07-31 15:36:15.472 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 3.2, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:27:21
2025-07-31 15:36:17.306 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.4, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:27:18
2025-07-31 15:36:18.100 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:36:24.357 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:36:25.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:36:25.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6039
2025-07-31 15:36:25.658 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5589
2025-07-31 15:36:25.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4220
2025-07-31 15:36:25.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5283
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.604
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.559
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.422
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.528
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:36:25.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:36:25.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:36:25.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:36:25.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:36:25.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:36:25.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:36:26.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:36:26.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:36:27.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:36:28.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:36:28.617 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:36:29.180 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:36:29.776 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:36:30.336 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:36:30.905 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:36:30.905 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:36:30.905 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:36:30.905 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:36:30.912 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.43 ms, Average NMS time: 0.96 ms, Average inference time: 2.39 ms

2025-07-31 15:36:30.913 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:36:30.935 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:36:30.966 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch501
2025-07-31 15:36:32.619 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:27:15
2025-07-31 15:36:34.406 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:27:12
2025-07-31 15:36:36.242 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:27:09
2025-07-31 15:36:37.968 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 1.4, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:27:06
2025-07-31 15:36:39.822 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 3.6, iou_loss: 1.3, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.4, lr: 5.000e-04, size: 352, ETA: 0:27:04
2025-07-31 15:36:41.653 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:27:01
2025-07-31 15:36:42.453 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:36:42.491 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch502
2025-07-31 15:36:44.224 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:26:57
2025-07-31 15:36:46.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.2, l1_loss: 1.4, conf_loss: 1.9, cls_loss: 1.3, lr: 5.000e-04, size: 512, ETA: 0:26:54
2025-07-31 15:36:47.840 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:26:52
2025-07-31 15:36:49.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:26:49
2025-07-31 15:36:51.605 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:26:46
2025-07-31 15:36:53.406 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 1.0, lr: 5.000e-04, size: 544, ETA: 0:26:44
2025-07-31 15:36:54.230 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:36:54.267 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch503
2025-07-31 15:36:56.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:26:40
2025-07-31 15:36:57.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 18.2, iou_loss: 4.3, l1_loss: 1.8, conf_loss: 11.4, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:26:37
2025-07-31 15:36:59.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 9.5, iou_loss: 2.8, l1_loss: 1.3, conf_loss: 4.5, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:26:34
2025-07-31 15:37:01.611 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:26:32
2025-07-31 15:37:03.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.007s, total_loss: 7.8, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:26:29
2025-07-31 15:37:05.357 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:26:26
2025-07-31 15:37:06.168 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:37:06.232 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch504
2025-07-31 15:37:08.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:26:23
2025-07-31 15:37:09.875 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:26:20
2025-07-31 15:37:11.686 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:26:17
2025-07-31 15:37:13.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:26:14
2025-07-31 15:37:15.366 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:26:12
2025-07-31 15:37:17.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:26:09
2025-07-31 15:37:18.038 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:37:18.088 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch505
2025-07-31 15:37:19.865 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:26:05
2025-07-31 15:37:21.684 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:26:03
2025-07-31 15:37:23.551 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:26:00
2025-07-31 15:37:25.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:25:57
2025-07-31 15:37:27.224 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.004s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:25:55
2025-07-31 15:37:29.144 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.2, l1_loss: 0.4, conf_loss: 1.6, cls_loss: 0.4, lr: 5.000e-04, size: 256, ETA: 0:25:52
2025-07-31 15:37:29.956 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:37:36.310 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:37:37.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:37:37.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6181
2025-07-31 15:37:37.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5674
2025-07-31 15:37:38.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4211
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5355
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.618
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.567
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.421
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.536
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:37:38.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:37:38.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:37:38.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:37:38.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:37:38.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:37:38.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:37:38.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:37:38.735 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:37:39.569 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:37:40.408 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:37:41.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:37:41.964 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:37:42.668 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:37:43.458 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:37:44.170 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:37:44.950 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:37:44.950 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-07-31 15:37:44.950 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-07-31 15:37:44.951 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:37:44.960 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.49 ms, Average NMS time: 0.97 ms, Average inference time: 2.46 ms

2025-07-31 15:37:44.960 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:37:44.989 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:37:45.023 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch506
2025-07-31 15:37:46.811 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 2.7, iou_loss: 1.1, l1_loss: 0.4, conf_loss: 0.9, cls_loss: 0.4, lr: 5.000e-04, size: 448, ETA: 0:25:48
2025-07-31 15:37:48.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:25:45
2025-07-31 15:37:50.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:25:43
2025-07-31 15:37:52.254 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:25:40
2025-07-31 15:37:54.187 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:25:37
2025-07-31 15:37:55.992 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:25:35
2025-07-31 15:37:56.804 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:37:56.851 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch507
2025-07-31 15:37:58.658 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:25:31
2025-07-31 15:38:00.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:25:28
2025-07-31 15:38:02.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:25:25
2025-07-31 15:38:04.183 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:25:23
2025-07-31 15:38:05.994 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:25:20
2025-07-31 15:38:07.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:25:17
2025-07-31 15:38:08.678 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:38:08.726 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch508
2025-07-31 15:38:10.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 1.4, cls_loss: 0.4, lr: 5.000e-04, size: 320, ETA: 0:25:14
2025-07-31 15:38:12.385 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:25:11
2025-07-31 15:38:14.237 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.4, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 3.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:25:08
2025-07-31 15:38:16.130 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:25:06
2025-07-31 15:38:17.929 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:25:03
2025-07-31 15:38:19.769 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.3, l1_loss: 1.2, conf_loss: 3.4, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:25:00
2025-07-31 15:38:20.587 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:38:20.636 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch509
2025-07-31 15:38:22.461 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:24:56
2025-07-31 15:38:24.296 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.8, l1_loss: 1.4, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:24:54
2025-07-31 15:38:26.163 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:24:51
2025-07-31 15:38:27.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:24:48
2025-07-31 15:38:29.782 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:24:46
2025-07-31 15:38:31.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:24:43
2025-07-31 15:38:32.443 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:38:32.489 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch510
2025-07-31 15:38:34.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 12.4, iou_loss: 3.5, l1_loss: 0.9, conf_loss: 7.0, cls_loss: 1.0, lr: 5.000e-04, size: 256, ETA: 0:24:39
2025-07-31 15:38:36.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.000e-04, size: 320, ETA: 0:24:37
2025-07-31 15:38:37.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:24:34
2025-07-31 15:38:39.714 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:24:31
2025-07-31 15:38:41.633 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:24:29
2025-07-31 15:38:43.434 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:24:26
2025-07-31 15:38:44.230 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:38:50.525 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:38:51.420 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:38:51.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6266
2025-07-31 15:38:51.995 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5620
2025-07-31 15:38:52.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4187
2025-07-31 15:38:52.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5358
2025-07-31 15:38:52.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:38:52.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:38:52.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.627
2025-07-31 15:38:52.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.562
2025-07-31 15:38:52.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.419
2025-07-31 15:38:52.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.536
2025-07-31 15:38:52.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:38:52.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:38:52.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:38:52.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:38:52.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:38:52.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:38:52.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:38:52.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:38:52.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:38:52.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:38:53.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:38:53.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:38:54.561 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:38:55.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:38:55.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:38:56.393 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:38:56.995 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:38:57.647 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:38:57.647 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:38:57.647 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-07-31 15:38:57.647 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:38:57.656 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 0.94 ms, Average inference time: 2.41 ms

2025-07-31 15:38:57.657 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:38:57.698 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:38:57.745 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch511
2025-07-31 15:38:59.501 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:24:22
2025-07-31 15:39:01.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:24:19
2025-07-31 15:39:03.194 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:24:17
2025-07-31 15:39:05.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.004s, total_loss: 8.6, iou_loss: 2.7, l1_loss: 1.5, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:24:14
2025-07-31 15:39:06.965 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:24:11
2025-07-31 15:39:08.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:24:09
2025-07-31 15:39:09.579 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:39:09.642 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch512
2025-07-31 15:39:11.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:24:05
2025-07-31 15:39:13.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:24:02
2025-07-31 15:39:14.987 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 3.3, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:24:00
2025-07-31 15:39:16.863 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:23:57
2025-07-31 15:39:18.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:23:54
2025-07-31 15:39:20.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:23:52
2025-07-31 15:39:21.345 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:39:21.392 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch513
2025-07-31 15:39:23.267 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:23:48
2025-07-31 15:39:25.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 1.4, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:23:45
2025-07-31 15:39:26.887 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 16.2, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 16.2, cls_loss: 0.0, lr: 5.000e-04, size: 288, ETA: 0:23:43
2025-07-31 15:39:28.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.095s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:23:40
2025-07-31 15:39:30.735 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:23:37
2025-07-31 15:39:32.589 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:23:35
2025-07-31 15:39:33.356 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:39:33.420 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch514
2025-07-31 15:39:35.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:23:31
2025-07-31 15:39:37.002 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:23:28
2025-07-31 15:39:38.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:23:25
2025-07-31 15:39:40.631 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 3.3, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:23:23
2025-07-31 15:39:42.427 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:23:20
2025-07-31 15:39:44.320 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:23:17
2025-07-31 15:39:45.097 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:39:45.151 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch515
2025-07-31 15:39:46.943 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:23:14
2025-07-31 15:39:48.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.1, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:23:11
2025-07-31 15:39:50.523 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:23:08
2025-07-31 15:39:52.426 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:23:06
2025-07-31 15:39:54.226 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.3, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:23:03
2025-07-31 15:39:56.087 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:23:00
2025-07-31 15:39:56.920 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:40:03.479 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:40:04.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:40:05.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6263
2025-07-31 15:40:05.331 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5676
2025-07-31 15:40:05.378 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3999
2025-07-31 15:40:05.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5313
2025-07-31 15:40:05.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:40:05.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:40:05.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.626
2025-07-31 15:40:05.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.568
2025-07-31 15:40:05.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.400
2025-07-31 15:40:05.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.531
2025-07-31 15:40:05.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:40:05.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:40:05.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:40:05.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:40:05.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:40:05.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:40:05.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:40:05.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:40:05.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:40:06.111 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:40:06.886 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:40:07.607 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:40:08.332 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:40:09.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:40:09.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:40:10.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:40:11.307 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:40:12.030 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:40:12.031 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-07-31 15:40:12.031 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:40:12.031 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:40:12.040 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.97 ms, Average inference time: 2.41 ms

2025-07-31 15:40:12.041 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:40:12.075 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:40:12.115 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch516
2025-07-31 15:40:13.898 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:22:57
2025-07-31 15:40:15.705 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:22:54
2025-07-31 15:40:17.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:22:51
2025-07-31 15:40:19.396 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:22:49
2025-07-31 15:40:21.214 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:22:46
2025-07-31 15:40:23.172 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.095s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:22:43
2025-07-31 15:40:24.009 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:40:24.077 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch517
2025-07-31 15:40:25.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:22:40
2025-07-31 15:40:27.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:22:37
2025-07-31 15:40:29.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:22:34
2025-07-31 15:40:31.348 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.007s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:22:32
2025-07-31 15:40:33.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:22:29
2025-07-31 15:40:35.007 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:22:26
2025-07-31 15:40:35.820 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:40:35.867 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch518
2025-07-31 15:40:37.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 3.6, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:22:23
2025-07-31 15:40:39.598 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.2, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:22:20
2025-07-31 15:40:41.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:22:17
2025-07-31 15:40:43.193 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:22:15
2025-07-31 15:40:44.994 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:22:12
2025-07-31 15:40:46.806 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:22:09
2025-07-31 15:40:47.633 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:40:47.698 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch519
2025-07-31 15:40:49.491 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:22:06
2025-07-31 15:40:51.316 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:22:03
2025-07-31 15:40:53.145 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:22:00
2025-07-31 15:40:55.006 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:21:58
2025-07-31 15:40:56.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:21:55
2025-07-31 15:40:58.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:21:52
2025-07-31 15:40:59.578 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:40:59.618 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch520
2025-07-31 15:41:01.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:21:49
2025-07-31 15:41:03.286 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:21:46
2025-07-31 15:41:05.170 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:21:43
2025-07-31 15:41:07.074 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 8.1, iou_loss: 1.9, l1_loss: 1.3, conf_loss: 3.4, cls_loss: 1.6, lr: 5.000e-04, size: 576, ETA: 0:21:41
2025-07-31 15:41:08.966 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:21:38
2025-07-31 15:41:10.787 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:21:36
2025-07-31 15:41:11.567 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:41:18.048 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:41:19.196 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:41:19.731 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6207
2025-07-31 15:41:19.854 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5704
2025-07-31 15:41:19.949 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4070
2025-07-31 15:41:19.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5327
2025-07-31 15:41:19.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:41:19.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:41:19.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.621
2025-07-31 15:41:19.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.570
2025-07-31 15:41:19.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.407
2025-07-31 15:41:19.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.533
2025-07-31 15:41:19.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:41:19.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:41:19.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:41:19.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:41:19.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:41:19.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:41:19.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:41:19.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:41:19.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:41:20.620 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:41:21.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:41:22.036 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:41:22.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:41:23.337 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:41:23.999 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:41:24.720 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:41:25.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:41:26.040 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:41:26.040 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:41:26.040 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:41:26.040 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:41:26.049 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 0.95 ms, Average inference time: 2.40 ms

2025-07-31 15:41:26.050 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:41:26.081 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:41:26.119 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch521
2025-07-31 15:41:27.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:21:32
2025-07-31 15:41:29.771 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 1.0, lr: 5.000e-04, size: 320, ETA: 0:21:29
2025-07-31 15:41:31.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:21:27
2025-07-31 15:41:33.497 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 4.0, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:21:24
2025-07-31 15:41:35.312 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:21:21
2025-07-31 15:41:37.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:21:19
2025-07-31 15:41:37.946 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:41:38.009 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch522
2025-07-31 15:41:39.942 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:21:15
2025-07-31 15:41:41.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:21:12
2025-07-31 15:41:43.582 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:21:10
2025-07-31 15:41:45.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:21:07
2025-07-31 15:41:47.254 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:21:04
2025-07-31 15:41:49.117 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.4, lr: 5.000e-04, size: 576, ETA: 0:21:02
2025-07-31 15:41:49.994 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:41:50.036 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch523
2025-07-31 15:41:51.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:20:58
2025-07-31 15:41:53.620 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:20:55
2025-07-31 15:41:55.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:20:53
2025-07-31 15:41:57.339 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.006s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:20:50
2025-07-31 15:41:59.203 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 1.2, lr: 5.000e-04, size: 256, ETA: 0:20:48
2025-07-31 15:42:01.000 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:20:45
2025-07-31 15:42:01.880 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:42:01.919 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch524
2025-07-31 15:42:03.654 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:20:41
2025-07-31 15:42:05.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:20:39
2025-07-31 15:42:07.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:20:36
2025-07-31 15:42:09.114 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 3.6, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:20:33
2025-07-31 15:42:10.942 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:20:31
2025-07-31 15:42:12.874 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:20:28
2025-07-31 15:42:13.673 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:42:13.723 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch525
2025-07-31 15:42:15.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:20:24
2025-07-31 15:42:17.235 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:20:22
2025-07-31 15:42:19.074 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:20:19
2025-07-31 15:42:20.945 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 6.8, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:20:16
2025-07-31 15:42:22.777 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:20:14
2025-07-31 15:42:24.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:20:11
2025-07-31 15:42:25.511 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:42:31.904 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:42:32.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:42:33.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5975
2025-07-31 15:42:33.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5627
2025-07-31 15:42:33.355 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3742
2025-07-31 15:42:33.355 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5115
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.597
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.563
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.374
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.511
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:42:33.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:42:33.357 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:42:33.357 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:42:33.357 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:42:33.357 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:42:33.357 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:42:34.037 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:42:34.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:42:35.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:42:35.868 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:42:36.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:42:37.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:42:37.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:42:38.346 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:42:38.956 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:42:38.957 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:42:38.957 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-31 15:42:38.957 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:42:38.965 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 0.98 ms, Average inference time: 2.43 ms

2025-07-31 15:42:38.968 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:42:39.004 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:42:39.050 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch526
2025-07-31 15:42:40.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:20:07
2025-07-31 15:42:42.600 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 1.5, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:20:05
2025-07-31 15:42:44.525 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:20:02
2025-07-31 15:42:46.317 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:20:00
2025-07-31 15:42:48.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:19:57
2025-07-31 15:42:50.125 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:19:54
2025-07-31 15:42:50.946 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:42:50.996 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch527
2025-07-31 15:42:52.829 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.4, lr: 5.000e-04, size: 288, ETA: 0:19:51
2025-07-31 15:42:54.620 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:19:48
2025-07-31 15:42:56.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:19:45
2025-07-31 15:42:58.426 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:19:43
2025-07-31 15:43:00.269 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:19:40
2025-07-31 15:43:02.203 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:19:38
2025-07-31 15:43:03.028 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:43:03.068 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch528
2025-07-31 15:43:04.962 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 14.2, iou_loss: 4.2, l1_loss: 1.6, conf_loss: 7.4, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:19:34
2025-07-31 15:43:06.900 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:19:31
2025-07-31 15:43:08.731 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:19:29
2025-07-31 15:43:10.589 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:19:26
2025-07-31 15:43:12.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:19:24
2025-07-31 15:43:14.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.1, l1_loss: 0.3, conf_loss: 2.0, cls_loss: 0.4, lr: 5.000e-04, size: 448, ETA: 0:19:21
2025-07-31 15:43:15.099 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:43:15.165 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch529
2025-07-31 15:43:16.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.001s, total_loss: 4.4, iou_loss: 2.1, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:19:17
2025-07-31 15:43:18.826 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:19:15
2025-07-31 15:43:20.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:19:12
2025-07-31 15:43:22.583 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.006s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:19:09
2025-07-31 15:43:24.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:19:07
2025-07-31 15:43:26.175 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:19:04
2025-07-31 15:43:26.987 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:43:27.028 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch530
2025-07-31 15:43:28.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:19:00
2025-07-31 15:43:30.621 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 1.3, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:18:58
2025-07-31 15:43:32.432 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 1.5, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:18:55
2025-07-31 15:43:34.325 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:18:53
2025-07-31 15:43:36.115 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.3, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:18:50
2025-07-31 15:43:37.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:18:47
2025-07-31 15:43:38.732 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:43:45.179 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:43:46.015 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:43:46.520 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6241
2025-07-31 15:43:46.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5679
2025-07-31 15:43:46.710 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4283
2025-07-31 15:43:46.711 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5401
2025-07-31 15:43:46.711 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:43:46.711 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.624
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.568
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.428
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.540
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:43:46.712 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:43:46.713 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:43:47.350 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:43:47.991 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:43:48.660 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:43:49.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:43:50.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:43:50.720 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:43:51.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:43:52.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:43:52.715 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:43:52.715 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:43:52.715 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-07-31 15:43:52.715 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:43:52.724 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 0.99 ms, Average inference time: 2.44 ms

2025-07-31 15:43:52.725 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:43:52.751 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:43:52.793 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch531
2025-07-31 15:43:54.687 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:18:44
2025-07-31 15:43:56.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:18:41
2025-07-31 15:43:58.295 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:18:39
2025-07-31 15:44:00.202 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:18:36
2025-07-31 15:44:02.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:18:33
2025-07-31 15:44:03.772 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:18:31
2025-07-31 15:44:04.579 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:44:04.621 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch532
2025-07-31 15:44:06.484 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:18:27
2025-07-31 15:44:08.286 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:18:24
2025-07-31 15:44:10.124 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:18:22
2025-07-31 15:44:12.000 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:18:19
2025-07-31 15:44:13.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:18:17
2025-07-31 15:44:15.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:18:14
2025-07-31 15:44:16.449 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:44:16.497 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch533
2025-07-31 15:44:18.331 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:18:10
2025-07-31 15:44:20.181 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:18:08
2025-07-31 15:44:22.040 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:18:05
2025-07-31 15:44:23.983 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.003s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:18:03
2025-07-31 15:44:25.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:18:00
2025-07-31 15:44:27.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:17:57
2025-07-31 15:44:28.330 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:44:28.367 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch534
2025-07-31 15:44:30.237 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:17:54
2025-07-31 15:44:32.045 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:17:51
2025-07-31 15:44:33.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:17:49
2025-07-31 15:44:35.745 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:17:46
2025-07-31 15:44:37.527 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.3, iou_loss: 1.3, l1_loss: 0.3, conf_loss: 1.3, cls_loss: 0.4, lr: 5.000e-04, size: 480, ETA: 0:17:43
2025-07-31 15:44:39.374 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:17:41
2025-07-31 15:44:40.178 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:44:40.223 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch535
2025-07-31 15:44:41.936 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:17:37
2025-07-31 15:44:43.735 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:17:34
2025-07-31 15:44:45.555 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:17:32
2025-07-31 15:44:47.453 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:17:29
2025-07-31 15:44:49.335 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:17:27
2025-07-31 15:44:51.136 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:17:24
2025-07-31 15:44:51.969 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:44:58.503 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:44:59.355 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:44:59.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6242
2025-07-31 15:44:59.980 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5800
2025-07-31 15:45:00.015 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4239
2025-07-31 15:45:00.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5427
2025-07-31 15:45:00.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:45:00.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:45:00.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.624
2025-07-31 15:45:00.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.580
2025-07-31 15:45:00.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.424
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.543
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:45:00.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:45:00.708 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:45:01.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:45:02.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:45:02.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:45:03.414 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:45:04.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:45:04.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:45:05.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:45:06.191 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:45:06.191 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-07-31 15:45:06.191 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-07-31 15:45:06.191 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:45:06.200 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.95 ms, Average inference time: 2.38 ms

2025-07-31 15:45:06.201 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:45:06.232 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:45:06.265 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch536
2025-07-31 15:45:08.006 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:17:20
2025-07-31 15:45:09.843 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:17:18
2025-07-31 15:45:11.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:17:15
2025-07-31 15:45:13.654 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 3.6, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:17:13
2025-07-31 15:45:15.449 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:17:10
2025-07-31 15:45:17.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 1.0, lr: 5.000e-04, size: 512, ETA: 0:17:08
2025-07-31 15:45:18.171 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:45:18.222 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch537
2025-07-31 15:45:20.034 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:17:04
2025-07-31 15:45:21.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:17:01
2025-07-31 15:45:23.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:16:59
2025-07-31 15:45:25.567 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 4.1, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:16:56
2025-07-31 15:45:27.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:16:53
2025-07-31 15:45:29.401 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:16:51
2025-07-31 15:45:30.173 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:45:30.234 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch538
2025-07-31 15:45:32.021 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:16:47
2025-07-31 15:45:33.850 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:16:45
2025-07-31 15:45:35.685 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:16:42
2025-07-31 15:45:37.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 4.3, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:16:39
2025-07-31 15:45:39.317 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:16:37
2025-07-31 15:45:41.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:16:34
2025-07-31 15:45:41.955 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:45:42.009 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch539
2025-07-31 15:45:43.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:16:31
2025-07-31 15:45:45.559 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:16:28
2025-07-31 15:45:47.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:16:25
2025-07-31 15:45:49.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:16:23
2025-07-31 15:45:51.106 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:16:20
2025-07-31 15:45:52.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:16:18
2025-07-31 15:45:53.786 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:45:53.838 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch540
2025-07-31 15:45:55.652 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:16:14
2025-07-31 15:45:57.507 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.3, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:16:12
2025-07-31 15:45:59.282 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:16:09
2025-07-31 15:46:01.246 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.095s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:16:06
2025-07-31 15:46:03.042 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:16:04
2025-07-31 15:46:04.790 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:16:01
2025-07-31 15:46:05.638 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:46:12.119 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:46:13.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:46:13.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6091
2025-07-31 15:46:13.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5579
2025-07-31 15:46:13.785 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3760
2025-07-31 15:46:13.786 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5143
2025-07-31 15:46:13.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:46:13.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:46:13.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.609
2025-07-31 15:46:13.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.558
2025-07-31 15:46:13.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.376
2025-07-31 15:46:13.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.514
2025-07-31 15:46:13.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:46:13.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:46:13.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:46:13.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:46:13.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:46:13.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:46:13.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:46:13.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:46:13.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:46:14.561 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:46:15.410 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:46:16.113 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:46:16.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:46:17.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:46:18.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:46:19.051 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:46:19.767 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:46:20.526 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:46:20.526 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:46:20.526 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-31 15:46:20.527 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:46:20.535 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 0.98 ms, Average inference time: 2.45 ms

2025-07-31 15:46:20.536 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:46:20.563 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:46:20.595 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch541
2025-07-31 15:46:22.345 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:15:58
2025-07-31 15:46:24.135 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:15:55
2025-07-31 15:46:26.125 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.095s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:15:52
2025-07-31 15:46:27.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:15:50
2025-07-31 15:46:29.783 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:15:47
2025-07-31 15:46:31.602 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:15:45
2025-07-31 15:46:32.447 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:46:32.493 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch542
2025-07-31 15:46:34.315 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:15:41
2025-07-31 15:46:36.207 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:15:38
2025-07-31 15:46:38.018 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 3.0, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.4, lr: 5.000e-04, size: 448, ETA: 0:15:36
2025-07-31 15:46:39.806 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:15:33
2025-07-31 15:46:41.586 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:15:31
2025-07-31 15:46:43.384 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.2, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:15:28
2025-07-31 15:46:44.178 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:46:44.217 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch543
2025-07-31 15:46:45.995 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:15:25
2025-07-31 15:46:47.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:15:22
2025-07-31 15:46:49.681 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 3.8, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:15:19
2025-07-31 15:46:51.470 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:15:17
2025-07-31 15:46:53.280 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.3, cls_loss: 0.4, lr: 5.000e-04, size: 352, ETA: 0:15:14
2025-07-31 15:46:55.142 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:15:12
2025-07-31 15:46:55.923 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:46:55.975 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch544
2025-07-31 15:46:57.808 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:15:08
2025-07-31 15:46:59.649 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.7, l1_loss: 1.4, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:15:06
2025-07-31 15:47:01.538 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:15:03
2025-07-31 15:47:03.397 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:15:00
2025-07-31 15:47:05.186 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:14:58
2025-07-31 15:47:07.045 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 1.1, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:14:55
2025-07-31 15:47:07.876 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:47:07.915 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch545
2025-07-31 15:47:09.687 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.4, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:14:52
2025-07-31 15:47:11.546 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:14:49
2025-07-31 15:47:13.458 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:14:47
2025-07-31 15:47:15.343 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:14:44
2025-07-31 15:47:17.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:14:41
2025-07-31 15:47:18.965 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:14:39
2025-07-31 15:47:19.781 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:47:26.357 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:47:27.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:47:27.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5770
2025-07-31 15:47:27.718 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5130
2025-07-31 15:47:27.751 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3624
2025-07-31 15:47:27.751 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4841
2025-07-31 15:47:27.751 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.577
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.513
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.362
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.484
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:47:27.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:47:27.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:47:27.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:47:27.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:47:27.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:47:28.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:47:29.026 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:47:29.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:47:30.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:47:30.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:47:31.591 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:47:32.193 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:47:32.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:47:33.458 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:47:33.459 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 15:47:33.459 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-31 15:47:33.459 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:47:33.468 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.41 ms, Average NMS time: 0.91 ms, Average inference time: 2.31 ms

2025-07-31 15:47:33.469 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:47:33.497 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:47:33.529 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch546
2025-07-31 15:47:35.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:14:35
2025-07-31 15:47:37.182 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 9.7, iou_loss: 3.5, l1_loss: 1.6, conf_loss: 3.8, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:14:33
2025-07-31 15:47:39.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.5, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:14:30
2025-07-31 15:47:40.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:14:28
2025-07-31 15:47:42.616 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:14:25
2025-07-31 15:47:44.421 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.7, l1_loss: 1.4, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:14:22
2025-07-31 15:47:45.239 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:47:45.279 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch547
2025-07-31 15:47:47.081 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 3.7, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:14:19
2025-07-31 15:47:48.880 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:14:16
2025-07-31 15:47:50.769 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:14:14
2025-07-31 15:47:52.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 2.7, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:14:11
2025-07-31 15:47:54.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 3.5, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:14:09
2025-07-31 15:47:56.316 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:14:06
2025-07-31 15:47:57.171 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:47:57.220 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch548
2025-07-31 15:47:59.003 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:14:02
2025-07-31 15:48:00.830 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:14:00
2025-07-31 15:48:02.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.1, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:13:57
2025-07-31 15:48:04.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:13:55
2025-07-31 15:48:06.273 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:13:52
2025-07-31 15:48:08.149 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:13:50
2025-07-31 15:48:08.968 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:48:09.029 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch549
2025-07-31 15:48:10.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:13:46
2025-07-31 15:48:12.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:13:43
2025-07-31 15:48:14.430 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 2.8, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 0.6, cls_loss: 0.4, lr: 5.000e-04, size: 352, ETA: 0:13:41
2025-07-31 15:48:16.207 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 3.7, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:13:38
2025-07-31 15:48:18.059 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 1.0, lr: 5.000e-04, size: 256, ETA: 0:13:36
2025-07-31 15:48:19.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 4.2, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:13:33
2025-07-31 15:48:20.787 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:48:20.839 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch550
2025-07-31 15:48:22.639 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:13:30
2025-07-31 15:48:24.406 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.7, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:13:27
2025-07-31 15:48:26.302 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:13:25
2025-07-31 15:48:28.145 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:13:22
2025-07-31 15:48:29.941 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:13:19
2025-07-31 15:48:31.762 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:13:17
2025-07-31 15:48:32.580 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:48:39.084 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:48:39.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:48:40.420 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6105
2025-07-31 15:48:40.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5676
2025-07-31 15:48:40.652 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3749
2025-07-31 15:48:40.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5177
2025-07-31 15:48:40.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:48:40.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:48:40.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.611
2025-07-31 15:48:40.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.568
2025-07-31 15:48:40.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.375
2025-07-31 15:48:40.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.518
2025-07-31 15:48:40.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:48:40.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:48:40.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:48:40.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:48:40.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:48:40.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:48:40.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:48:40.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:48:40.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:48:41.383 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:48:42.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:48:42.785 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:48:43.555 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:48:44.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:48:44.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:48:45.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:48:46.259 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:48:46.970 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:48:46.971 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:48:46.971 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:48:46.971 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:48:46.980 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 0.97 ms, Average inference time: 2.42 ms

2025-07-31 15:48:46.981 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:48:47.009 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:48:47.043 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch551
2025-07-31 15:48:48.746 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:13:13
2025-07-31 15:48:50.529 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:13:11
2025-07-31 15:48:52.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.096s, data_time: 0.003s, total_loss: 5.5, iou_loss: 1.8, l1_loss: 1.2, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:13:08
2025-07-31 15:48:54.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:13:06
2025-07-31 15:48:56.350 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.095s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:13:03
2025-07-31 15:48:58.236 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:13:01
2025-07-31 15:48:59.199 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:48:59.244 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch552
2025-07-31 15:49:01.015 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:12:57
2025-07-31 15:49:02.864 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.004s, total_loss: 7.9, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 1.1, lr: 5.000e-04, size: 448, ETA: 0:12:54
2025-07-31 15:49:04.876 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.096s, data_time: 0.004s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:12:52
2025-07-31 15:49:06.714 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:12:49
2025-07-31 15:49:08.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:12:47
2025-07-31 15:49:10.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:12:44
2025-07-31 15:49:11.343 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:49:11.390 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch553
2025-07-31 15:49:13.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:12:41
2025-07-31 15:49:15.073 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.004s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:12:38
2025-07-31 15:49:17.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.096s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:12:36
2025-07-31 15:49:18.896 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.092s, data_time: 0.005s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:12:33
2025-07-31 15:49:20.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:12:31
2025-07-31 15:49:22.644 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:12:28
2025-07-31 15:49:23.484 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:49:23.546 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch554
2025-07-31 15:49:25.348 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:12:24
2025-07-31 15:49:27.099 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:12:22
2025-07-31 15:49:28.863 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.004s, total_loss: 4.3, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:12:19
2025-07-31 15:49:30.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:12:17
2025-07-31 15:49:32.532 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:12:14
2025-07-31 15:49:34.330 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:12:12
2025-07-31 15:49:35.127 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:49:35.182 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch555
2025-07-31 15:49:36.910 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:12:08
2025-07-31 15:49:38.731 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:12:06
2025-07-31 15:49:40.583 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 3.8, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.5, cls_loss: 0.4, lr: 5.000e-04, size: 256, ETA: 0:12:03
2025-07-31 15:49:42.367 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 1.3, l1_loss: 0.8, conf_loss: 3.3, cls_loss: 0.4, lr: 5.000e-04, size: 544, ETA: 0:12:01
2025-07-31 15:49:44.282 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:11:58
2025-07-31 15:49:46.156 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:11:56
2025-07-31 15:49:46.953 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:49:53.445 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:49:54.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:49:54.937 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6187
2025-07-31 15:49:55.128 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5795
2025-07-31 15:49:55.170 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4309
2025-07-31 15:49:55.170 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5430
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.619
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.579
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.431
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.543
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:49:55.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:49:55.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:49:55.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:49:55.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:49:55.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:49:55.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:49:55.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:49:56.639 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:49:57.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:49:58.070 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:49:58.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:49:59.498 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:50:00.205 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:50:00.976 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:50:01.707 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:50:01.707 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:50:01.707 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-07-31 15:50:01.707 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:50:01.716 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.94 ms, Average inference time: 2.33 ms

2025-07-31 15:50:01.717 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:50:01.745 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:50:01.780 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch556
2025-07-31 15:50:03.532 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:11:52
2025-07-31 15:50:05.379 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:11:49
2025-07-31 15:50:07.254 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:11:47
2025-07-31 15:50:09.054 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:11:44
2025-07-31 15:50:10.888 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:11:42
2025-07-31 15:50:12.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:11:39
2025-07-31 15:50:13.548 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:50:13.614 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch557
2025-07-31 15:50:15.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:11:36
2025-07-31 15:50:17.257 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 3.8, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:11:33
2025-07-31 15:50:19.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:11:31
2025-07-31 15:50:20.960 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:11:28
2025-07-31 15:50:22.804 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:11:26
2025-07-31 15:50:24.611 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:11:23
2025-07-31 15:50:25.426 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:50:25.469 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch558
2025-07-31 15:50:27.312 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 9.2, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 4.6, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:11:19
2025-07-31 15:50:29.121 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.1, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:11:17
2025-07-31 15:50:31.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.007s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:11:14
2025-07-31 15:50:32.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:11:12
2025-07-31 15:50:34.725 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:11:09
2025-07-31 15:50:36.519 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 2.7, iou_loss: 1.3, l1_loss: 0.3, conf_loss: 0.6, cls_loss: 0.4, lr: 5.000e-04, size: 256, ETA: 0:11:07
2025-07-31 15:50:37.324 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:50:37.367 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch559
2025-07-31 15:50:39.156 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.2, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:11:03
2025-07-31 15:50:41.015 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 40/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 3.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:11:01
2025-07-31 15:50:42.894 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:10:58
2025-07-31 15:50:44.659 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:10:56
2025-07-31 15:50:46.486 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:10:53
2025-07-31 15:50:48.234 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:10:51
2025-07-31 15:50:49.056 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:50:49.131 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch560
2025-07-31 15:50:50.933 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:10:47
2025-07-31 15:50:52.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 40/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:10:45
2025-07-31 15:50:54.567 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:10:42
2025-07-31 15:50:56.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.4, l1_loss: 1.4, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:10:39
2025-07-31 15:50:58.229 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:10:37
2025-07-31 15:51:00.087 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:10:34
2025-07-31 15:51:00.891 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:51:07.296 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:51:08.708 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:51:09.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6016
2025-07-31 15:51:09.445 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4644
2025-07-31 15:51:09.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3905
2025-07-31 15:51:09.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4855
2025-07-31 15:51:09.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:51:09.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:51:09.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.602
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.464
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.390
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.485
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:51:09.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:51:09.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:51:09.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:51:10.321 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:51:11.142 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:51:11.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:51:12.695 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:51:13.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:51:14.319 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:51:15.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:51:15.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:51:16.720 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:51:16.721 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-31 15:51:16.721 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-07-31 15:51:16.722 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:51:16.737 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 0.95 ms, Average inference time: 2.42 ms

2025-07-31 15:51:16.738 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:51:16.773 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:51:16.819 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch561
2025-07-31 15:51:18.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:10:31
2025-07-31 15:51:20.373 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 1.0, lr: 5.000e-04, size: 448, ETA: 0:10:28
2025-07-31 15:51:22.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 7.5, iou_loss: 2.3, l1_loss: 1.3, conf_loss: 3.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:10:26
2025-07-31 15:51:24.060 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.2, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:10:23
2025-07-31 15:51:25.877 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:10:21
2025-07-31 15:51:27.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:10:18
2025-07-31 15:51:28.405 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:51:28.450 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch562
2025-07-31 15:51:30.212 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:10:15
2025-07-31 15:51:32.014 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:10:12
2025-07-31 15:51:33.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:10:10
2025-07-31 15:51:35.795 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:10:07
2025-07-31 15:51:37.652 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.1, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.4, lr: 5.000e-04, size: 448, ETA: 0:10:05
2025-07-31 15:51:39.425 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.3, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:10:02
2025-07-31 15:51:40.218 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:51:40.301 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch563
2025-07-31 15:51:42.048 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:09:59
2025-07-31 15:51:43.885 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:09:56
2025-07-31 15:51:45.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 7.6, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:09:54
2025-07-31 15:51:47.564 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:09:51
2025-07-31 15:51:49.343 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 9.2, iou_loss: 3.2, l1_loss: 1.3, conf_loss: 3.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:09:49
2025-07-31 15:51:51.109 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:09:46
2025-07-31 15:51:51.956 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:51:51.997 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch564
2025-07-31 15:51:53.816 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:09:42
2025-07-31 15:51:55.656 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:09:40
2025-07-31 15:51:57.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:09:37
2025-07-31 15:51:59.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:09:35
2025-07-31 15:52:01.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:09:32
2025-07-31 15:52:02.847 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:09:30
2025-07-31 15:52:03.704 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:52:03.744 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch565
2025-07-31 15:52:05.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:09:26
2025-07-31 15:52:07.349 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 40/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:09:24
2025-07-31 15:52:09.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 4.4, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:09:21
2025-07-31 15:52:11.066 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:09:19
2025-07-31 15:52:12.864 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.4, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:09:16
2025-07-31 15:52:14.639 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:09:14
2025-07-31 15:52:15.455 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:52:21.975 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:52:22.910 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:52:23.530 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6165
2025-07-31 15:52:23.635 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5452
2025-07-31 15:52:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3929
2025-07-31 15:52:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5182
2025-07-31 15:52:23.674 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:52:23.674 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:52:23.675 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.616
2025-07-31 15:52:23.675 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.545
2025-07-31 15:52:23.676 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.393
2025-07-31 15:52:23.676 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.518
2025-07-31 15:52:23.677 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:52:23.677 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:52:23.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:52:23.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:52:23.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:52:23.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:52:23.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:52:23.680 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:52:23.681 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:52:24.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:52:25.267 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:52:26.070 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:52:26.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:52:27.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:52:28.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:52:29.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:52:29.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:52:30.668 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:52:30.668 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-31 15:52:30.668 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:52:30.668 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:52:30.678 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 0.98 ms, Average inference time: 2.43 ms

2025-07-31 15:52:30.678 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:52:30.706 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:52:30.742 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch566
2025-07-31 15:52:32.474 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:09:10
2025-07-31 15:52:34.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:09:08
2025-07-31 15:52:36.232 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:09:05
2025-07-31 15:52:38.079 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:09:03
2025-07-31 15:52:39.988 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:09:00
2025-07-31 15:52:41.779 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:08:58
2025-07-31 15:52:42.577 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:52:42.657 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch567
2025-07-31 15:52:44.447 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:08:54
2025-07-31 15:52:46.276 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 9.0, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 4.3, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:08:52
2025-07-31 15:52:48.075 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:08:49
2025-07-31 15:52:49.948 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:08:47
2025-07-31 15:52:51.763 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:08:44
2025-07-31 15:52:53.485 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:08:42
2025-07-31 15:52:54.269 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:52:54.318 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch568
2025-07-31 15:52:56.143 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:08:38
2025-07-31 15:52:57.968 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:08:36
2025-07-31 15:52:59.884 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.007s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:08:33
2025-07-31 15:53:01.702 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:08:31
2025-07-31 15:53:03.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 6.4, iou_loss: 1.8, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:08:28
2025-07-31 15:53:05.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 3.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:08:26
2025-07-31 15:53:06.093 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:53:06.135 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch569
2025-07-31 15:53:07.932 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:08:22
2025-07-31 15:53:09.841 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:08:20
2025-07-31 15:53:11.728 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:08:17
2025-07-31 15:53:13.482 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.4, lr: 5.000e-04, size: 352, ETA: 0:08:15
2025-07-31 15:53:15.300 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:08:12
2025-07-31 15:53:17.127 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:08:10
2025-07-31 15:53:17.940 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:53:17.998 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch570
2025-07-31 15:53:19.798 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:08:06
2025-07-31 15:53:21.617 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 1.3, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:08:04
2025-07-31 15:53:23.472 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:08:01
2025-07-31 15:53:25.262 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:07:59
2025-07-31 15:53:26.983 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:07:56
2025-07-31 15:53:28.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:07:54
2025-07-31 15:53:29.696 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:53:36.051 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:53:36.872 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:53:37.371 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6184
2025-07-31 15:53:37.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5601
2025-07-31 15:53:37.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4089
2025-07-31 15:53:37.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5291
2025-07-31 15:53:37.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:53:37.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:53:37.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.618
2025-07-31 15:53:37.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.560
2025-07-31 15:53:37.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.409
2025-07-31 15:53:37.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.529
2025-07-31 15:53:37.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:53:37.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:53:37.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:53:37.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:53:37.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:53:37.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:53:37.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:53:37.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:53:37.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:53:38.192 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:53:38.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:53:39.498 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:53:40.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:53:40.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:53:41.349 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:53:42.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:53:42.623 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:53:43.240 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:53:43.240 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-07-31 15:53:43.240 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:53:43.240 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:53:43.252 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.47 ms, Average NMS time: 0.96 ms, Average inference time: 2.43 ms

2025-07-31 15:53:43.253 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:53:43.292 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:53:43.334 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch571
2025-07-31 15:53:45.018 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:07:50
2025-07-31 15:53:46.804 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:07:48
2025-07-31 15:53:48.615 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:07:45
2025-07-31 15:53:50.382 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:07:43
2025-07-31 15:53:52.242 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:07:40
2025-07-31 15:53:54.051 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:07:38
2025-07-31 15:53:54.820 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:53:54.884 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch572
2025-07-31 15:53:56.644 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:07:34
2025-07-31 15:53:58.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:07:32
2025-07-31 15:54:00.318 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.006s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:07:29
2025-07-31 15:54:02.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.8, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 4.4, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:07:27
2025-07-31 15:54:03.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:07:24
2025-07-31 15:54:05.669 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:07:22
2025-07-31 15:54:06.484 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:54:06.534 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch573
2025-07-31 15:54:08.317 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:07:18
2025-07-31 15:54:10.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:07:16
2025-07-31 15:54:11.888 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:07:13
2025-07-31 15:54:13.701 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:07:11
2025-07-31 15:54:15.568 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:07:08
2025-07-31 15:54:17.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:07:06
2025-07-31 15:54:18.238 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:54:18.283 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch574
2025-07-31 15:54:20.067 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:07:02
2025-07-31 15:54:21.896 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:07:00
2025-07-31 15:54:23.746 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:06:57
2025-07-31 15:54:25.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:06:55
2025-07-31 15:54:27.472 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:06:52
2025-07-31 15:54:29.274 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 1.3, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:06:50
2025-07-31 15:54:30.083 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:54:30.122 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch575
2025-07-31 15:54:31.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:06:46
2025-07-31 15:54:33.786 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:06:44
2025-07-31 15:54:35.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.6, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 5.5, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:06:41
2025-07-31 15:54:37.428 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:06:39
2025-07-31 15:54:39.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:06:36
2025-07-31 15:54:41.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:06:34
2025-07-31 15:54:41.906 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:54:48.417 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:54:49.232 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:54:49.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6140
2025-07-31 15:54:49.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5621
2025-07-31 15:54:49.879 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4099
2025-07-31 15:54:49.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5287
2025-07-31 15:54:49.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:54:49.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:54:49.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.614
2025-07-31 15:54:49.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.562
2025-07-31 15:54:49.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.410
2025-07-31 15:54:49.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.529
2025-07-31 15:54:49.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:54:49.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:54:49.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:54:49.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:54:49.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:54:49.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:54:49.882 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:54:49.882 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:54:49.882 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:54:50.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:54:51.219 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:54:51.873 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:54:52.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:54:53.179 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:54:53.842 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:54:54.458 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:54:55.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:54:55.745 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:54:55.745 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-31 15:54:55.745 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:54:55.745 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:54:55.755 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.45 ms, Average NMS time: 0.95 ms, Average inference time: 2.40 ms

2025-07-31 15:54:55.755 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:54:55.787 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:54:55.820 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch576
2025-07-31 15:54:57.647 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:06:30
2025-07-31 15:54:59.471 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 8.1, iou_loss: 2.8, l1_loss: 1.3, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:06:28
2025-07-31 15:55:01.292 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:06:25
2025-07-31 15:55:03.101 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.4, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:06:23
2025-07-31 15:55:04.999 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:06:20
2025-07-31 15:55:06.885 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:06:18
2025-07-31 15:55:07.670 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:55:07.710 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch577
2025-07-31 15:55:09.501 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:06:14
2025-07-31 15:55:11.290 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:06:12
2025-07-31 15:55:13.131 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:06:09
2025-07-31 15:55:14.975 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:06:07
2025-07-31 15:55:16.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:06:04
2025-07-31 15:55:18.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:06:02
2025-07-31 15:55:19.336 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:55:19.404 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch578
2025-07-31 15:55:21.120 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:05:58
2025-07-31 15:55:22.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 3.7, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:05:56
2025-07-31 15:55:24.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:05:54
2025-07-31 15:55:26.465 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:05:51
2025-07-31 15:55:28.253 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:05:49
2025-07-31 15:55:30.065 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:05:46
2025-07-31 15:55:30.828 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:55:30.867 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch579
2025-07-31 15:55:32.634 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:05:43
2025-07-31 15:55:34.461 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 4.8, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:05:40
2025-07-31 15:55:36.415 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:05:38
2025-07-31 15:55:38.289 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:05:35
2025-07-31 15:55:40.083 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.1, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:05:33
2025-07-31 15:55:41.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:05:30
2025-07-31 15:55:42.700 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:55:42.737 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch580
2025-07-31 15:55:44.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:05:27
2025-07-31 15:55:46.350 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 40/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.4, iou_loss: 0.8, l1_loss: 0.3, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:05:24
2025-07-31 15:55:48.272 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:05:22
2025-07-31 15:55:50.144 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:05:19
2025-07-31 15:55:52.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:05:17
2025-07-31 15:55:53.811 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:05:14
2025-07-31 15:55:54.596 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:56:01.000 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:56:01.976 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:56:02.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5950
2025-07-31 15:56:02.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5466
2025-07-31 15:56:02.720 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4063
2025-07-31 15:56:02.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5159
2025-07-31 15:56:02.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:56:02.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:56:02.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.595
2025-07-31 15:56:02.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.547
2025-07-31 15:56:02.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.406
2025-07-31 15:56:02.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.516
2025-07-31 15:56:02.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:56:02.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:56:02.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:56:02.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:56:02.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:56:02.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:56:02.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:56:02.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:56:02.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:56:03.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:56:04.255 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:56:04.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:56:05.735 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:56:06.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:56:07.198 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:56:07.896 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:56:08.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:56:09.375 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:56:09.375 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:56:09.375 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:56:09.375 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:56:09.384 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.50 ms, Average NMS time: 0.99 ms, Average inference time: 2.49 ms

2025-07-31 15:56:09.385 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:56:09.427 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:56:09.473 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch581
2025-07-31 15:56:11.220 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:05:11
2025-07-31 15:56:12.995 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.2, iou_loss: 1.3, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:05:08
2025-07-31 15:56:14.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.6, l1_loss: 1.4, conf_loss: 3.6, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:05:06
2025-07-31 15:56:16.639 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:05:03
2025-07-31 15:56:18.428 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 10.3, iou_loss: 2.8, l1_loss: 1.7, conf_loss: 4.2, cls_loss: 1.6, lr: 5.000e-04, size: 512, ETA: 0:05:01
2025-07-31 15:56:20.355 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:04:59
2025-07-31 15:56:21.174 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:56:21.213 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch582
2025-07-31 15:56:23.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:04:55
2025-07-31 15:56:24.860 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:04:53
2025-07-31 15:56:26.738 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.0, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 0.8, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:04:50
2025-07-31 15:56:28.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:04:48
2025-07-31 15:56:30.307 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 0.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:04:45
2025-07-31 15:56:32.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:04:43
2025-07-31 15:56:33.021 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:56:33.063 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch583
2025-07-31 15:56:34.864 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:04:39
2025-07-31 15:56:36.679 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:04:37
2025-07-31 15:56:38.452 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:04:34
2025-07-31 15:56:40.274 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:04:32
2025-07-31 15:56:42.051 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:04:29
2025-07-31 15:56:43.858 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:04:27
2025-07-31 15:56:44.647 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:56:44.698 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch584
2025-07-31 15:56:46.546 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:04:23
2025-07-31 15:56:48.292 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:04:21
2025-07-31 15:56:50.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:04:19
2025-07-31 15:56:51.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 1.0, lr: 5.000e-04, size: 352, ETA: 0:04:16
2025-07-31 15:56:53.749 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:04:14
2025-07-31 15:56:55.650 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:04:11
2025-07-31 15:56:56.495 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:56:56.570 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch585
2025-07-31 15:56:58.316 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 11.3, iou_loss: 3.5, l1_loss: 1.5, conf_loss: 5.4, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:04:08
2025-07-31 15:57:00.198 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 40/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:04:05
2025-07-31 15:57:02.048 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:04:03
2025-07-31 15:57:03.859 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.6, l1_loss: 1.2, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:04:00
2025-07-31 15:57:05.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:03:58
2025-07-31 15:57:07.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:03:55
2025-07-31 15:57:08.295 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:57:14.818 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:57:15.845 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:57:16.432 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6184
2025-07-31 15:57:16.540 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5689
2025-07-31 15:57:16.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4132
2025-07-31 15:57:16.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5335
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.618
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.569
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.413
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.534
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:57:16.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:57:16.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:57:16.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:57:16.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:57:16.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:57:17.355 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:57:18.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:57:18.841 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:57:19.544 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:57:20.309 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:57:21.014 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:57:21.733 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:57:22.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:57:23.244 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:57:23.245 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:57:23.245 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-07-31 15:57:23.245 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:57:23.255 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.46 ms, Average NMS time: 1.01 ms, Average inference time: 2.46 ms

2025-07-31 15:57:23.256 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:57:23.284 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:57:23.320 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch586
2025-07-31 15:57:25.047 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:03:52
2025-07-31 15:57:26.916 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:03:49
2025-07-31 15:57:28.650 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:03:47
2025-07-31 15:57:30.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:03:45
2025-07-31 15:57:32.330 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:03:42
2025-07-31 15:57:34.273 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:03:40
2025-07-31 15:57:35.038 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:57:35.089 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch587
2025-07-31 15:57:36.815 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:03:36
2025-07-31 15:57:38.736 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 40/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.095s, data_time: 0.007s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:03:34
2025-07-31 15:57:40.538 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:03:31
2025-07-31 15:57:42.388 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:03:29
2025-07-31 15:57:44.222 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 0.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:03:26
2025-07-31 15:57:45.999 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:03:24
2025-07-31 15:57:46.786 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:57:46.825 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch588
2025-07-31 15:57:48.637 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:03:20
2025-07-31 15:57:50.491 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 4.7, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:03:18
2025-07-31 15:57:52.341 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.3, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.4, lr: 5.000e-04, size: 320, ETA: 0:03:15
2025-07-31 15:57:54.179 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:03:13
2025-07-31 15:57:55.956 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:03:11
2025-07-31 15:57:57.769 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:03:08
2025-07-31 15:57:58.540 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:57:58.595 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch589
2025-07-31 15:58:00.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:03:05
2025-07-31 15:58:02.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:03:02
2025-07-31 15:58:04.079 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:03:00
2025-07-31 15:58:05.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:02:57
2025-07-31 15:58:07.842 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:02:55
2025-07-31 15:58:09.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:02:52
2025-07-31 15:58:10.458 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:58:10.529 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch590
2025-07-31 15:58:12.355 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:02:49
2025-07-31 15:58:14.223 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:02:46
2025-07-31 15:58:16.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:02:44
2025-07-31 15:58:17.814 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:02:42
2025-07-31 15:58:19.595 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.3, iou_loss: 2.1, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:02:39
2025-07-31 15:58:21.378 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:02:37
2025-07-31 15:58:22.221 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:58:28.705 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:58:29.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:58:29.765 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6149
2025-07-31 15:58:29.855 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5551
2025-07-31 15:58:29.924 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3838
2025-07-31 15:58:29.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5179
2025-07-31 15:58:29.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:58:29.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:58:29.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.615
2025-07-31 15:58:29.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.555
2025-07-31 15:58:29.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.384
2025-07-31 15:58:29.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.518
2025-07-31 15:58:29.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:58:29.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:58:29.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:58:29.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:58:29.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:58:29.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:58:29.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:58:29.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:58:29.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:58:30.421 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:58:30.912 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:58:31.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:58:31.937 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:58:32.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:58:33.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:58:33.530 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:58:34.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:58:34.531 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:58:34.531 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-07-31 15:58:34.531 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:58:34.531 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:58:34.539 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.88 ms, Average inference time: 2.26 ms

2025-07-31 15:58:34.540 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:58:34.569 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:58:34.611 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch591
2025-07-31 15:58:36.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:02:33
2025-07-31 15:58:38.122 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:02:31
2025-07-31 15:58:39.951 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:02:28
2025-07-31 15:58:41.833 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:02:26
2025-07-31 15:58:43.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:02:24
2025-07-31 15:58:45.385 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:02:21
2025-07-31 15:58:46.159 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:58:46.211 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch592
2025-07-31 15:58:48.053 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:02:18
2025-07-31 15:58:49.929 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:02:15
2025-07-31 15:58:51.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:02:13
2025-07-31 15:58:53.599 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:02:10
2025-07-31 15:58:55.374 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:02:08
2025-07-31 15:58:57.206 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 120/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:02:05
2025-07-31 15:58:58.008 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:58:58.048 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch593
2025-07-31 15:58:59.855 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:02:02
2025-07-31 15:59:01.818 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 40/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.095s, data_time: 0.003s, total_loss: 7.0, iou_loss: 1.9, l1_loss: 1.2, conf_loss: 3.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:01:59
2025-07-31 15:59:03.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:01:57
2025-07-31 15:59:05.484 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:01:55
2025-07-31 15:59:07.317 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:01:52
2025-07-31 15:59:09.114 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:01:50
2025-07-31 15:59:09.884 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:59:09.925 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch594
2025-07-31 15:59:11.732 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:01:46
2025-07-31 15:59:13.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.007s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:01:44
2025-07-31 15:59:15.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:01:41
2025-07-31 15:59:17.190 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:01:39
2025-07-31 15:59:19.010 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:01:37
2025-07-31 15:59:20.830 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:01:34
2025-07-31 15:59:21.640 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:59:21.721 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch595
2025-07-31 15:59:23.485 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:01:31
2025-07-31 15:59:25.306 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.2, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:01:28
2025-07-31 15:59:27.114 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:01:26
2025-07-31 15:59:28.942 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:01:23
2025-07-31 15:59:30.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:01:21
2025-07-31 15:59:32.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.3, l1_loss: 1.4, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:01:18
2025-07-31 15:59:33.565 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:59:40.121 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 15:59:40.946 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 15:59:41.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6164
2025-07-31 15:59:41.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5726
2025-07-31 15:59:41.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3775
2025-07-31 15:59:41.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5221
2025-07-31 15:59:41.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 15:59:41.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 15:59:41.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.616
2025-07-31 15:59:41.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.573
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.377
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.522
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 15:59:41.646 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 15:59:41.647 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 15:59:42.290 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 15:59:42.939 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 15:59:43.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 15:59:44.323 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 15:59:44.980 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 15:59:45.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 15:59:46.377 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 15:59:47.053 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 15:59:47.736 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 15:59:47.737 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-07-31 15:59:47.737 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-07-31 15:59:47.737 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 15:59:47.746 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.44 ms, Average NMS time: 0.96 ms, Average inference time: 2.40 ms

2025-07-31 15:59:47.747 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:59:47.789 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:59:47.842 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch596
2025-07-31 15:59:49.524 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:01:15
2025-07-31 15:59:51.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:01:13
2025-07-31 15:59:53.209 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:01:10
2025-07-31 15:59:55.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:01:08
2025-07-31 15:59:56.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:01:05
2025-07-31 15:59:58.797 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:01:03
2025-07-31 15:59:59.644 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 15:59:59.698 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch597
2025-07-31 16:00:01.502 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:00:59
2025-07-31 16:00:03.413 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 40/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.094s, data_time: 0.007s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:00:57
2025-07-31 16:00:05.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:00:55
2025-07-31 16:00:06.971 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.5, l1_loss: 0.3, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:00:52
2025-07-31 16:00:08.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:00:50
2025-07-31 16:00:10.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:00:47
2025-07-31 16:00:11.636 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 16:00:11.706 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch598
2025-07-31 16:00:13.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 20/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:00:44
2025-07-31 16:00:15.352 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:00:41
2025-07-31 16:00:17.090 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 60/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:00:39
2025-07-31 16:00:18.939 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:00:37
2025-07-31 16:00:20.795 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 2.9, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.4, lr: 5.000e-04, size: 480, ETA: 0:00:34
2025-07-31 16:00:22.641 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:00:32
2025-07-31 16:00:23.450 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 16:00:23.489 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch599
2025-07-31 16:00:25.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:00:28
2025-07-31 16:00:27.096 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 40/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 4.3, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:00:26
2025-07-31 16:00:28.990 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:00:23
2025-07-31 16:00:30.841 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 80/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:00:21
2025-07-31 16:00:32.658 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 100/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:00:19
2025-07-31 16:00:34.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:00:16
2025-07-31 16:00:35.378 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 16:00:35.442 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch600
2025-07-31 16:00:37.252 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 20/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:00:13
2025-07-31 16:00:39.087 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 40/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 3.7, iou_loss: 1.4, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:00:10
2025-07-31 16:00:41.007 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 60/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:00:08
2025-07-31 16:00:42.885 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 80/129, gpu mem: 1723Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:00:05
2025-07-31 16:00:44.644 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 100/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:00:03
2025-07-31 16:00:46.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 120/129, gpu mem: 1723Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:00:01
2025-07-31 16:00:47.172 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 16:00:53.529 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-31 16:00:54.639 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-31 16:00:55.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5633
2025-07-31 16:00:55.394 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5227
2025-07-31 16:00:55.454 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3236
2025-07-31 16:00:55.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4699
2025-07-31 16:00:55.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-31 16:00:55.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-31 16:00:55.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.563
2025-07-31 16:00:55.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.523
2025-07-31 16:00:55.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.324
2025-07-31 16:00:55.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.470
2025-07-31 16:00:55.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-31 16:00:55.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-31 16:00:55.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-31 16:00:55.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-31 16:00:55.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-31 16:00:55.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-31 16:00:55.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-31 16:00:55.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-31 16:00:55.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-31 16:00:56.289 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-31 16:00:57.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-31 16:00:57.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-31 16:00:58.829 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-31 16:00:59.676 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-31 16:01:00.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-31 16:01:01.318 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-31 16:01:02.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-31 16:01:02.979 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-31 16:01:02.980 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-31 16:01:02.980 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-31 16:01:02.980 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-31 16:01:02.991 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.52 ms, Average NMS time: 1.07 ms, Average inference time: 2.59 ms

2025-07-31 16:01:02.992 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 16:01:03.032 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset_sc1_pretrain
2025-07-31 16:01:03.082 | INFO     | yolox_microbt.core.trainer:after_train:172 - Training of experiment is done and the best AP is 30.36
