2025-07-30 03:06:12.540 | INFO     | yolox_microbt.core.trainer:before_train:88 - args: Namespace(config='configs.sa6921_vnne_3classes_voc_float_600e_trainset', experiment_name='sa6921_vnne_3classes_voc_float_600e_trainset', name=None, dist_backend='nccl', dist_url=None, batch_size=64, devices=8, exp_file=None, resume=False, ckpt='checkpoint/SA6921/coco_pretrain.pth', start_epoch=None, num_machines=1, machine_rank=0, fp16=False, cache=None, occupy=False, logger='tensorboard', opts=[])
2025-07-30 03:06:12.543 | 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' │
├───────────────────┼────────────────────────────────────────────────┤
│ test_size         │ (416, 416)                                     │
├───────────────────┼────────────────────────────────────────────────┤
│ test_conf         │ 0.01                                           │
├───────────────────┼────────────────────────────────────────────────┤
│ nmsthre           │ 0.65                                           │
├───────────────────┼────────────────────────────────────────────────┤
│ qat_warmup_epoch  │ -1                                             │
├───────────────────┼────────────────────────────────────────────────┤
│ qat_clib_epoch    │ 1                                              │
╘═══════════════════╧════════════════════════════════════════════════╛
2025-07-30 03:06:12.579 | INFO     | yolox_microbt.core.trainer:resume_train:325 - loading checkpoint for fine tuning
2025-07-30 03:06:13.538 | INFO     | yolox_microbt.core.trainer:before_train:129 - init prefetcher, this might take one minute or less...
2025-07-30 03:06:16.720 | INFO     | yolox_microbt.core.trainer:before_train:168 - Training start...
2025-07-30 03:06:16.722 | 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, 8, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn2): BatchNorm2d(8, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (2): 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, 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, 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)
            )
          )
          (4): 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, 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, 24, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(24, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (6): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(24, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(96, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=96, bias=False)
              (bn2): BatchNorm2d(96, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(96, 24, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(24, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (7): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(24, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(96, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(96, 96, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=96, bias=False)
              (bn2): BatchNorm2d(96, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(96, 40, kernel_size=(1, 1), stride=(1, 1), groups=2, bias=False)
              (bn3): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
            (1): InvertedResidual(
              (conv_pw): Conv2d(40, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(160, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(160, 160, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=160, bias=False)
              (bn2): BatchNorm2d(160, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(160, 40, kernel_size=(1, 1), stride=(1, 1), groups=2, bias=False)
              (bn3): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (8): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(40, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(160, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(160, 160, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=160, bias=False)
              (bn2): BatchNorm2d(160, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(160, 80, kernel_size=(1, 1), stride=(1, 1), groups=2, bias=False)
              (bn3): BatchNorm2d(80, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
        )
      )
      (head0): YOLOXHead(
        (shared_layer_8): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(8, 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(24, 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(80, 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()
    )
  )
)
2025-07-30 03:06:16.723 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch1
2025-07-30 03:06:16.724 | INFO     | yolox_microbt.core.trainer:before_epoch:204 - --->enable mosaic aug for quantization training!
2025-07-30 03:06:20.549 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 20/129, gpu mem: 660Mb, mem: 76.0Gb, iter_time: 0.181s, data_time: 0.011s, total_loss: 14.2, iou_loss: 4.6, l1_loss: 0.0, conf_loss: 8.5, cls_loss: 1.2, lr: 9.615e-06, size: 320, ETA: 3:52:50
2025-07-30 03:06:23.426 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 40/129, gpu mem: 740Mb, mem: 76.0Gb, iter_time: 0.133s, data_time: 0.016s, total_loss: 11.4, iou_loss: 4.5, l1_loss: 0.0, conf_loss: 5.6, cls_loss: 1.3, lr: 3.846e-05, size: 256, ETA: 3:22:24
2025-07-30 03:06:26.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 60/129, gpu mem: 828Mb, mem: 76.0Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 11.3, iou_loss: 4.3, l1_loss: 0.0, conf_loss: 5.7, cls_loss: 1.4, lr: 8.653e-05, size: 416, ETA: 3:12:14
2025-07-30 03:06:29.193 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 11.2, iou_loss: 4.1, l1_loss: 0.0, conf_loss: 5.9, cls_loss: 1.1, lr: 1.538e-04, size: 576, ETA: 3:08:06
2025-07-30 03:06:32.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.144s, data_time: 0.003s, total_loss: 9.3, iou_loss: 3.9, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.2, lr: 2.404e-04, size: 288, ETA: 3:07:39
2025-07-30 03:06:34.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 1/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 8.6, iou_loss: 3.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.4, lr: 3.461e-04, size: 256, ETA: 3:05:27
2025-07-30 03:06:36.102 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:06:36.147 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch2
2025-07-30 03:06:39.049 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 9.1, iou_loss: 3.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.5, lr: 5.336e-04, size: 288, ETA: 3:02:37
2025-07-30 03:06:41.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.131s, data_time: 0.010s, total_loss: 8.6, iou_loss: 3.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 6.865e-04, size: 320, ETA: 3:00:52
2025-07-30 03:06:44.694 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 10.7, iou_loss: 4.0, l1_loss: 0.0, conf_loss: 5.7, cls_loss: 1.0, lr: 8.586e-04, size: 256, ETA: 2:59:34
2025-07-30 03:06:47.382 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 9.1, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.1, lr: 1.050e-03, size: 256, ETA: 2:58:06
2025-07-30 03:06:50.295 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 1.261e-03, size: 256, ETA: 2:57:16
2025-07-30 03:06:53.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 2/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 10.3, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 5.3, cls_loss: 1.4, lr: 1.490e-03, size: 576, ETA: 2:56:05
2025-07-30 03:06:54.306 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:06:54.456 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch3
2025-07-30 03:06:57.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 10.3, iou_loss: 3.7, l1_loss: 0.0, conf_loss: 5.3, cls_loss: 1.3, lr: 1.858e-03, size: 448, ETA: 2:54:29
2025-07-30 03:07:00.165 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 9.6, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 5.1, cls_loss: 0.9, lr: 2.135e-03, size: 288, ETA: 2:53:03
2025-07-30 03:07:02.996 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 9.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.9, cls_loss: 1.0, lr: 2.431e-03, size: 416, ETA: 2:52:18
2025-07-30 03:07:05.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.117s, data_time: 0.004s, total_loss: 9.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.7, cls_loss: 1.1, lr: 2.746e-03, size: 448, ETA: 2:50:58
2025-07-30 03:07:08.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 10.6, iou_loss: 3.7, l1_loss: 0.0, conf_loss: 5.6, cls_loss: 1.3, lr: 3.081e-03, size: 416, ETA: 2:49:55
2025-07-30 03:07:11.574 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 3/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 9.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 5.2, cls_loss: 1.0, lr: 3.435e-03, size: 576, ETA: 2:49:39
2025-07-30 03:07:12.689 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:07:12.792 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch4
2025-07-30 03:07:15.523 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.0, lr: 3.982e-03, size: 320, ETA: 2:48:31
2025-07-30 03:07:18.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.2, lr: 4.383e-03, size: 416, ETA: 2:48:30
2025-07-30 03:07:21.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 12.7, iou_loss: 4.1, l1_loss: 0.0, conf_loss: 7.4, cls_loss: 1.2, lr: 4.803e-03, size: 576, ETA: 2:48:06
2025-07-30 03:07:24.006 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 10.3, iou_loss: 3.7, l1_loss: 0.0, conf_loss: 5.3, cls_loss: 1.3, lr: 5.242e-03, size: 416, ETA: 2:48:10
2025-07-30 03:07:26.864 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.135s, data_time: 0.006s, total_loss: 9.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 1.2, lr: 5.701e-03, size: 480, ETA: 2:48:19
2025-07-30 03:07:29.693 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 4/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.1, lr: 6.179e-03, size: 512, ETA: 2:48:19
2025-07-30 03:07:30.923 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:07:30.976 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch5
2025-07-30 03:07:33.720 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 10.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 5.4, cls_loss: 1.2, lr: 6.906e-03, size: 544, ETA: 2:48:23
2025-07-30 03:07:36.501 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 9.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.9, cls_loss: 0.9, lr: 7.431e-03, size: 384, ETA: 2:48:09
2025-07-30 03:07:39.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 7.975e-03, size: 448, ETA: 2:48:08
2025-07-30 03:07:42.017 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 9.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 5.0, cls_loss: 1.0, lr: 8.538e-03, size: 576, ETA: 2:48:00
2025-07-30 03:07:44.745 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.3, lr: 9.121e-03, size: 512, ETA: 2:47:57
2025-07-30 03:07:47.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 5/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.0Gb, iter_time: 0.127s, data_time: 0.005s, total_loss: 8.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.0, lr: 9.723e-03, size: 576, ETA: 2:47:43
2025-07-30 03:07:48.732 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:07:55.577 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:07:59.652 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:08:02.204 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.1044
2025-07-30 03:08:02.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.0086
2025-07-30 03:08:02.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.0000
2025-07-30 03:08:02.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.0377
2025-07-30 03:08:02.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:08:02.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:08:02.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.104
2025-07-30 03:08:02.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.009
2025-07-30 03:08:02.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.000
2025-07-30 03:08:02.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.038
2025-07-30 03:08:02.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:08:02.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:08:02.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:08:02.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:08:02.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:08:02.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:08:02.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:08:02.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:08:02.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:08:07.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:08:10.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:08:12.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:08:15.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:08:18.593 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:08:21.716 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:08:24.589 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:08:28.989 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:08:33.124 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:08:33.124 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.01
2025-07-30 03:08:33.124 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.04
2025-07-30 03:08:33.124 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:08:33.149 | 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: 2.42 ms

2025-07-30 03:08:33.150 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:08:33.183 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:08:33.215 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch6
2025-07-30 03:08:35.620 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.115s, data_time: 0.012s, total_loss: 7.9, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.000e-02, size: 256, ETA: 2:46:59
2025-07-30 03:08:38.411 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.127s, data_time: 0.013s, total_loss: 8.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 1.000e-02, size: 256, ETA: 2:46:49
2025-07-30 03:08:41.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.134s, data_time: 0.019s, total_loss: 9.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.9, cls_loss: 1.0, lr: 1.000e-02, size: 512, ETA: 2:46:55
2025-07-30 03:08:43.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.125s, 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: 1.000e-02, size: 384, ETA: 2:46:40
2025-07-30 03:08:46.739 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 1.000e-02, size: 256, ETA: 2:46:36
2025-07-30 03:08:49.654 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 6/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.5, lr: 1.000e-02, size: 320, ETA: 2:46:46
2025-07-30 03:08:50.856 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:08:50.924 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch7
2025-07-30 03:08:53.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 1.000e-02, size: 512, ETA: 2:47:02
2025-07-30 03:08:56.529 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 1.000e-02, size: 384, ETA: 2:46:59
2025-07-30 03:08:59.388 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.137s, 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: 1.000e-02, size: 288, ETA: 2:47:08
2025-07-30 03:09:02.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 1.000e-02, size: 544, ETA: 2:47:03
2025-07-30 03:09:05.057 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.000e-02, size: 384, ETA: 2:47:05
2025-07-30 03:09:07.922 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 7/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 9.6, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 1.2, lr: 9.999e-03, size: 512, ETA: 2:47:07
2025-07-30 03:09:09.192 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:09:09.303 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch8
2025-07-30 03:09:12.066 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.0, lr: 9.999e-03, size: 352, ETA: 2:47:04
2025-07-30 03:09:14.987 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.2, lr: 9.999e-03, size: 384, ETA: 2:47:07
2025-07-30 03:09:17.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 8.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 9.999e-03, size: 448, ETA: 2:47:00
2025-07-30 03:09:20.459 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.2, lr: 9.999e-03, size: 320, ETA: 2:46:53
2025-07-30 03:09:23.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 9.999e-03, size: 448, ETA: 2:46:50
2025-07-30 03:09:26.201 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 8/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 8.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.999e-03, size: 512, ETA: 2:46:46
2025-07-30 03:09:27.411 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:09:27.534 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch9
2025-07-30 03:09:30.216 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.999e-03, size: 480, ETA: 2:46:16
2025-07-30 03:09:32.963 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 9.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.6, lr: 9.998e-03, size: 352, ETA: 2:46:02
2025-07-30 03:09:35.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.121s, data_time: 0.005s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.998e-03, size: 416, ETA: 2:45:47
2025-07-30 03:09:38.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.3, lr: 9.998e-03, size: 480, ETA: 2:45:38
2025-07-30 03:09:41.413 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 9.998e-03, size: 320, ETA: 2:45:30
2025-07-30 03:09:44.144 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 9/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 8.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.3, lr: 9.998e-03, size: 352, ETA: 2:45:25
2025-07-30 03:09:45.278 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:09:45.365 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch10
2025-07-30 03:09:48.108 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 8.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 9.997e-03, size: 384, ETA: 2:45:17
2025-07-30 03:09:50.867 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.997e-03, size: 416, ETA: 2:45:15
2025-07-30 03:09:53.758 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 10.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 5.8, cls_loss: 1.1, lr: 9.997e-03, size: 512, ETA: 2:45:20
2025-07-30 03:09:56.525 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 9.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.9, cls_loss: 1.4, lr: 9.997e-03, size: 512, ETA: 2:45:19
2025-07-30 03:09:59.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 9.997e-03, size: 384, ETA: 2:45:25
2025-07-30 03:10:02.106 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 10/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.996e-03, size: 448, ETA: 2:45:21
2025-07-30 03:10:03.395 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:10:09.935 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:10:11.923 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:10:13.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.2188
2025-07-30 03:10:13.407 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.1806
2025-07-30 03:10:13.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.0138
2025-07-30 03:10:13.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.1377
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.219
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.181
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.014
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.138
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:10:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:10:13.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:10:13.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:10:13.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:10:13.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:10:13.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:10:15.035 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:10:16.607 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:10:18.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:10:19.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:10:21.244 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:10:22.768 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:10:24.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:10:25.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:10:27.410 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:10:27.410 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.04
2025-07-30 03:10:27.410 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.14
2025-07-30 03:10:27.410 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:10:27.434 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.95 ms, Average inference time: 2.30 ms

2025-07-30 03:10:27.435 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:10:27.464 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:10:27.493 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch11
2025-07-30 03:10:29.946 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.120s, data_time: 0.012s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.3, lr: 9.996e-03, size: 352, ETA: 2:45:10
2025-07-30 03:10:32.792 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 9.996e-03, size: 576, ETA: 2:45:19
2025-07-30 03:10:35.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 9.996e-03, size: 384, ETA: 2:45:19
2025-07-30 03:10:38.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 1.0, lr: 9.995e-03, size: 480, ETA: 2:45:29
2025-07-30 03:10:41.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.2, lr: 9.995e-03, size: 576, ETA: 2:45:33
2025-07-30 03:10:43.947 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 11/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 8.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.3, lr: 9.995e-03, size: 416, ETA: 2:45:37
2025-07-30 03:10:45.172 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:10:45.338 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch12
2025-07-30 03:10:47.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 9.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.9, cls_loss: 0.9, lr: 9.994e-03, size: 576, ETA: 2:45:32
2025-07-30 03:10:50.745 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 8.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 9.994e-03, size: 384, ETA: 2:45:32
2025-07-30 03:10:53.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.994e-03, size: 384, ETA: 2:45:22
2025-07-30 03:10:56.435 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 8.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 9.993e-03, size: 416, ETA: 2:45:20
2025-07-30 03:10:59.158 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.5, lr: 9.993e-03, size: 320, ETA: 2:45:18
2025-07-30 03:11:02.008 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 12/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.132s, data_time: 0.012s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 9.993e-03, size: 544, ETA: 2:45:16
2025-07-30 03:11:03.168 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:11:03.258 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch13
2025-07-30 03:11:06.081 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.992e-03, size: 544, ETA: 2:45:05
2025-07-30 03:11:08.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.3, lr: 9.992e-03, size: 384, ETA: 2:45:01
2025-07-30 03:11:11.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.146s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.7, cls_loss: 1.1, lr: 9.992e-03, size: 544, ETA: 2:45:13
2025-07-30 03:11:14.652 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.1, lr: 9.991e-03, size: 480, ETA: 2:45:18
2025-07-30 03:11:17.377 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.0, lr: 9.991e-03, size: 448, ETA: 2:45:14
2025-07-30 03:11:20.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 13/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.991e-03, size: 544, ETA: 2:45:16
2025-07-30 03:11:21.394 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:11:21.550 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch14
2025-07-30 03:11:24.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.4, lr: 9.990e-03, size: 576, ETA: 2:45:16
2025-07-30 03:11:27.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 9.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 5.0, cls_loss: 1.5, lr: 9.990e-03, size: 448, ETA: 2:45:12
2025-07-30 03:11:29.855 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.989e-03, size: 288, ETA: 2:45:06
2025-07-30 03:11:32.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.989e-03, size: 448, ETA: 2:45:01
2025-07-30 03:11:35.525 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 9.988e-03, size: 288, ETA: 2:44:56
2025-07-30 03:11:38.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 14/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.988e-03, size: 576, ETA: 2:44:47
2025-07-30 03:11:39.465 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:11:39.608 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch15
2025-07-30 03:11:42.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.120s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 9.987e-03, size: 256, ETA: 2:44:31
2025-07-30 03:11:45.042 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.119s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.987e-03, size: 352, ETA: 2:44:19
2025-07-30 03:11:47.893 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 9.987e-03, size: 480, ETA: 2:44:08
2025-07-30 03:11:50.721 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.986e-03, size: 320, ETA: 2:44:04
2025-07-30 03:11:53.549 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.986e-03, size: 384, ETA: 2:44:03
2025-07-30 03:11:56.266 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 15/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.121s, data_time: 0.006s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.985e-03, size: 320, ETA: 2:43:53
2025-07-30 03:11:57.412 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:12:03.656 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:12:05.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:12:05.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.2151
2025-07-30 03:12:06.067 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2126
2025-07-30 03:12:06.122 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.0459
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.1579
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.215
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.213
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.046
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.158
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:12:06.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:12:06.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:12:06.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:12:06.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:12:06.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:12:06.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:12:06.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:12:07.103 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:12:08.086 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:12:09.057 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:12:10.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:12:10.995 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:12:11.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:12:12.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:12:13.942 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:12:14.914 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:12:14.914 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.08
2025-07-30 03:12:14.914 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.16
2025-07-30 03:12:14.914 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:12:14.923 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.97 ms, Average inference time: 2.36 ms

2025-07-30 03:12:14.923 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:12:14.948 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:12:14.978 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch16
2025-07-30 03:12:17.476 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.116s, data_time: 0.024s, total_loss: 8.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.3, lr: 9.985e-03, size: 576, ETA: 2:43:34
2025-07-30 03:12:20.193 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.3, lr: 9.984e-03, size: 544, ETA: 2:43:26
2025-07-30 03:12:22.980 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.127s, data_time: 0.009s, total_loss: 8.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 9.984e-03, size: 416, ETA: 2:43:21
2025-07-30 03:12:25.718 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.124s, data_time: 0.007s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 9.983e-03, size: 384, ETA: 2:43:14
2025-07-30 03:12:28.693 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 9.983e-03, size: 576, ETA: 2:43:16
2025-07-30 03:12:31.399 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 16/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.120s, data_time: 0.003s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.982e-03, size: 576, ETA: 2:43:06
2025-07-30 03:12:32.575 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:12:32.665 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch17
2025-07-30 03:12:35.374 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.3, lr: 9.981e-03, size: 320, ETA: 2:42:55
2025-07-30 03:12:38.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.3, lr: 9.981e-03, size: 256, ETA: 2:42:53
2025-07-30 03:12:41.121 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.980e-03, size: 320, ETA: 2:42:53
2025-07-30 03:12:43.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.2, lr: 9.980e-03, size: 448, ETA: 2:42:44
2025-07-30 03:12:46.645 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.979e-03, size: 416, ETA: 2:42:41
2025-07-30 03:12:49.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 17/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.979e-03, size: 480, ETA: 2:42:34
2025-07-30 03:12:50.646 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:12:50.681 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch18
2025-07-30 03:12:53.507 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.006s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.978e-03, size: 288, ETA: 2:42:31
2025-07-30 03:12:56.346 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.3, lr: 9.977e-03, size: 384, ETA: 2:42:33
2025-07-30 03:12:59.244 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 9.977e-03, size: 544, ETA: 2:42:35
2025-07-30 03:13:02.199 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.139s, 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: 9.976e-03, size: 512, ETA: 2:42:39
2025-07-30 03:13:04.988 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.976e-03, size: 512, ETA: 2:42:37
2025-07-30 03:13:07.663 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 18/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.128s, data_time: 0.006s, total_loss: 8.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.2, lr: 9.975e-03, size: 352, ETA: 2:42:34
2025-07-30 03:13:08.879 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:13:08.905 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch19
2025-07-30 03:13:11.794 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 8.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.7, cls_loss: 1.1, lr: 9.974e-03, size: 384, ETA: 2:42:38
2025-07-30 03:13:14.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.973e-03, size: 320, ETA: 2:42:42
2025-07-30 03:13:17.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.3, lr: 9.973e-03, size: 352, ETA: 2:42:42
2025-07-30 03:13:20.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.1, lr: 9.972e-03, size: 256, ETA: 2:42:43
2025-07-30 03:13:22.936 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.972e-03, size: 416, ETA: 2:42:45
2025-07-30 03:13:25.620 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 19/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.010s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.971e-03, size: 256, ETA: 2:42:44
2025-07-30 03:13:26.901 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:13:27.038 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch20
2025-07-30 03:13:29.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 9.970e-03, size: 512, ETA: 2:42:43
2025-07-30 03:13:32.596 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.133s, 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: 9.969e-03, size: 448, ETA: 2:42:42
2025-07-30 03:13:35.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.3, lr: 9.969e-03, size: 256, ETA: 2:42:39
2025-07-30 03:13:38.236 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.968e-03, size: 512, ETA: 2:42:39
2025-07-30 03:13:41.021 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 9.967e-03, size: 256, ETA: 2:42:37
2025-07-30 03:13:43.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 20/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.127s, 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: 9.967e-03, size: 448, ETA: 2:42:32
2025-07-30 03:13:45.230 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:13:51.549 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:13:54.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:13:55.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3140
2025-07-30 03:13:55.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2556
2025-07-30 03:13:56.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1358
2025-07-30 03:13:56.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2351
2025-07-30 03:13:56.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:13:56.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:13:56.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.314
2025-07-30 03:13:56.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.256
2025-07-30 03:13:56.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.136
2025-07-30 03:13:56.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.235
2025-07-30 03:13:56.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:13:56.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:13:56.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:13:56.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:13:56.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:13:56.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:13:56.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:13:56.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:13:56.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:13:58.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:14:00.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:14:02.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:14:04.182 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:14:06.202 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:14:08.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:14:10.220 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:14:12.277 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:14:14.434 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:14:14.435 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.11
2025-07-30 03:14:14.435 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.24
2025-07-30 03:14:14.435 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:14:14.462 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.96 ms, Average inference time: 2.33 ms

2025-07-30 03:14:14.464 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:14:14.488 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:14:14.515 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch21
2025-07-30 03:14:16.960 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.119s, data_time: 0.010s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.966e-03, size: 416, ETA: 2:42:22
2025-07-30 03:14:19.783 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.965e-03, size: 544, ETA: 2:42:24
2025-07-30 03:14:22.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.145s, data_time: 0.001s, total_loss: 9.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.6, lr: 9.964e-03, size: 320, ETA: 2:42:30
2025-07-30 03:14:25.487 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 9.963e-03, size: 544, ETA: 2:42:31
2025-07-30 03:14:28.447 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 9.963e-03, size: 480, ETA: 2:42:37
2025-07-30 03:14:31.122 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 21/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.131s, data_time: 0.007s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 9.962e-03, size: 416, ETA: 2:42:35
2025-07-30 03:14:32.301 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:14:32.413 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch22
2025-07-30 03:14:35.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 9.961e-03, size: 288, ETA: 2:42:31
2025-07-30 03:14:37.936 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 9.960e-03, size: 544, ETA: 2:42:30
2025-07-30 03:14:40.641 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 9.959e-03, size: 512, ETA: 2:42:25
2025-07-30 03:14:43.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.2, lr: 9.959e-03, size: 288, ETA: 2:42:20
2025-07-30 03:14:46.356 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 9.958e-03, size: 512, ETA: 2:42:19
2025-07-30 03:14:49.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 22/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.122s, data_time: 0.004s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 9.957e-03, size: 448, ETA: 2:42:12
2025-07-30 03:14:50.269 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:14:50.388 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch23
2025-07-30 03:14:53.167 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.956e-03, size: 320, ETA: 2:42:04
2025-07-30 03:14:55.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 9.955e-03, size: 480, ETA: 2:41:56
2025-07-30 03:14:58.720 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.954e-03, size: 384, ETA: 2:41:48
2025-07-30 03:15:01.493 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 9.8, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 5.1, cls_loss: 1.3, lr: 9.953e-03, size: 384, ETA: 2:41:43
2025-07-30 03:15:04.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 9.953e-03, size: 416, ETA: 2:41:36
2025-07-30 03:15:07.124 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 23/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.952e-03, size: 480, ETA: 2:41:35
2025-07-30 03:15:08.306 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:15:08.395 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch24
2025-07-30 03:15:11.184 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.126s, 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: 9.951e-03, size: 384, ETA: 2:41:27
2025-07-30 03:15:13.885 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 0.8, lr: 9.950e-03, size: 544, ETA: 2:41:22
2025-07-30 03:15:16.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 60/129, gpu mem: 1553Mb, 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: 0.9, lr: 9.949e-03, size: 512, ETA: 2:41:20
2025-07-30 03:15:19.616 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 9.948e-03, size: 384, ETA: 2:41:20
2025-07-30 03:15:22.383 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.4, lr: 9.947e-03, size: 288, ETA: 2:41:17
2025-07-30 03:15:25.203 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 24/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 9.946e-03, size: 384, ETA: 2:41:17
2025-07-30 03:15:26.381 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:15:26.440 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch25
2025-07-30 03:15:29.233 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.3, lr: 9.945e-03, size: 448, ETA: 2:41:14
2025-07-30 03:15:31.947 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.944e-03, size: 384, ETA: 2:41:11
2025-07-30 03:15:34.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.943e-03, size: 512, ETA: 2:41:11
2025-07-30 03:15:37.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 9.942e-03, size: 256, ETA: 2:41:11
2025-07-30 03:15:40.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 9.941e-03, size: 288, ETA: 2:41:13
2025-07-30 03:15:43.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 25/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.940e-03, size: 448, ETA: 2:41:13
2025-07-30 03:15:44.343 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:15:50.827 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:15:58.348 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:16:04.656 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.2805
2025-07-30 03:16:05.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2197
2025-07-30 03:16:05.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.0807
2025-07-30 03:16:05.244 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.1936
2025-07-30 03:16:05.244 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:16:05.244 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.281
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.220
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.081
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.194
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:16:05.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:16:05.246 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:16:12.069 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:16:18.847 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:16:25.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:16:32.296 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:16:38.990 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:16:45.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:16:52.414 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:16:59.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:17:05.793 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:17:05.793 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.08
2025-07-30 03:17:05.793 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.19
2025-07-30 03:17:05.793 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:17:05.821 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.98 ms, Average inference time: 2.34 ms

2025-07-30 03:17:05.822 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:17:05.852 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:17:05.881 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch26
2025-07-30 03:17:08.314 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.114s, data_time: 0.021s, total_loss: 8.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.0, lr: 9.939e-03, size: 544, ETA: 2:41:02
2025-07-30 03:17:11.149 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 9.938e-03, size: 512, ETA: 2:41:01
2025-07-30 03:17:13.916 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 9.937e-03, size: 416, ETA: 2:40:56
2025-07-30 03:17:16.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 8.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 9.936e-03, size: 480, ETA: 2:40:53
2025-07-30 03:17:19.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.935e-03, size: 448, ETA: 2:40:47
2025-07-30 03:17:22.424 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 26/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.129s, data_time: 0.005s, total_loss: 8.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.2, lr: 9.934e-03, size: 480, ETA: 2:40:44
2025-07-30 03:17:23.678 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:17:23.827 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch27
2025-07-30 03:17:26.579 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 9.933e-03, size: 256, ETA: 2:40:35
2025-07-30 03:17:29.511 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 9.932e-03, size: 480, ETA: 2:40:30
2025-07-30 03:17:32.316 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.931e-03, size: 544, ETA: 2:40:28
2025-07-30 03:17:35.121 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.930e-03, size: 544, ETA: 2:40:25
2025-07-30 03:17:37.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.8, lr: 9.929e-03, size: 544, ETA: 2:40:24
2025-07-30 03:17:40.589 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 27/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.928e-03, size: 352, ETA: 2:40:21
2025-07-30 03:17:41.776 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:17:41.918 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch28
2025-07-30 03:17:44.726 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.926e-03, size: 480, ETA: 2:40:18
2025-07-30 03:17:47.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.925e-03, size: 384, ETA: 2:40:17
2025-07-30 03:17:50.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.126s, data_time: 0.014s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.924e-03, size: 288, ETA: 2:40:13
2025-07-30 03:17:53.350 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.0, lr: 9.923e-03, size: 544, ETA: 2:40:15
2025-07-30 03:17:56.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 9.922e-03, size: 480, ETA: 2:40:10
2025-07-30 03:17:58.822 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 28/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 9.921e-03, size: 320, ETA: 2:40:04
2025-07-30 03:17:59.994 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:18:00.064 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch29
2025-07-30 03:18:03.066 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.005s, total_loss: 8.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.2, lr: 9.920e-03, size: 288, ETA: 2:40:01
2025-07-30 03:18:05.861 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 9.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 5.0, cls_loss: 1.1, lr: 9.919e-03, size: 384, ETA: 2:39:56
2025-07-30 03:18:08.653 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.3, lr: 9.918e-03, size: 320, ETA: 2:39:49
2025-07-30 03:18:11.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.112s, data_time: 0.014s, total_loss: 9.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.4, lr: 9.916e-03, size: 288, ETA: 2:39:39
2025-07-30 03:18:13.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.915e-03, size: 512, ETA: 2:39:38
2025-07-30 03:18:16.787 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 29/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.914e-03, size: 544, ETA: 2:39:37
2025-07-30 03:18:18.031 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:18:18.094 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch30
2025-07-30 03:18:20.904 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.129s, 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: 9.913e-03, size: 288, ETA: 2:39:33
2025-07-30 03:18:23.607 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 9.911e-03, size: 480, ETA: 2:39:27
2025-07-30 03:18:26.387 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.910e-03, size: 448, ETA: 2:39:23
2025-07-30 03:18:29.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.124s, data_time: 0.011s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.909e-03, size: 544, ETA: 2:39:18
2025-07-30 03:18:31.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.129s, data_time: 0.017s, total_loss: 8.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.2, lr: 9.908e-03, size: 384, ETA: 2:39:15
2025-07-30 03:18:34.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 30/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.028s, total_loss: 8.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.0, lr: 9.907e-03, size: 480, ETA: 2:39:14
2025-07-30 03:18:36.047 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:18:42.225 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:18:45.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:18:46.817 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3324
2025-07-30 03:18:47.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2921
2025-07-30 03:18:47.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1671
2025-07-30 03:18:47.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2638
2025-07-30 03:18:47.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:18:47.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:18:47.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.332
2025-07-30 03:18:47.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.292
2025-07-30 03:18:47.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.167
2025-07-30 03:18:47.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.264
2025-07-30 03:18:47.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:18:47.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:18:47.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:18:47.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:18:47.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:18:47.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:18:47.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:18:47.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:18:47.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:18:49.569 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:18:51.866 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:18:54.119 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:18:56.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:18:58.856 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:19:01.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:19:03.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:19:05.587 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:19:07.824 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:19:07.825 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.13
2025-07-30 03:19:07.825 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.26
2025-07-30 03:19:07.825 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:19:07.849 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.98 ms, Average inference time: 2.35 ms

2025-07-30 03:19:07.851 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:19:07.875 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:19:07.903 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch31
2025-07-30 03:19:10.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.118s, data_time: 0.016s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.905e-03, size: 288, ETA: 2:39:07
2025-07-30 03:19:13.108 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 7.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.904e-03, size: 448, ETA: 2:39:07
2025-07-30 03:19:15.977 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.141s, data_time: 0.004s, total_loss: 8.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 9.903e-03, size: 448, ETA: 2:39:08
2025-07-30 03:19:18.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.005s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.902e-03, size: 512, ETA: 2:39:07
2025-07-30 03:19:21.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 0.9, lr: 9.901e-03, size: 480, ETA: 2:39:08
2025-07-30 03:19:24.463 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 31/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.147s, 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: 9.899e-03, size: 480, ETA: 2:39:11
2025-07-30 03:19:25.633 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:19:25.799 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch32
2025-07-30 03:19:28.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.898e-03, size: 480, ETA: 2:39:08
2025-07-30 03:19:31.246 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.896e-03, size: 256, ETA: 2:39:03
2025-07-30 03:19:34.156 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.895e-03, size: 416, ETA: 2:39:03
2025-07-30 03:19:36.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 8.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.2, lr: 9.894e-03, size: 256, ETA: 2:38:59
2025-07-30 03:19:39.659 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.893e-03, size: 384, ETA: 2:38:57
2025-07-30 03:19:42.505 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 32/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.2, lr: 9.891e-03, size: 320, ETA: 2:38:55
2025-07-30 03:19:43.732 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:19:43.792 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch33
2025-07-30 03:19:46.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.890e-03, size: 512, ETA: 2:38:54
2025-07-30 03:19:49.421 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.888e-03, size: 512, ETA: 2:38:55
2025-07-30 03:19:52.188 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.007s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.887e-03, size: 480, ETA: 2:38:54
2025-07-30 03:19:54.955 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.137s, data_time: 0.054s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.886e-03, size: 512, ETA: 2:38:53
2025-07-30 03:19:57.787 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.885e-03, size: 384, ETA: 2:38:53
2025-07-30 03:20:00.612 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 33/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.124s, data_time: 0.033s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.883e-03, size: 320, ETA: 2:38:48
2025-07-30 03:20:01.827 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:20:01.878 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch34
2025-07-30 03:20:04.829 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.881e-03, size: 512, ETA: 2:38:43
2025-07-30 03:20:07.523 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.880e-03, size: 288, ETA: 2:38:38
2025-07-30 03:20:10.308 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.879e-03, size: 480, ETA: 2:38:34
2025-07-30 03:20:13.175 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 9.877e-03, size: 544, ETA: 2:38:32
2025-07-30 03:20:16.117 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 11.0, iou_loss: 3.7, l1_loss: 0.0, conf_loss: 6.0, cls_loss: 1.2, lr: 9.876e-03, size: 480, ETA: 2:38:30
2025-07-30 03:20:18.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 34/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.127s, 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: 9.875e-03, size: 256, ETA: 2:38:26
2025-07-30 03:20:20.140 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:20:20.251 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch35
2025-07-30 03:20:22.963 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.119s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.873e-03, size: 544, ETA: 2:38:17
2025-07-30 03:20:25.836 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.3, lr: 9.872e-03, size: 544, ETA: 2:38:14
2025-07-30 03:20:28.573 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.117s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.870e-03, size: 544, ETA: 2:38:07
2025-07-30 03:20:31.398 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.869e-03, size: 416, ETA: 2:38:02
2025-07-30 03:20:34.133 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.867e-03, size: 416, ETA: 2:37:58
2025-07-30 03:20:36.924 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 35/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.122s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.866e-03, size: 384, ETA: 2:37:52
2025-07-30 03:20:38.133 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:20:44.644 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:20:47.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:20:50.298 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3406
2025-07-30 03:20:50.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2872
2025-07-30 03:20:50.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1258
2025-07-30 03:20:50.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2512
2025-07-30 03:20:50.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:20:50.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:20:50.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.341
2025-07-30 03:20:50.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.287
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.126
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.251
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:20:50.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:20:53.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:20:56.418 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:20:59.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:21:01.976 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:21:04.703 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:21:07.472 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:21:10.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:21:13.034 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:21:15.767 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:21:15.767 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.12
2025-07-30 03:21:15.767 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.25
2025-07-30 03:21:15.767 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:21:15.793 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.34 ms, Average NMS time: 0.97 ms, Average inference time: 2.31 ms

2025-07-30 03:21:15.794 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:21:15.825 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:21:15.856 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch36
2025-07-30 03:21:18.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.113s, data_time: 0.025s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.864e-03, size: 320, ETA: 2:37:42
2025-07-30 03:21:21.088 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.015s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.863e-03, size: 544, ETA: 2:37:39
2025-07-30 03:21:23.854 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.861e-03, size: 448, ETA: 2:37:36
2025-07-30 03:21:26.607 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 8.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.4, lr: 9.860e-03, size: 576, ETA: 2:37:34
2025-07-30 03:21:29.500 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.858e-03, size: 512, ETA: 2:37:32
2025-07-30 03:21:32.264 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 36/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.857e-03, size: 352, ETA: 2:37:30
2025-07-30 03:21:33.345 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:21:33.379 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch37
2025-07-30 03:21:36.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.121s, data_time: 0.024s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.855e-03, size: 480, ETA: 2:37:21
2025-07-30 03:21:38.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.121s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 9.853e-03, size: 416, ETA: 2:37:16
2025-07-30 03:21:41.794 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.852e-03, size: 448, ETA: 2:37:16
2025-07-30 03:21:44.557 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.135s, 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: 9.851e-03, size: 256, ETA: 2:37:15
2025-07-30 03:21:47.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.849e-03, size: 480, ETA: 2:37:14
2025-07-30 03:21:50.199 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 37/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.140s, data_time: 0.004s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.3, lr: 9.848e-03, size: 288, ETA: 2:37:15
2025-07-30 03:21:51.337 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:21:51.505 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch38
2025-07-30 03:21:54.279 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 9.846e-03, size: 288, ETA: 2:37:10
2025-07-30 03:21:57.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.844e-03, size: 544, ETA: 2:37:07
2025-07-30 03:21:59.833 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 9.843e-03, size: 320, ETA: 2:37:06
2025-07-30 03:22:02.750 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.7, cls_loss: 0.9, lr: 9.841e-03, size: 576, ETA: 2:37:02
2025-07-30 03:22:05.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 9.840e-03, size: 416, ETA: 2:36:59
2025-07-30 03:22:08.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 38/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.838e-03, size: 320, ETA: 2:36:57
2025-07-30 03:22:09.443 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:22:09.583 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch39
2025-07-30 03:22:12.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.836e-03, size: 320, ETA: 2:36:49
2025-07-30 03:22:15.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.834e-03, size: 512, ETA: 2:36:45
2025-07-30 03:22:17.967 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 9.833e-03, size: 288, ETA: 2:36:40
2025-07-30 03:22:20.838 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.831e-03, size: 384, ETA: 2:36:36
2025-07-30 03:22:23.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 9.830e-03, size: 448, ETA: 2:36:30
2025-07-30 03:22:26.411 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 39/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.828e-03, size: 320, ETA: 2:36:30
2025-07-30 03:22:27.608 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:22:27.639 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch40
2025-07-30 03:22:30.509 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.826e-03, size: 544, ETA: 2:36:27
2025-07-30 03:22:33.295 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.2, lr: 9.824e-03, size: 352, ETA: 2:36:26
2025-07-30 03:22:36.186 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 9.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 5.3, cls_loss: 1.1, lr: 9.823e-03, size: 512, ETA: 2:36:25
2025-07-30 03:22:39.079 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.821e-03, size: 544, ETA: 2:36:24
2025-07-30 03:22:42.004 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 0.8, lr: 9.819e-03, size: 512, ETA: 2:36:24
2025-07-30 03:22:44.804 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 40/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.818e-03, size: 448, ETA: 2:36:22
2025-07-30 03:22:45.984 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:22:52.346 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:22:54.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:22:56.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3589
2025-07-30 03:22:56.701 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2948
2025-07-30 03:22:56.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1616
2025-07-30 03:22:56.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2718
2025-07-30 03:22:56.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:22:56.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:22:56.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.359
2025-07-30 03:22:56.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.295
2025-07-30 03:22:56.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.162
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.272
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:22:56.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:22:58.735 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:23:00.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:23:02.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:23:04.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:23:06.699 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:23:08.648 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:23:10.612 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:23:12.567 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:23:14.542 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:23:14.543 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.12
2025-07-30 03:23:14.543 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.27
2025-07-30 03:23:14.543 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:23:14.570 | 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

2025-07-30 03:23:14.572 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:23:14.592 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:23:14.624 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch41
2025-07-30 03:23:17.003 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.118s, data_time: 0.032s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 9.816e-03, size: 544, ETA: 2:36:15
2025-07-30 03:23:19.703 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.020s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.814e-03, size: 320, ETA: 2:36:11
2025-07-30 03:23:22.618 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.812e-03, size: 384, ETA: 2:36:11
2025-07-30 03:23:25.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 9.811e-03, size: 544, ETA: 2:36:11
2025-07-30 03:23:28.255 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.809e-03, size: 576, ETA: 2:36:10
2025-07-30 03:23:31.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 41/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.3Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 8.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 0.9, lr: 9.807e-03, size: 480, ETA: 2:36:08
2025-07-30 03:23:32.262 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:23:32.446 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch42
2025-07-30 03:23:35.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.805e-03, size: 448, ETA: 2:36:05
2025-07-30 03:23:37.964 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.803e-03, size: 480, ETA: 2:36:03
2025-07-30 03:23:40.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.802e-03, size: 544, ETA: 2:36:02
2025-07-30 03:23:43.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.800e-03, size: 416, ETA: 2:36:01
2025-07-30 03:23:46.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.798e-03, size: 448, ETA: 2:35:59
2025-07-30 03:23:49.278 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 42/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, 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: 9.797e-03, size: 448, ETA: 2:35:57
2025-07-30 03:23:50.421 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:23:50.456 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch43
2025-07-30 03:23:53.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.9, lr: 9.794e-03, size: 416, ETA: 2:35:54
2025-07-30 03:23:55.996 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.792e-03, size: 384, ETA: 2:35:53
2025-07-30 03:23:58.909 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.142s, 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: 9.791e-03, size: 384, ETA: 2:35:54
2025-07-30 03:24:01.688 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 9.789e-03, size: 480, ETA: 2:35:53
2025-07-30 03:24:04.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.787e-03, size: 320, ETA: 2:35:53
2025-07-30 03:24:07.360 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 43/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.785e-03, size: 288, ETA: 2:35:51
2025-07-30 03:24:08.582 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:24:08.775 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch44
2025-07-30 03:24:11.519 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.0, lr: 9.783e-03, size: 448, ETA: 2:35:48
2025-07-30 03:24:14.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.007s, total_loss: 8.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.1, lr: 9.781e-03, size: 480, ETA: 2:35:44
2025-07-30 03:24:17.072 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 9.779e-03, size: 576, ETA: 2:35:42
2025-07-30 03:24:19.816 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.778e-03, size: 256, ETA: 2:35:38
2025-07-30 03:24:22.595 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.4, lr: 9.776e-03, size: 576, ETA: 2:35:36
2025-07-30 03:24:25.398 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 44/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.774e-03, size: 448, ETA: 2:35:33
2025-07-30 03:24:26.602 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:24:26.751 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch45
2025-07-30 03:24:29.758 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.772e-03, size: 576, ETA: 2:35:28
2025-07-30 03:24:32.452 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.117s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.770e-03, size: 256, ETA: 2:35:22
2025-07-30 03:24:35.226 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 8.7, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.8, lr: 9.768e-03, size: 352, ETA: 2:35:18
2025-07-30 03:24:38.040 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.766e-03, size: 256, ETA: 2:35:17
2025-07-30 03:24:40.906 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 9.764e-03, size: 448, ETA: 2:35:17
2025-07-30 03:24:43.736 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 45/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.139s, 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: 9.762e-03, size: 320, ETA: 2:35:17
2025-07-30 03:24:44.934 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:24:51.376 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:24:54.432 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:24:56.239 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3667
2025-07-30 03:24:56.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3149
2025-07-30 03:24:56.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2119
2025-07-30 03:24:56.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2978
2025-07-30 03:24:56.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:24:56.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.367
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.315
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.212
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.298
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:24:56.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:24:56.739 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:24:59.069 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:25:01.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:25:03.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:25:06.139 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:25:08.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:25:10.727 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:25:12.964 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:25:15.297 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:25:17.557 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:25:17.558 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.14
2025-07-30 03:25:17.558 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.30
2025-07-30 03:25:17.558 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:25:17.584 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.95 ms, Average inference time: 2.34 ms

2025-07-30 03:25:17.586 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:25:17.617 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:25:17.646 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch46
2025-07-30 03:25:20.129 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.120s, data_time: 0.036s, total_loss: 8.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 9.760e-03, size: 544, ETA: 2:35:10
2025-07-30 03:25:22.897 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.758e-03, size: 416, ETA: 2:35:08
2025-07-30 03:25:25.639 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.756e-03, size: 576, ETA: 2:35:03
2025-07-30 03:25:28.418 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 9.754e-03, size: 448, ETA: 2:35:01
2025-07-30 03:25:31.126 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.120s, data_time: 0.005s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 9.752e-03, size: 320, ETA: 2:34:56
2025-07-30 03:25:33.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 46/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.004s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.751e-03, size: 256, ETA: 2:34:52
2025-07-30 03:25:35.174 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:25:35.207 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch47
2025-07-30 03:25:38.123 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 9.748e-03, size: 288, ETA: 2:34:51
2025-07-30 03:25:40.924 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.746e-03, size: 288, ETA: 2:34:50
2025-07-30 03:25:43.753 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.138s, data_time: 0.005s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.744e-03, size: 544, ETA: 2:34:49
2025-07-30 03:25:46.553 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.742e-03, size: 512, ETA: 2:34:48
2025-07-30 03:25:49.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.139s, 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: 9.740e-03, size: 288, ETA: 2:34:48
2025-07-30 03:25:52.168 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 47/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.738e-03, size: 544, ETA: 2:34:46
2025-07-30 03:25:53.317 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:25:53.395 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch48
2025-07-30 03:25:56.183 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.736e-03, size: 288, ETA: 2:34:43
2025-07-30 03:25:59.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.734e-03, size: 320, ETA: 2:34:40
2025-07-30 03:26:01.842 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.732e-03, size: 544, ETA: 2:34:37
2025-07-30 03:26:04.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.730e-03, size: 288, ETA: 2:34:36
2025-07-30 03:26:07.482 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 8.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.728e-03, size: 480, ETA: 2:34:33
2025-07-30 03:26:10.315 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 48/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, 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: 9.726e-03, size: 256, ETA: 2:34:32
2025-07-30 03:26:11.529 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:26:11.568 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch49
2025-07-30 03:26:14.303 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.723e-03, size: 320, ETA: 2:34:29
2025-07-30 03:26:17.131 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.139s, data_time: 0.014s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.721e-03, size: 448, ETA: 2:34:29
2025-07-30 03:26:20.002 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 9.719e-03, size: 384, ETA: 2:34:27
2025-07-30 03:26:22.698 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.2, lr: 9.717e-03, size: 512, ETA: 2:34:24
2025-07-30 03:26:25.597 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.143s, data_time: 0.007s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.715e-03, size: 480, ETA: 2:34:24
2025-07-30 03:26:28.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 49/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.713e-03, size: 256, ETA: 2:34:23
2025-07-30 03:26:29.576 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:26:29.655 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch50
2025-07-30 03:26:32.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, 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: 0.9, lr: 9.710e-03, size: 416, ETA: 2:34:19
2025-07-30 03:26:35.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.708e-03, size: 448, ETA: 2:34:16
2025-07-30 03:26:38.026 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.706e-03, size: 352, ETA: 2:34:14
2025-07-30 03:26:40.797 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.012s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.704e-03, size: 256, ETA: 2:34:12
2025-07-30 03:26:43.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.012s, total_loss: 9.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 5.2, cls_loss: 0.9, lr: 9.702e-03, size: 544, ETA: 2:34:09
2025-07-30 03:26:46.432 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 50/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 9.700e-03, size: 480, ETA: 2:34:06
2025-07-30 03:26:47.790 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:26:54.305 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:26:55.663 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:26:56.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.2212
2025-07-30 03:26:56.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2641
2025-07-30 03:26:56.677 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1051
2025-07-30 03:26:56.677 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.1968
2025-07-30 03:26:56.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:26:56.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:26:56.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.221
2025-07-30 03:26:56.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.264
2025-07-30 03:26:56.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.105
2025-07-30 03:26:56.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.197
2025-07-30 03:26:56.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:26:56.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:26:56.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:26:56.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:26:56.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:26:56.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:26:56.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:26:56.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:26:56.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:26:57.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:26:58.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:26:59.659 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:27:00.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:27:01.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:27:02.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:27:03.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:27:04.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:27:05.641 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:27:05.641 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.09
2025-07-30 03:27:05.641 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.20
2025-07-30 03:27:05.641 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:27:05.648 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.95 ms, Average inference time: 2.29 ms

2025-07-30 03:27:05.650 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:27:05.670 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:27:05.699 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch51
2025-07-30 03:27:08.106 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.106s, data_time: 0.023s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.697e-03, size: 448, ETA: 2:33:58
2025-07-30 03:27:10.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.695e-03, size: 480, ETA: 2:33:55
2025-07-30 03:27:13.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 60/129, gpu mem: 1553Mb, 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: 9.693e-03, size: 544, ETA: 2:33:52
2025-07-30 03:27:16.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.691e-03, size: 288, ETA: 2:33:48
2025-07-30 03:27:19.338 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.689e-03, size: 256, ETA: 2:33:47
2025-07-30 03:27:22.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 51/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.687e-03, size: 480, ETA: 2:33:46
2025-07-30 03:27:23.381 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:27:23.618 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch52
2025-07-30 03:27:26.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.684e-03, size: 448, ETA: 2:33:42
2025-07-30 03:27:29.101 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.681e-03, size: 384, ETA: 2:33:40
2025-07-30 03:27:32.014 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.679e-03, size: 448, ETA: 2:33:38
2025-07-30 03:27:34.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.677e-03, size: 512, ETA: 2:33:37
2025-07-30 03:27:37.680 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.675e-03, size: 512, ETA: 2:33:34
2025-07-30 03:27:40.472 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 52/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.673e-03, size: 512, ETA: 2:33:32
2025-07-30 03:27:41.693 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:27:41.728 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch53
2025-07-30 03:27:44.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.144s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 9.670e-03, size: 320, ETA: 2:33:32
2025-07-30 03:27:47.485 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.668e-03, size: 448, ETA: 2:33:30
2025-07-30 03:27:50.296 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.136s, 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: 9.666e-03, size: 384, ETA: 2:33:29
2025-07-30 03:27:53.098 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.663e-03, size: 320, ETA: 2:33:28
2025-07-30 03:27:55.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.661e-03, size: 352, ETA: 2:33:26
2025-07-30 03:27:58.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 53/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.013s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.659e-03, size: 448, ETA: 2:33:23
2025-07-30 03:27:59.815 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:27:59.882 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch54
2025-07-30 03:28:02.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.032s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.656e-03, size: 544, ETA: 2:33:20
2025-07-30 03:28:05.421 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.007s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.654e-03, size: 288, ETA: 2:33:17
2025-07-30 03:28:08.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.651e-03, size: 256, ETA: 2:33:14
2025-07-30 03:28:11.163 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 9.649e-03, size: 480, ETA: 2:33:11
2025-07-30 03:28:14.089 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.647e-03, size: 416, ETA: 2:33:07
2025-07-30 03:28:16.874 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 54/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.009s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 9.645e-03, size: 384, ETA: 2:33:04
2025-07-30 03:28:18.080 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:28:18.198 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch55
2025-07-30 03:28:20.892 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.004s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.642e-03, size: 480, ETA: 2:32:59
2025-07-30 03:28:23.679 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.639e-03, size: 416, ETA: 2:32:57
2025-07-30 03:28:26.537 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.637e-03, size: 320, ETA: 2:32:53
2025-07-30 03:28:29.262 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 9.635e-03, size: 416, ETA: 2:32:49
2025-07-30 03:28:32.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.133s, 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: 9.633e-03, size: 288, ETA: 2:32:47
2025-07-30 03:28:34.892 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 55/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.630e-03, size: 448, ETA: 2:32:45
2025-07-30 03:28:36.101 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:28:42.608 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:28:43.849 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:28:44.591 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3321
2025-07-30 03:28:44.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3078
2025-07-30 03:28:44.829 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1270
2025-07-30 03:28:44.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2556
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.332
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.308
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.127
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.256
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:28:44.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:28:44.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:28:44.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:28:44.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:28:45.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:28:46.731 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:28:47.689 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:28:48.659 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:28:49.634 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:28:50.575 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:28:51.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:28:52.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:28:53.428 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:28:53.429 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.12
2025-07-30 03:28:53.429 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.26
2025-07-30 03:28:53.429 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:28:53.436 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.94 ms, Average inference time: 2.36 ms

2025-07-30 03:28:53.437 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:28:53.461 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:28:53.489 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch56
2025-07-30 03:28:55.946 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.112s, data_time: 0.007s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.627e-03, size: 448, ETA: 2:32:38
2025-07-30 03:28:58.773 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.625e-03, size: 512, ETA: 2:32:36
2025-07-30 03:29:01.471 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.623e-03, size: 448, ETA: 2:32:34
2025-07-30 03:29:04.412 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.620e-03, size: 384, ETA: 2:32:31
2025-07-30 03:29:07.187 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.618e-03, size: 384, ETA: 2:32:28
2025-07-30 03:29:10.091 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 56/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.3, lr: 9.616e-03, size: 256, ETA: 2:32:26
2025-07-30 03:29:11.264 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:29:11.320 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch57
2025-07-30 03:29:14.149 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 9.612e-03, size: 320, ETA: 2:32:23
2025-07-30 03:29:16.960 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.610e-03, size: 256, ETA: 2:32:22
2025-07-30 03:29:19.970 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.146s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.608e-03, size: 576, ETA: 2:32:22
2025-07-30 03:29:22.570 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.0, lr: 9.605e-03, size: 448, ETA: 2:32:19
2025-07-30 03:29:25.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.140s, 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: 9.603e-03, size: 480, ETA: 2:32:18
2025-07-30 03:29:28.197 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 57/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.015s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 9.601e-03, size: 320, ETA: 2:32:17
2025-07-30 03:29:29.468 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:29:29.579 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch58
2025-07-30 03:29:32.300 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.597e-03, size: 480, ETA: 2:32:13
2025-07-30 03:29:35.213 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 9.595e-03, size: 352, ETA: 2:32:12
2025-07-30 03:29:37.910 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.014s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.592e-03, size: 512, ETA: 2:32:09
2025-07-30 03:29:40.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.590e-03, size: 384, ETA: 2:32:07
2025-07-30 03:29:43.529 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.019s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.588e-03, size: 416, ETA: 2:32:04
2025-07-30 03:29:46.171 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 58/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 7.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 9.585e-03, size: 512, ETA: 2:32:00
2025-07-30 03:29:47.416 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:29:47.506 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch59
2025-07-30 03:29:50.266 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.582e-03, size: 288, ETA: 2:31:55
2025-07-30 03:29:53.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.125s, data_time: 0.004s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.579e-03, size: 384, ETA: 2:31:52
2025-07-30 03:29:55.867 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.125s, 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: 9.577e-03, size: 320, ETA: 2:31:48
2025-07-30 03:29:58.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.575e-03, size: 416, ETA: 2:31:44
2025-07-30 03:30:01.570 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 8.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 9.572e-03, size: 384, ETA: 2:31:41
2025-07-30 03:30:04.283 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 59/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.570e-03, size: 384, ETA: 2:31:38
2025-07-30 03:30:05.509 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:30:05.661 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch60
2025-07-30 03:30:08.305 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.122s, data_time: 0.017s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.566e-03, size: 352, ETA: 2:31:33
2025-07-30 03:30:11.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.129s, data_time: 0.009s, total_loss: 8.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 9.564e-03, size: 256, ETA: 2:31:30
2025-07-30 03:30:13.932 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.561e-03, size: 352, ETA: 2:31:26
2025-07-30 03:30:16.744 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, 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: 9.559e-03, size: 384, ETA: 2:31:23
2025-07-30 03:30:19.556 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 9.556e-03, size: 448, ETA: 2:31:21
2025-07-30 03:30:22.314 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 60/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.006s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.554e-03, size: 352, ETA: 2:31:18
2025-07-30 03:30:23.568 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:30:30.025 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:30:35.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:30:39.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3727
2025-07-30 03:30:39.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3436
2025-07-30 03:30:39.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1756
2025-07-30 03:30:39.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2973
2025-07-30 03:30:39.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:30:39.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:30:39.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.373
2025-07-30 03:30:39.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.344
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.176
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.297
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:30:39.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:30:39.806 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:30:44.253 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:30:48.657 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:30:53.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:30:57.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:31:02.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:31:06.497 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:31:10.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:31:15.289 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:31:19.726 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:31:19.727 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.14
2025-07-30 03:31:19.727 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.30
2025-07-30 03:31:19.727 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:31:19.755 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.96 ms, Average inference time: 2.32 ms

2025-07-30 03:31:19.757 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:31:19.783 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:31:19.822 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch61
2025-07-30 03:31:22.234 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.118s, data_time: 0.042s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.550e-03, size: 256, ETA: 2:31:12
2025-07-30 03:31:25.123 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.142s, data_time: 0.005s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 9.548e-03, size: 448, ETA: 2:31:11
2025-07-30 03:31:27.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.545e-03, size: 256, ETA: 2:31:09
2025-07-30 03:31:30.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.543e-03, size: 384, ETA: 2:31:09
2025-07-30 03:31:33.609 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.540e-03, size: 512, ETA: 2:31:07
2025-07-30 03:31:36.501 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 61/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.142s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.538e-03, size: 448, ETA: 2:31:07
2025-07-30 03:31:37.756 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:31:37.869 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch62
2025-07-30 03:31:40.565 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.534e-03, size: 352, ETA: 2:31:04
2025-07-30 03:31:43.350 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.532e-03, size: 576, ETA: 2:31:01
2025-07-30 03:31:46.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 7.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.3, lr: 9.529e-03, size: 416, ETA: 2:30:59
2025-07-30 03:31:48.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, 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: 9.526e-03, size: 512, ETA: 2:30:56
2025-07-30 03:31:51.762 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 9.524e-03, size: 448, ETA: 2:30:53
2025-07-30 03:31:54.594 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 62/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.521e-03, size: 576, ETA: 2:30:50
2025-07-30 03:31:55.727 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:31:55.922 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch63
2025-07-30 03:31:58.570 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.121s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.518e-03, size: 352, ETA: 2:30:43
2025-07-30 03:32:01.410 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.515e-03, size: 512, ETA: 2:30:41
2025-07-30 03:32:04.280 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 9.512e-03, size: 448, ETA: 2:30:40
2025-07-30 03:32:07.133 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.0, lr: 9.510e-03, size: 480, ETA: 2:30:38
2025-07-30 03:32:09.945 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 9.507e-03, size: 576, ETA: 2:30:37
2025-07-30 03:32:12.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 63/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.505e-03, size: 448, ETA: 2:30:35
2025-07-30 03:32:13.988 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:32:14.154 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch64
2025-07-30 03:32:16.864 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.013s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.501e-03, size: 448, ETA: 2:30:32
2025-07-30 03:32:19.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.123s, data_time: 0.018s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.498e-03, size: 288, ETA: 2:30:28
2025-07-30 03:32:22.360 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.136s, 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: 9.496e-03, size: 544, ETA: 2:30:26
2025-07-30 03:32:25.248 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.493e-03, size: 352, ETA: 2:30:24
2025-07-30 03:32:28.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.125s, data_time: 0.006s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.490e-03, size: 288, ETA: 2:30:21
2025-07-30 03:32:31.003 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 64/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.488e-03, size: 512, ETA: 2:30:17
2025-07-30 03:32:32.317 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:32:32.440 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch65
2025-07-30 03:32:35.080 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.117s, 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: 9.484e-03, size: 384, ETA: 2:30:11
2025-07-30 03:32:38.013 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.123s, 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: 9.481e-03, size: 384, ETA: 2:30:07
2025-07-30 03:32:40.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.479e-03, size: 448, ETA: 2:30:04
2025-07-30 03:32:43.551 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 9.476e-03, size: 256, ETA: 2:30:03
2025-07-30 03:32:46.214 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 9.473e-03, size: 512, ETA: 2:30:01
2025-07-30 03:32:49.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 65/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 9.471e-03, size: 288, ETA: 2:29:59
2025-07-30 03:32:50.280 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:32:56.658 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:32:57.221 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:32:57.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.2322
2025-07-30 03:32:57.522 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2311
2025-07-30 03:32:57.557 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1554
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2062
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.232
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.231
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.155
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.206
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:32:57.558 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:32:57.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:32:57.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:32:57.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:32:57.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:32:57.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:32:57.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:32:57.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:32:58.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:32:58.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:32:59.150 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:32:59.462 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:32:59.807 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:33:00.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:33:00.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:33:00.759 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:33:00.759 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.10
2025-07-30 03:33:00.759 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.21
2025-07-30 03:33:00.759 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:33:00.767 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.90 ms, Average inference time: 2.29 ms

2025-07-30 03:33:00.769 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:33:00.788 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:33:00.815 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch66
2025-07-30 03:33:03.350 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.119s, data_time: 0.007s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 9.467e-03, size: 512, ETA: 2:29:54
2025-07-30 03:33:06.129 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 9.464e-03, size: 288, ETA: 2:29:50
2025-07-30 03:33:08.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.461e-03, size: 256, ETA: 2:29:47
2025-07-30 03:33:11.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.122s, data_time: 0.005s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 9.459e-03, size: 544, ETA: 2:29:43
2025-07-30 03:33:14.537 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.020s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 9.456e-03, size: 544, ETA: 2:29:41
2025-07-30 03:33:17.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 66/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.453e-03, size: 384, ETA: 2:29:38
2025-07-30 03:33:18.578 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:33:18.622 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch67
2025-07-30 03:33:21.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.449e-03, size: 320, ETA: 2:29:34
2025-07-30 03:33:24.223 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.446e-03, size: 288, ETA: 2:29:30
2025-07-30 03:33:26.995 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.444e-03, size: 448, ETA: 2:29:26
2025-07-30 03:33:29.928 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.441e-03, size: 288, ETA: 2:29:23
2025-07-30 03:33:32.664 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 9.438e-03, size: 480, ETA: 2:29:20
2025-07-30 03:33:35.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 67/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.120s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.435e-03, size: 352, ETA: 2:29:15
2025-07-30 03:33:36.692 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:33:36.725 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch68
2025-07-30 03:33:39.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 9.431e-03, size: 320, ETA: 2:29:10
2025-07-30 03:33:42.312 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.429e-03, size: 512, ETA: 2:29:08
2025-07-30 03:33:45.202 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 9.426e-03, size: 384, ETA: 2:29:06
2025-07-30 03:33:47.996 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 9.423e-03, size: 288, ETA: 2:29:03
2025-07-30 03:33:50.708 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.1, lr: 9.420e-03, size: 576, ETA: 2:28:59
2025-07-30 03:33:53.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 68/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.417e-03, size: 384, ETA: 2:28:56
2025-07-30 03:33:54.798 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:33:54.935 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch69
2025-07-30 03:33:57.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 9.413e-03, size: 384, ETA: 2:28:51
2025-07-30 03:34:00.550 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.410e-03, size: 288, ETA: 2:28:47
2025-07-30 03:34:03.347 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 9.408e-03, size: 544, ETA: 2:28:44
2025-07-30 03:34:06.215 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.4Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.405e-03, size: 352, ETA: 2:28:43
2025-07-30 03:34:08.904 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 9.402e-03, size: 416, ETA: 2:28:41
2025-07-30 03:34:11.956 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 69/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.149s, data_time: 0.001s, total_loss: 8.4, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 9.399e-03, size: 320, ETA: 2:28:41
2025-07-30 03:34:13.182 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:34:13.279 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch70
2025-07-30 03:34:15.971 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.005s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 9.395e-03, size: 512, ETA: 2:28:37
2025-07-30 03:34:18.884 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.392e-03, size: 576, ETA: 2:28:36
2025-07-30 03:34:21.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.389e-03, size: 448, ETA: 2:28:33
2025-07-30 03:34:24.352 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.386e-03, size: 256, ETA: 2:28:31
2025-07-30 03:34:27.247 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.383e-03, size: 480, ETA: 2:28:29
2025-07-30 03:34:30.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 70/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 11.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 7.7, cls_loss: 0.8, lr: 9.381e-03, size: 576, ETA: 2:28:27
2025-07-30 03:34:31.350 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:34:37.758 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:34:38.501 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:34:38.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.2237
2025-07-30 03:34:38.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2458
2025-07-30 03:34:38.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1074
2025-07-30 03:34:38.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.1923
2025-07-30 03:34:38.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.224
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.246
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.107
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.192
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:34:38.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:34:38.934 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:34:38.934 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:34:39.358 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:34:39.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:34:40.238 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:34:40.659 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:34:41.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:34:41.509 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:34:41.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:34:42.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:34:42.786 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:34:42.787 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.08
2025-07-30 03:34:42.787 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.19
2025-07-30 03:34:42.788 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:34:42.805 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.94 ms, Average inference time: 2.36 ms

2025-07-30 03:34:42.806 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:34:42.835 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:34:42.873 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch71
2025-07-30 03:34:45.319 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.121s, data_time: 0.022s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.376e-03, size: 256, ETA: 2:28:22
2025-07-30 03:34:48.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.373e-03, size: 512, ETA: 2:28:22
2025-07-30 03:34:50.966 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.371e-03, size: 256, ETA: 2:28:19
2025-07-30 03:34:53.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, 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: 9.368e-03, size: 384, ETA: 2:28:16
2025-07-30 03:34:56.660 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, 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: 9.365e-03, size: 288, ETA: 2:28:13
2025-07-30 03:34:59.388 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 71/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.016s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.362e-03, size: 320, ETA: 2:28:11
2025-07-30 03:35:00.648 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:35:00.764 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch72
2025-07-30 03:35:03.483 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.358e-03, size: 352, ETA: 2:28:08
2025-07-30 03:35:06.328 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, 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: 9.355e-03, size: 288, ETA: 2:28:05
2025-07-30 03:35:09.091 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.352e-03, size: 448, ETA: 2:28:03
2025-07-30 03:35:11.903 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 9.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 5.3, cls_loss: 0.9, lr: 9.349e-03, size: 416, ETA: 2:28:01
2025-07-30 03:35:14.729 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.346e-03, size: 256, ETA: 2:27:58
2025-07-30 03:35:17.570 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 72/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 9.343e-03, size: 384, ETA: 2:27:56
2025-07-30 03:35:18.752 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:35:18.818 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch73
2025-07-30 03:35:21.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.338e-03, size: 576, ETA: 2:27:53
2025-07-30 03:35:24.495 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 9.335e-03, size: 320, ETA: 2:27:52
2025-07-30 03:35:27.241 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.332e-03, size: 416, ETA: 2:27:49
2025-07-30 03:35:30.106 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.329e-03, size: 416, ETA: 2:27:48
2025-07-30 03:35:32.876 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.326e-03, size: 416, ETA: 2:27:46
2025-07-30 03:35:35.737 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 73/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.323e-03, size: 576, ETA: 2:27:45
2025-07-30 03:35:36.965 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:35:37.091 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch74
2025-07-30 03:35:39.798 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.125s, data_time: 0.006s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.319e-03, size: 288, ETA: 2:27:41
2025-07-30 03:35:42.617 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.316e-03, size: 512, ETA: 2:27:39
2025-07-30 03:35:45.456 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 9.313e-03, size: 320, ETA: 2:27:36
2025-07-30 03:35:48.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.310e-03, size: 448, ETA: 2:27:33
2025-07-30 03:35:51.099 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.127s, data_time: 0.006s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.307e-03, size: 320, ETA: 2:27:30
2025-07-30 03:35:53.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 74/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.304e-03, size: 320, ETA: 2:27:28
2025-07-30 03:35:55.156 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:35:55.246 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch75
2025-07-30 03:35:58.183 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.299e-03, size: 576, ETA: 2:27:26
2025-07-30 03:36:01.004 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.296e-03, size: 352, ETA: 2:27:24
2025-07-30 03:36:03.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.293e-03, size: 480, ETA: 2:27:22
2025-07-30 03:36:06.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 9.290e-03, size: 512, ETA: 2:27:20
2025-07-30 03:36:09.373 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.287e-03, size: 416, ETA: 2:27:17
2025-07-30 03:36:12.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 75/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.284e-03, size: 512, ETA: 2:27:16
2025-07-30 03:36:13.367 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:36:19.871 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:36:27.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:36:32.885 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3811
2025-07-30 03:36:33.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3216
2025-07-30 03:36:33.473 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1465
2025-07-30 03:36:33.474 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2831
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.381
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.322
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.146
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.283
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:36:33.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:36:33.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:36:33.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:36:33.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:36:33.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:36:38.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:36:44.471 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:36:50.000 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:36:55.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:37:01.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:37:06.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:37:12.725 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:37:20.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:37:26.809 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:37:26.809 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.13
2025-07-30 03:37:26.810 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.28
2025-07-30 03:37:26.810 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:37:26.837 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.32 ms, Average NMS time: 0.95 ms, Average inference time: 2.27 ms

2025-07-30 03:37:26.838 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:37:26.872 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:37:26.907 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch76
2025-07-30 03:37:29.344 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.118s, data_time: 0.024s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.280e-03, size: 416, ETA: 2:27:10
2025-07-30 03:37:32.249 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.276e-03, size: 544, ETA: 2:27:07
2025-07-30 03:37:35.118 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.273e-03, size: 384, ETA: 2:27:05
2025-07-30 03:37:37.903 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 9.270e-03, size: 320, ETA: 2:27:02
2025-07-30 03:37:40.750 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.267e-03, size: 352, ETA: 2:26:59
2025-07-30 03:37:43.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 76/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.127s, data_time: 0.005s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.264e-03, size: 448, ETA: 2:26:56
2025-07-30 03:37:44.760 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:37:44.861 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch77
2025-07-30 03:37:47.568 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.121s, 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: 9.259e-03, size: 256, ETA: 2:26:51
2025-07-30 03:37:50.618 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.256e-03, size: 448, ETA: 2:26:48
2025-07-30 03:37:53.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.253e-03, size: 320, ETA: 2:26:44
2025-07-30 03:37:56.101 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.121s, data_time: 0.003s, total_loss: 8.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.9, cls_loss: 0.9, lr: 9.250e-03, size: 352, ETA: 2:26:40
2025-07-30 03:37:58.978 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.2, lr: 9.247e-03, size: 320, ETA: 2:26:37
2025-07-30 03:38:01.594 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 77/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.125s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.244e-03, size: 288, ETA: 2:26:34
2025-07-30 03:38:02.841 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:38:02.958 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch78
2025-07-30 03:38:05.685 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 9.239e-03, size: 480, ETA: 2:26:30
2025-07-30 03:38:08.474 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.236e-03, size: 384, ETA: 2:26:28
2025-07-30 03:38:11.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.4, lr: 9.233e-03, size: 384, ETA: 2:26:26
2025-07-30 03:38:14.158 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.229e-03, size: 576, ETA: 2:26:23
2025-07-30 03:38:16.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.2, lr: 9.226e-03, size: 416, ETA: 2:26:21
2025-07-30 03:38:19.707 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 78/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.223e-03, size: 448, ETA: 2:26:18
2025-07-30 03:38:20.909 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:38:20.943 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch79
2025-07-30 03:38:23.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.145s, data_time: 0.001s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.218e-03, size: 288, ETA: 2:26:16
2025-07-30 03:38:26.567 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 7.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 9.215e-03, size: 544, ETA: 2:26:14
2025-07-30 03:38:29.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 9.212e-03, size: 352, ETA: 2:26:12
2025-07-30 03:38:32.255 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 9.209e-03, size: 416, ETA: 2:26:11
2025-07-30 03:38:35.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.206e-03, size: 544, ETA: 2:26:10
2025-07-30 03:38:37.968 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 79/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.202e-03, size: 512, ETA: 2:26:08
2025-07-30 03:38:39.224 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:38:39.353 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch80
2025-07-30 03:38:42.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.6, lr: 9.198e-03, size: 256, ETA: 2:26:05
2025-07-30 03:38:44.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.126s, data_time: 0.005s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.194e-03, size: 320, ETA: 2:26:02
2025-07-30 03:38:47.709 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.137s, data_time: 0.010s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.191e-03, size: 512, ETA: 2:26:00
2025-07-30 03:38:50.473 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 9.188e-03, size: 352, ETA: 2:25:58
2025-07-30 03:38:53.355 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.184e-03, size: 448, ETA: 2:25:56
2025-07-30 03:38:56.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 80/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.029s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.7, lr: 9.181e-03, size: 512, ETA: 2:25:54
2025-07-30 03:38:57.348 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:39:03.711 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:39:05.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:39:06.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3687
2025-07-30 03:39:06.473 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3625
2025-07-30 03:39:06.608 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1988
2025-07-30 03:39:06.609 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3100
2025-07-30 03:39:06.609 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:39:06.609 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:39:06.609 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.369
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.362
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.199
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.310
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:39:06.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:39:06.611 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:39:06.611 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:39:07.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:39:09.040 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:39:10.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:39:11.440 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:39:12.633 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:39:13.824 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:39:15.014 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:39:16.186 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:39:17.409 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:39:17.409 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.15
2025-07-30 03:39:17.409 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.31
2025-07-30 03:39:17.409 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:39:17.417 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.91 ms, Average inference time: 2.29 ms

2025-07-30 03:39:17.419 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:39:17.444 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:39:17.474 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch81
2025-07-30 03:39:19.820 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.115s, data_time: 0.040s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.176e-03, size: 288, ETA: 2:25:48
2025-07-30 03:39:22.692 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.133s, data_time: 0.047s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.173e-03, size: 480, ETA: 2:25:46
2025-07-30 03:39:25.501 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.018s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.170e-03, size: 544, ETA: 2:25:43
2025-07-30 03:39:28.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.166e-03, size: 544, ETA: 2:25:40
2025-07-30 03:39:31.300 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 9.163e-03, size: 320, ETA: 2:25:38
2025-07-30 03:39:34.168 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 81/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.160e-03, size: 544, ETA: 2:25:35
2025-07-30 03:39:35.398 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:39:35.433 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch82
2025-07-30 03:39:38.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.155e-03, size: 352, ETA: 2:25:31
2025-07-30 03:39:40.945 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.123s, 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: 9.152e-03, size: 352, ETA: 2:25:27
2025-07-30 03:39:43.662 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.148e-03, size: 352, ETA: 2:25:24
2025-07-30 03:39:46.556 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.131s, 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: 9.145e-03, size: 544, ETA: 2:25:21
2025-07-30 03:39:49.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 9.142e-03, size: 256, ETA: 2:25:19
2025-07-30 03:39:52.201 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 82/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.138e-03, size: 544, ETA: 2:25:16
2025-07-30 03:39:53.324 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:39:53.466 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch83
2025-07-30 03:39:56.236 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 9.133e-03, size: 480, ETA: 2:25:11
2025-07-30 03:39:59.068 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.130e-03, size: 448, ETA: 2:25:07
2025-07-30 03:40:01.846 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.122s, data_time: 0.005s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 9.127e-03, size: 544, ETA: 2:25:04
2025-07-30 03:40:04.604 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.022s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 9.123e-03, size: 288, ETA: 2:25:01
2025-07-30 03:40:07.378 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.120e-03, size: 288, ETA: 2:24:58
2025-07-30 03:40:10.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 83/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.116e-03, size: 512, ETA: 2:24:55
2025-07-30 03:40:11.401 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:40:11.436 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch84
2025-07-30 03:40:14.228 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.112e-03, size: 320, ETA: 2:24:50
2025-07-30 03:40:17.138 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.108e-03, size: 512, ETA: 2:24:47
2025-07-30 03:40:20.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.105e-03, size: 384, ETA: 2:24:45
2025-07-30 03:40:22.946 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.101e-03, size: 512, ETA: 2:24:43
2025-07-30 03:40:25.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.098e-03, size: 384, ETA: 2:24:41
2025-07-30 03:40:28.539 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 84/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 9.094e-03, size: 480, ETA: 2:24:37
2025-07-30 03:40:29.783 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:40:29.924 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch85
2025-07-30 03:40:32.641 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.116s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.089e-03, size: 480, ETA: 2:24:32
2025-07-30 03:40:35.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.086e-03, size: 416, ETA: 2:24:28
2025-07-30 03:40:38.251 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 9.082e-03, size: 544, ETA: 2:24:24
2025-07-30 03:40:41.063 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 9.079e-03, size: 416, ETA: 2:24:21
2025-07-30 03:40:43.898 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.076e-03, size: 480, ETA: 2:24:17
2025-07-30 03:40:46.721 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 85/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.2, lr: 9.072e-03, size: 256, ETA: 2:24:14
2025-07-30 03:40:47.816 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:40:54.410 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:41:01.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:41:06.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3744
2025-07-30 03:41:07.541 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3576
2025-07-30 03:41:07.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1631
2025-07-30 03:41:07.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2984
2025-07-30 03:41:07.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:41:07.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:41:07.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.374
2025-07-30 03:41:07.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.358
2025-07-30 03:41:07.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.163
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.298
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:41:07.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:41:13.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:41:19.606 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:41:25.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:41:31.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:41:37.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:41:43.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:41:49.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:41:55.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:42:01.317 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:42:01.318 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.14
2025-07-30 03:42:01.318 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.30
2025-07-30 03:42:01.318 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:42:01.345 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.99 ms, Average inference time: 2.34 ms

2025-07-30 03:42:01.347 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:42:01.377 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:42:01.406 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch86
2025-07-30 03:42:03.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.120s, data_time: 0.010s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.067e-03, size: 544, ETA: 2:24:08
2025-07-30 03:42:06.777 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 9.064e-03, size: 416, ETA: 2:24:05
2025-07-30 03:42:09.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.060e-03, size: 448, ETA: 2:24:02
2025-07-30 03:42:12.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.057e-03, size: 544, ETA: 2:23:59
2025-07-30 03:42:15.387 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, 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: 0.9, lr: 9.053e-03, size: 256, ETA: 2:23:57
2025-07-30 03:42:18.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 86/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.050e-03, size: 512, ETA: 2:23:54
2025-07-30 03:42:19.401 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:42:19.608 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch87
2025-07-30 03:42:22.410 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 9.044e-03, size: 544, ETA: 2:23:49
2025-07-30 03:42:25.090 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.041e-03, size: 288, ETA: 2:23:45
2025-07-30 03:42:27.936 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.123s, data_time: 0.004s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.037e-03, size: 320, ETA: 2:23:41
2025-07-30 03:42:30.654 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 9.034e-03, size: 384, ETA: 2:23:38
2025-07-30 03:42:33.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.7, lr: 9.030e-03, size: 480, ETA: 2:23:36
2025-07-30 03:42:36.344 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 87/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.027e-03, size: 448, ETA: 2:23:34
2025-07-30 03:42:37.574 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:42:37.668 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch88
2025-07-30 03:42:40.452 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 8.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 9.022e-03, size: 576, ETA: 2:23:30
2025-07-30 03:42:43.346 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.018e-03, size: 256, ETA: 2:23:28
2025-07-30 03:42:46.087 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.014e-03, size: 512, ETA: 2:23:25
2025-07-30 03:42:48.854 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.011e-03, size: 256, ETA: 2:23:23
2025-07-30 03:42:51.634 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 9.007e-03, size: 448, ETA: 2:23:20
2025-07-30 03:42:54.557 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 88/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.004e-03, size: 416, ETA: 2:23:18
2025-07-30 03:42:55.712 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:42:55.750 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch89
2025-07-30 03:42:58.590 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 8.998e-03, size: 512, ETA: 2:23:15
2025-07-30 03:43:01.444 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 8.995e-03, size: 288, ETA: 2:23:14
2025-07-30 03:43:04.171 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.009s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.991e-03, size: 544, ETA: 2:23:12
2025-07-30 03:43:06.969 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.988e-03, size: 512, ETA: 2:23:09
2025-07-30 03:43:09.756 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 8.984e-03, size: 480, ETA: 2:23:07
2025-07-30 03:43:12.582 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 89/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 8.980e-03, size: 544, ETA: 2:23:04
2025-07-30 03:43:13.795 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:43:13.845 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch90
2025-07-30 03:43:16.678 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 8.975e-03, size: 384, ETA: 2:23:01
2025-07-30 03:43:19.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.972e-03, size: 576, ETA: 2:22:59
2025-07-30 03:43:22.344 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.968e-03, size: 448, ETA: 2:22:56
2025-07-30 03:43:25.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, 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: 8.964e-03, size: 384, ETA: 2:22:54
2025-07-30 03:43:27.972 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.961e-03, size: 320, ETA: 2:22:52
2025-07-30 03:43:30.703 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 90/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 8.957e-03, size: 256, ETA: 2:22:49
2025-07-30 03:43:32.039 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:43:38.391 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:43:43.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:43:47.504 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.2604
2025-07-30 03:43:47.892 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3527
2025-07-30 03:43:48.015 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1512
2025-07-30 03:43:48.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2548
2025-07-30 03:43:48.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:43:48.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:43:48.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.260
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.353
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.151
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.255
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:43:48.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:43:48.018 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:43:52.474 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:43:56.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:44:01.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:44:05.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:44:10.283 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:44:14.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:44:19.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:44:23.609 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:44:27.972 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:44:27.973 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.13
2025-07-30 03:44:27.973 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.25
2025-07-30 03:44:27.973 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:44:27.998 | 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

2025-07-30 03:44:27.999 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:44:28.032 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:44:28.061 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch91
2025-07-30 03:44:30.533 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.121s, data_time: 0.003s, total_loss: 7.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.4, lr: 8.952e-03, size: 576, ETA: 2:22:45
2025-07-30 03:44:33.384 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 8.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.3, lr: 8.948e-03, size: 320, ETA: 2:22:43
2025-07-30 03:44:36.106 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.011s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 8.944e-03, size: 384, ETA: 2:22:41
2025-07-30 03:44:38.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, 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: 8.941e-03, size: 416, ETA: 2:22:38
2025-07-30 03:44:41.658 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.937e-03, size: 256, ETA: 2:22:36
2025-07-30 03:44:44.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 91/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 8.933e-03, size: 512, ETA: 2:22:34
2025-07-30 03:44:45.629 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:44:45.674 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch92
2025-07-30 03:44:48.445 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.022s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.928e-03, size: 352, ETA: 2:22:30
2025-07-30 03:44:51.273 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 8.924e-03, size: 480, ETA: 2:22:28
2025-07-30 03:44:54.045 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.920e-03, size: 416, ETA: 2:22:25
2025-07-30 03:44:56.892 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.917e-03, size: 512, ETA: 2:22:23
2025-07-30 03:44:59.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.135s, 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: 8.913e-03, size: 288, ETA: 2:22:20
2025-07-30 03:45:02.579 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 92/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 8.909e-03, size: 320, ETA: 2:22:18
2025-07-30 03:45:03.807 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:45:03.868 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch93
2025-07-30 03:45:06.648 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 8.904e-03, size: 576, ETA: 2:22:15
2025-07-30 03:45:09.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.4, lr: 8.900e-03, size: 352, ETA: 2:22:13
2025-07-30 03:45:12.237 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 8.896e-03, size: 448, ETA: 2:22:10
2025-07-30 03:45:14.937 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.893e-03, size: 384, ETA: 2:22:08
2025-07-30 03:45:17.749 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.889e-03, size: 448, ETA: 2:22:06
2025-07-30 03:45:20.561 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 93/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.885e-03, size: 544, ETA: 2:22:04
2025-07-30 03:45:21.640 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:45:21.800 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch94
2025-07-30 03:45:24.503 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.126s, data_time: 0.011s, total_loss: 8.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 8.880e-03, size: 480, ETA: 2:21:59
2025-07-30 03:45:27.382 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.876e-03, size: 352, ETA: 2:21:57
2025-07-30 03:45:30.309 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.9, lr: 8.872e-03, size: 256, ETA: 2:21:55
2025-07-30 03:45:33.125 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.009s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.868e-03, size: 512, ETA: 2:21:53
2025-07-30 03:45:35.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.5Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 8.864e-03, size: 512, ETA: 2:21:50
2025-07-30 03:45:38.652 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 94/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 8.861e-03, size: 288, ETA: 2:21:47
2025-07-30 03:45:39.929 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:45:39.969 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch95
2025-07-30 03:45:42.800 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.855e-03, size: 256, ETA: 2:21:44
2025-07-30 03:45:45.622 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, 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: 8.851e-03, size: 288, ETA: 2:21:41
2025-07-30 03:45:48.412 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 8.847e-03, size: 288, ETA: 2:21:39
2025-07-30 03:45:51.082 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.844e-03, size: 288, ETA: 2:21:37
2025-07-30 03:45:53.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.136s, 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: 8.840e-03, size: 384, ETA: 2:21:35
2025-07-30 03:45:56.815 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 95/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 0.8, lr: 8.836e-03, size: 448, ETA: 2:21:33
2025-07-30 03:45:58.008 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:46:04.456 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:46:06.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:46:08.117 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3688
2025-07-30 03:46:08.387 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3916
2025-07-30 03:46:08.463 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2029
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3211
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.369
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.392
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.203
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.321
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:46:08.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:46:08.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:46:08.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:46:08.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:46:08.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:46:08.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:46:08.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:46:10.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:46:12.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:46:13.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:46:15.617 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:46:17.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:46:19.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:46:20.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:46:22.677 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:46:24.453 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:46:24.453 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.15
2025-07-30 03:46:24.453 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.32
2025-07-30 03:46:24.453 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:46:24.481 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.95 ms, Average inference time: 2.32 ms

2025-07-30 03:46:24.483 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:46:24.516 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:46:24.546 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch96
2025-07-30 03:46:26.938 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.118s, data_time: 0.031s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.830e-03, size: 384, ETA: 2:21:28
2025-07-30 03:46:29.682 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.043s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.826e-03, size: 384, ETA: 2:21:25
2025-07-30 03:46:32.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.007s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 8.823e-03, size: 288, ETA: 2:21:23
2025-07-30 03:46:35.395 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 8.9, iou_loss: 3.7, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 8.819e-03, size: 544, ETA: 2:21:20
2025-07-30 03:46:38.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 8.815e-03, size: 256, ETA: 2:21:17
2025-07-30 03:46:41.022 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 96/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.136s, data_time: 0.011s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.811e-03, size: 416, ETA: 2:21:15
2025-07-30 03:46:42.114 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:46:42.276 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch97
2025-07-30 03:46:44.992 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.131s, data_time: 0.037s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.805e-03, size: 384, ETA: 2:21:11
2025-07-30 03:46:47.845 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.802e-03, size: 288, ETA: 2:21:09
2025-07-30 03:46:50.723 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 8.798e-03, size: 448, ETA: 2:21:07
2025-07-30 03:46:53.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.131s, 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: 8.794e-03, size: 576, ETA: 2:21:04
2025-07-30 03:46:56.175 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.790e-03, size: 416, ETA: 2:21:02
2025-07-30 03:46:59.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 97/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.144s, data_time: 0.001s, total_loss: 9.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.7, cls_loss: 1.3, lr: 8.786e-03, size: 256, ETA: 2:21:01
2025-07-30 03:47:00.268 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:47:00.430 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch98
2025-07-30 03:47:03.201 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 8.780e-03, size: 480, ETA: 2:20:57
2025-07-30 03:47:06.105 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 8.776e-03, size: 352, ETA: 2:20:55
2025-07-30 03:47:08.763 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 8.772e-03, size: 544, ETA: 2:20:53
2025-07-30 03:47:11.561 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.009s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 8.768e-03, size: 512, ETA: 2:20:50
2025-07-30 03:47:14.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.765e-03, size: 416, ETA: 2:20:48
2025-07-30 03:47:17.141 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 98/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 8.761e-03, size: 576, ETA: 2:20:45
2025-07-30 03:47:18.345 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:47:18.386 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch99
2025-07-30 03:47:21.131 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.755e-03, size: 416, ETA: 2:20:41
2025-07-30 03:47:24.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.142s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.751e-03, size: 352, ETA: 2:20:40
2025-07-30 03:47:26.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.747e-03, size: 416, ETA: 2:20:38
2025-07-30 03:47:29.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.743e-03, size: 256, ETA: 2:20:36
2025-07-30 03:47:32.433 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.739e-03, size: 384, ETA: 2:20:32
2025-07-30 03:47:35.331 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 99/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.0, lr: 8.735e-03, size: 256, ETA: 2:20:29
2025-07-30 03:47:36.544 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:47:36.594 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch100
2025-07-30 03:47:39.284 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.121s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 8.729e-03, size: 416, ETA: 2:20:24
2025-07-30 03:47:42.114 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 10.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 5.9, cls_loss: 1.1, lr: 8.725e-03, size: 512, ETA: 2:20:22
2025-07-30 03:47:44.961 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 9.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 5.4, cls_loss: 1.1, lr: 8.721e-03, size: 512, ETA: 2:20:19
2025-07-30 03:47:47.745 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.717e-03, size: 512, ETA: 2:20:16
2025-07-30 03:47:50.457 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 8.713e-03, size: 480, ETA: 2:20:13
2025-07-30 03:47:53.197 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 100/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.709e-03, size: 352, ETA: 2:20:10
2025-07-30 03:47:54.583 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:48:00.919 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:48:04.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:48:06.725 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4328
2025-07-30 03:48:07.082 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3752
2025-07-30 03:48:07.212 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2173
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3418
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.433
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.375
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.217
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.342
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:48:07.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:48:07.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:48:07.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:48:07.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:48:07.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:48:07.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:48:07.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:48:10.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:48:12.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:48:15.879 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:48:18.728 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:48:21.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:48:24.492 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:48:27.360 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:48:30.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:48:33.122 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:48:33.122 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-07-30 03:48:33.122 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.34
2025-07-30 03:48:33.122 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:48:33.147 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.98 ms, Average inference time: 2.33 ms

2025-07-30 03:48:33.149 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:48:33.181 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:48:33.229 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch101
2025-07-30 03:48:35.661 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.119s, data_time: 0.017s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 8.703e-03, size: 288, ETA: 2:20:05
2025-07-30 03:48:38.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 8.699e-03, size: 448, ETA: 2:20:04
2025-07-30 03:48:41.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 8.695e-03, size: 288, ETA: 2:20:02
2025-07-30 03:48:44.278 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.691e-03, size: 288, ETA: 2:20:00
2025-07-30 03:48:47.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.9, lr: 8.687e-03, size: 384, ETA: 2:19:59
2025-07-30 03:48:49.987 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 101/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 9.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 5.0, cls_loss: 1.4, lr: 8.683e-03, size: 544, ETA: 2:19:57
2025-07-30 03:48:51.125 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:48:51.281 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch102
2025-07-30 03:48:54.049 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 8.677e-03, size: 384, ETA: 2:19:53
2025-07-30 03:48:56.826 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.673e-03, size: 288, ETA: 2:19:51
2025-07-30 03:48:59.719 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.3, lr: 8.669e-03, size: 512, ETA: 2:19:49
2025-07-30 03:49:02.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 8.665e-03, size: 448, ETA: 2:19:46
2025-07-30 03:49:05.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.661e-03, size: 480, ETA: 2:19:43
2025-07-30 03:49:08.024 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 102/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 8.657e-03, size: 256, ETA: 2:19:40
2025-07-30 03:49:09.331 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:49:09.431 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch103
2025-07-30 03:49:12.230 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.651e-03, size: 448, ETA: 2:19:35
2025-07-30 03:49:15.088 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.120s, 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: 8.647e-03, size: 512, ETA: 2:19:32
2025-07-30 03:49:17.752 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.119s, data_time: 0.009s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.643e-03, size: 384, ETA: 2:19:28
2025-07-30 03:49:20.552 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.007s, total_loss: 8.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 8.639e-03, size: 512, ETA: 2:19:25
2025-07-30 03:49:23.382 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.635e-03, size: 544, ETA: 2:19:22
2025-07-30 03:49:26.175 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 103/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.631e-03, size: 288, ETA: 2:19:19
2025-07-30 03:49:27.371 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:49:27.405 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch104
2025-07-30 03:49:30.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 8.625e-03, size: 256, ETA: 2:19:14
2025-07-30 03:49:33.022 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 8.620e-03, size: 480, ETA: 2:19:11
2025-07-30 03:49:35.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.616e-03, size: 416, ETA: 2:19:08
2025-07-30 03:49:38.572 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.612e-03, size: 416, ETA: 2:19:05
2025-07-30 03:49:41.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.608e-03, size: 576, ETA: 2:19:02
2025-07-30 03:49:44.300 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 104/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.604e-03, size: 544, ETA: 2:19:00
2025-07-30 03:49:45.501 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:49:45.655 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch105
2025-07-30 03:49:48.528 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.124s, 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: 8.598e-03, size: 576, ETA: 2:18:55
2025-07-30 03:49:51.231 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.120s, data_time: 0.011s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 8.594e-03, size: 576, ETA: 2:18:52
2025-07-30 03:49:54.022 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.119s, 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: 8.590e-03, size: 448, ETA: 2:18:48
2025-07-30 03:49:56.947 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 8.585e-03, size: 576, ETA: 2:18:45
2025-07-30 03:49:59.851 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.581e-03, size: 544, ETA: 2:18:42
2025-07-30 03:50:02.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 105/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.577e-03, size: 384, ETA: 2:18:39
2025-07-30 03:50:03.781 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:50:09.996 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:50:13.492 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:50:15.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4062
2025-07-30 03:50:16.067 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3748
2025-07-30 03:50:16.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2182
2025-07-30 03:50:16.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3331
2025-07-30 03:50:16.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:50:16.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:50:16.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.406
2025-07-30 03:50:16.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.375
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.218
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.333
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:50:16.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:50:16.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:50:18.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:50:21.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:50:24.294 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:50:26.920 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:50:29.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:50:32.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:50:34.940 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:50:37.569 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:50:40.290 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:50:40.291 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 03:50:40.291 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.33
2025-07-30 03:50:40.291 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:50:40.320 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 0.94 ms, Average inference time: 2.36 ms

2025-07-30 03:50:40.321 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:50:40.350 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:50:40.380 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch106
2025-07-30 03:50:42.899 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.118s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.571e-03, size: 512, ETA: 2:18:33
2025-07-30 03:50:45.791 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 8.567e-03, size: 288, ETA: 2:18:31
2025-07-30 03:50:48.598 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.563e-03, size: 544, ETA: 2:18:28
2025-07-30 03:50:51.246 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.123s, data_time: 0.004s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.558e-03, size: 352, ETA: 2:18:25
2025-07-30 03:50:54.152 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.137s, 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: 8.554e-03, size: 352, ETA: 2:18:23
2025-07-30 03:50:56.962 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 106/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 8.550e-03, size: 288, ETA: 2:18:20
2025-07-30 03:50:58.114 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:50:58.284 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch107
2025-07-30 03:51:01.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.544e-03, size: 288, ETA: 2:18:14
2025-07-30 03:51:03.897 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 8.540e-03, size: 544, ETA: 2:18:11
2025-07-30 03:51:06.777 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 8.535e-03, size: 480, ETA: 2:18:10
2025-07-30 03:51:09.562 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.3, lr: 8.531e-03, size: 352, ETA: 2:18:07
2025-07-30 03:51:12.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.527e-03, size: 544, ETA: 2:18:05
2025-07-30 03:51:15.183 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 107/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.4, lr: 8.523e-03, size: 352, ETA: 2:18:03
2025-07-30 03:51:16.400 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:51:16.509 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch108
2025-07-30 03:51:19.305 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 8.517e-03, size: 416, ETA: 2:17:59
2025-07-30 03:51:22.105 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.3, lr: 8.512e-03, size: 320, ETA: 2:17:57
2025-07-30 03:51:24.978 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.508e-03, size: 256, ETA: 2:17:54
2025-07-30 03:51:27.711 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.123s, 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: 8.504e-03, size: 384, ETA: 2:17:51
2025-07-30 03:51:30.510 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.500e-03, size: 352, ETA: 2:17:48
2025-07-30 03:51:33.328 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 108/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 8.495e-03, size: 544, ETA: 2:17:45
2025-07-30 03:51:34.539 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:51:34.627 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch109
2025-07-30 03:51:37.393 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.122s, 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: 8.489e-03, size: 512, ETA: 2:17:40
2025-07-30 03:51:40.103 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.5, lr: 8.485e-03, size: 288, ETA: 2:17:37
2025-07-30 03:51:43.003 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.480e-03, size: 512, ETA: 2:17:34
2025-07-30 03:51:45.742 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 8.476e-03, size: 416, ETA: 2:17:31
2025-07-30 03:51:48.580 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 8.472e-03, size: 416, ETA: 2:17:27
2025-07-30 03:51:51.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 109/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.468e-03, size: 384, ETA: 2:17:24
2025-07-30 03:51:52.596 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:51:52.630 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch110
2025-07-30 03:51:55.520 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.461e-03, size: 448, ETA: 2:17:20
2025-07-30 03:51:58.348 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 8.457e-03, size: 320, ETA: 2:17:17
2025-07-30 03:52:01.174 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 8.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 8.453e-03, size: 576, ETA: 2:17:15
2025-07-30 03:52:03.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.024s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 8.448e-03, size: 288, ETA: 2:17:12
2025-07-30 03:52:06.681 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 8.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.1, lr: 8.444e-03, size: 416, ETA: 2:17:09
2025-07-30 03:52:09.539 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 110/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 8.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.2, lr: 8.440e-03, size: 480, ETA: 2:17:06
2025-07-30 03:52:10.809 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:52:17.132 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:52:18.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:52:18.907 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4006
2025-07-30 03:52:19.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3749
2025-07-30 03:52:19.104 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2201
2025-07-30 03:52:19.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3319
2025-07-30 03:52:19.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.401
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.375
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.220
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.332
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:52:19.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:52:19.107 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:52:19.107 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:52:20.027 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:52:20.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:52:21.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:52:22.554 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:52:23.400 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:52:24.212 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:52:25.053 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:52:25.892 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:52:26.705 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:52:26.705 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-07-30 03:52:26.705 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.33
2025-07-30 03:52:26.706 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:52:26.713 | 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

2025-07-30 03:52:26.716 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:52:26.737 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:52:26.764 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch111
2025-07-30 03:52:29.224 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.113s, data_time: 0.031s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.433e-03, size: 256, ETA: 2:17:01
2025-07-30 03:52:32.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.131s, 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: 8.429e-03, size: 384, ETA: 2:16:58
2025-07-30 03:52:34.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.425e-03, size: 448, ETA: 2:16:56
2025-07-30 03:52:37.785 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 8.420e-03, size: 352, ETA: 2:16:53
2025-07-30 03:52:40.701 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.416e-03, size: 352, ETA: 2:16:51
2025-07-30 03:52:43.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 111/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.412e-03, size: 416, ETA: 2:16:48
2025-07-30 03:52:44.628 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:52:44.685 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch112
2025-07-30 03:52:47.447 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 8.405e-03, size: 416, ETA: 2:16:44
2025-07-30 03:52:50.185 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.123s, 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: 8.401e-03, size: 544, ETA: 2:16:41
2025-07-30 03:52:52.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 8.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 8.396e-03, size: 256, ETA: 2:16:38
2025-07-30 03:52:55.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.129s, 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: 8.392e-03, size: 384, ETA: 2:16:36
2025-07-30 03:52:58.635 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.134s, 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: 8.388e-03, size: 416, ETA: 2:16:33
2025-07-30 03:53:01.394 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 112/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.383e-03, size: 448, ETA: 2:16:30
2025-07-30 03:53:02.670 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:53:02.815 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch113
2025-07-30 03:53:05.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 8.377e-03, size: 544, ETA: 2:16:26
2025-07-30 03:53:08.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.121s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.372e-03, size: 416, ETA: 2:16:23
2025-07-30 03:53:11.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.121s, 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: 8.368e-03, size: 384, ETA: 2:16:19
2025-07-30 03:53:13.909 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 8.364e-03, size: 544, ETA: 2:16:16
2025-07-30 03:53:16.755 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.359e-03, size: 320, ETA: 2:16:12
2025-07-30 03:53:19.469 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 113/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.122s, data_time: 0.004s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 8.355e-03, size: 448, ETA: 2:16:09
2025-07-30 03:53:20.609 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:53:20.717 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch114
2025-07-30 03:53:23.476 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.124s, data_time: 0.004s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.348e-03, size: 448, ETA: 2:16:04
2025-07-30 03:53:26.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.012s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.344e-03, size: 448, ETA: 2:16:02
2025-07-30 03:53:29.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.135s, 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: 8.339e-03, size: 384, ETA: 2:16:00
2025-07-30 03:53:31.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.125s, data_time: 0.022s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 8.335e-03, size: 480, ETA: 2:15:57
2025-07-30 03:53:34.617 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.125s, data_time: 0.033s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 8.331e-03, size: 416, ETA: 2:15:54
2025-07-30 03:53:37.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 114/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.127s, data_time: 0.032s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.326e-03, size: 416, ETA: 2:15:51
2025-07-30 03:53:38.566 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:53:38.731 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch115
2025-07-30 03:53:41.522 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 8.320e-03, size: 480, ETA: 2:15:46
2025-07-30 03:53:44.333 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.127s, 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: 8.315e-03, size: 320, ETA: 2:15:43
2025-07-30 03:53:47.220 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.311e-03, size: 320, ETA: 2:15:40
2025-07-30 03:53:49.955 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.115s, 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: 8.306e-03, size: 480, ETA: 2:15:36
2025-07-30 03:53:52.873 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.6Gb, iter_time: 0.125s, data_time: 0.029s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 8.302e-03, size: 576, ETA: 2:15:33
2025-07-30 03:53:55.610 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 115/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.120s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 8.297e-03, size: 576, ETA: 2:15:30
2025-07-30 03:53:56.884 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:54:03.255 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:54:06.090 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:54:07.746 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4085
2025-07-30 03:54:07.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3705
2025-07-30 03:54:08.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1821
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3204
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.408
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.371
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.182
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.320
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:54:08.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:54:08.049 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:54:08.049 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:54:08.049 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:54:08.049 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:54:08.049 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:54:09.842 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:54:11.588 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:54:13.236 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:54:14.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:54:16.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:54:18.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:54:20.019 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:54:21.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:54:23.427 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:54:23.427 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-07-30 03:54:23.427 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.32
2025-07-30 03:54:23.427 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:54:23.487 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.42 ms, Average NMS time: 1.02 ms, Average inference time: 2.44 ms

2025-07-30 03:54:23.488 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:54:23.508 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:54:23.537 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch116
2025-07-30 03:54:25.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.111s, data_time: 0.007s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.291e-03, size: 416, ETA: 2:15:25
2025-07-30 03:54:28.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.286e-03, size: 512, ETA: 2:15:22
2025-07-30 03:54:31.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.282e-03, size: 256, ETA: 2:15:19
2025-07-30 03:54:34.414 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.277e-03, size: 256, ETA: 2:15:17
2025-07-30 03:54:37.300 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 8.273e-03, size: 288, ETA: 2:15:15
2025-07-30 03:54:40.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 116/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 8.268e-03, size: 384, ETA: 2:15:12
2025-07-30 03:54:41.251 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:54:41.297 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch117
2025-07-30 03:54:44.158 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.138s, 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: 8.262e-03, size: 512, ETA: 2:15:09
2025-07-30 03:54:46.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.257e-03, size: 320, ETA: 2:15:06
2025-07-30 03:54:49.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 8.253e-03, size: 480, ETA: 2:15:04
2025-07-30 03:54:52.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.141s, 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: 8.248e-03, size: 384, ETA: 2:15:02
2025-07-30 03:54:55.296 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.243e-03, size: 448, ETA: 2:15:00
2025-07-30 03:54:58.028 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 117/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 8.239e-03, size: 384, ETA: 2:14:58
2025-07-30 03:54:59.251 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:54:59.420 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch118
2025-07-30 03:55:02.187 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.232e-03, size: 416, ETA: 2:14:54
2025-07-30 03:55:05.124 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 8.228e-03, size: 320, ETA: 2:14:52
2025-07-30 03:55:07.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 7.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 8.223e-03, size: 512, ETA: 2:14:50
2025-07-30 03:55:10.702 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.219e-03, size: 384, ETA: 2:14:47
2025-07-30 03:55:13.501 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.214e-03, size: 576, ETA: 2:14:44
2025-07-30 03:55:16.371 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 118/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 8.209e-03, size: 256, ETA: 2:14:42
2025-07-30 03:55:17.534 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:55:17.650 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch119
2025-07-30 03:55:20.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.136s, 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: 8.203e-03, size: 320, ETA: 2:14:38
2025-07-30 03:55:23.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.198e-03, size: 320, ETA: 2:14:36
2025-07-30 03:55:25.983 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 8.194e-03, size: 256, ETA: 2:14:33
2025-07-30 03:55:28.833 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 8.189e-03, size: 544, ETA: 2:14:31
2025-07-30 03:55:31.619 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 8.184e-03, size: 320, ETA: 2:14:29
2025-07-30 03:55:34.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 119/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.142s, data_time: 0.001s, total_loss: 7.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 8.180e-03, size: 320, ETA: 2:14:27
2025-07-30 03:55:35.758 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:55:35.907 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch120
2025-07-30 03:55:38.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.173e-03, size: 576, ETA: 2:14:24
2025-07-30 03:55:41.447 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 8.168e-03, size: 256, ETA: 2:14:21
2025-07-30 03:55:44.248 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.164e-03, size: 288, ETA: 2:14:19
2025-07-30 03:55:47.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 8.159e-03, size: 576, ETA: 2:14:17
2025-07-30 03:55:49.922 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 8.155e-03, size: 288, ETA: 2:14:15
2025-07-30 03:55:52.784 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 120/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 8.150e-03, size: 416, ETA: 2:14:12
2025-07-30 03:55:53.990 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:56:00.427 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:56:03.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:56:05.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4512
2025-07-30 03:56:05.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4027
2025-07-30 03:56:05.501 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2146
2025-07-30 03:56:05.501 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3562
2025-07-30 03:56:05.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:56:05.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:56:05.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.451
2025-07-30 03:56:05.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.403
2025-07-30 03:56:05.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.215
2025-07-30 03:56:05.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.356
2025-07-30 03:56:05.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:56:05.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:56:05.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:56:05.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:56:05.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:56:05.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:56:05.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:56:05.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:56:05.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:56:07.768 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:56:10.074 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:56:12.396 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:56:14.622 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:56:16.908 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:56:19.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:56:21.463 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:56:23.714 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:56:25.963 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:56:25.963 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 03:56:25.964 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-30 03:56:25.964 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:56:25.989 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.96 ms, Average inference time: 2.33 ms

2025-07-30 03:56:25.991 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:56:26.011 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:56:26.040 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch121
2025-07-30 03:56:28.442 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.118s, data_time: 0.023s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 8.143e-03, size: 512, ETA: 2:14:08
2025-07-30 03:56:31.300 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.142s, data_time: 0.011s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 8.139e-03, size: 352, ETA: 2:14:06
2025-07-30 03:56:34.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.134e-03, size: 480, ETA: 2:14:04
2025-07-30 03:56:36.942 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 8.129e-03, size: 576, ETA: 2:14:02
2025-07-30 03:56:39.799 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.142s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 8.125e-03, size: 352, ETA: 2:14:01
2025-07-30 03:56:42.609 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 121/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.120e-03, size: 416, ETA: 2:13:58
2025-07-30 03:56:43.825 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:56:43.934 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch122
2025-07-30 03:56:46.716 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.7, lr: 8.113e-03, size: 288, ETA: 2:13:54
2025-07-30 03:56:49.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.108e-03, size: 576, ETA: 2:13:52
2025-07-30 03:56:52.308 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.104e-03, size: 480, ETA: 2:13:50
2025-07-30 03:56:55.115 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.099e-03, size: 320, ETA: 2:13:47
2025-07-30 03:56:57.883 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.094e-03, size: 416, ETA: 2:13:45
2025-07-30 03:57:00.714 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 122/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 8.090e-03, size: 288, ETA: 2:13:42
2025-07-30 03:57:01.961 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:57:02.065 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch123
2025-07-30 03:57:04.964 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 8.083e-03, size: 384, ETA: 2:13:38
2025-07-30 03:57:07.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.120s, 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: 8.078e-03, size: 352, ETA: 2:13:34
2025-07-30 03:57:10.558 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.074e-03, size: 352, ETA: 2:13:31
2025-07-30 03:57:13.268 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.123s, data_time: 0.013s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.069e-03, size: 416, ETA: 2:13:28
2025-07-30 03:57:16.134 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.125s, 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: 8.064e-03, size: 256, ETA: 2:13:25
2025-07-30 03:57:18.901 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 123/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.119s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 8.059e-03, size: 416, ETA: 2:13:21
2025-07-30 03:57:20.096 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:57:20.239 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch124
2025-07-30 03:57:23.004 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 8.053e-03, size: 480, ETA: 2:13:17
2025-07-30 03:57:25.870 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.3, lr: 8.048e-03, size: 352, ETA: 2:13:14
2025-07-30 03:57:28.607 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.006s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.8, lr: 8.043e-03, size: 544, ETA: 2:13:12
2025-07-30 03:57:31.573 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.038e-03, size: 448, ETA: 2:13:09
2025-07-30 03:57:34.356 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.034e-03, size: 544, ETA: 2:13:06
2025-07-30 03:57:37.199 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 124/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 8.029e-03, size: 416, ETA: 2:13:04
2025-07-30 03:57:38.401 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:57:38.551 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch125
2025-07-30 03:57:41.284 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 8.022e-03, size: 512, ETA: 2:12:59
2025-07-30 03:57:44.039 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.014s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.017e-03, size: 288, ETA: 2:12:56
2025-07-30 03:57:46.756 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.016s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.012e-03, size: 288, ETA: 2:12:53
2025-07-30 03:57:49.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.006s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 8.008e-03, size: 512, ETA: 2:12:50
2025-07-30 03:57:52.485 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.003e-03, size: 384, ETA: 2:12:47
2025-07-30 03:57:55.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 125/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 7.998e-03, size: 544, ETA: 2:12:44
2025-07-30 03:57:56.363 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:58:02.753 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:58:04.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 03:58:05.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4805
2025-07-30 03:58:05.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3989
2025-07-30 03:58:05.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2236
2025-07-30 03:58:05.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3677
2025-07-30 03:58:05.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 03:58:05.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 03:58:05.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.481
2025-07-30 03:58:05.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.399
2025-07-30 03:58:05.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.224
2025-07-30 03:58:05.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.368
2025-07-30 03:58:05.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 03:58:05.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 03:58:05.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 03:58:05.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 03:58:05.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 03:58:05.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 03:58:05.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 03:58:05.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 03:58:05.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 03:58:06.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 03:58:07.872 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 03:58:09.070 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 03:58:10.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 03:58:11.462 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 03:58:12.648 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 03:58:13.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 03:58:15.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 03:58:16.380 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 03:58:16.380 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 03:58:16.380 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-07-30 03:58:16.380 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 03:58:16.390 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.92 ms, Average inference time: 2.30 ms

2025-07-30 03:58:16.391 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:58:16.415 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:58:16.446 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch126
2025-07-30 03:58:18.829 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.112s, data_time: 0.005s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 7.991e-03, size: 416, ETA: 2:12:39
2025-07-30 03:58:21.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.986e-03, size: 448, ETA: 2:12:36
2025-07-30 03:58:24.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 7.982e-03, size: 544, ETA: 2:12:34
2025-07-30 03:58:27.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.120s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.6, lr: 7.977e-03, size: 448, ETA: 2:12:30
2025-07-30 03:58:30.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.972e-03, size: 448, ETA: 2:12:28
2025-07-30 03:58:33.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 126/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.967e-03, size: 288, ETA: 2:12:25
2025-07-30 03:58:34.346 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:58:34.450 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch127
2025-07-30 03:58:37.223 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.124s, data_time: 0.005s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.960e-03, size: 512, ETA: 2:12:21
2025-07-30 03:58:40.014 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 7.955e-03, size: 480, ETA: 2:12:18
2025-07-30 03:58:42.809 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.951e-03, size: 576, ETA: 2:12:15
2025-07-30 03:58:45.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.946e-03, size: 384, ETA: 2:12:11
2025-07-30 03:58:48.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.120s, data_time: 0.001s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 7.941e-03, size: 512, ETA: 2:12:08
2025-07-30 03:58:51.226 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 127/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.137s, 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: 7.936e-03, size: 320, ETA: 2:12:06
2025-07-30 03:58:52.384 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:58:52.555 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch128
2025-07-30 03:58:55.239 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 7.929e-03, size: 448, ETA: 2:12:01
2025-07-30 03:58:58.013 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.924e-03, size: 576, ETA: 2:11:58
2025-07-30 03:59:00.808 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.919e-03, size: 448, ETA: 2:11:56
2025-07-30 03:59:03.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 7.915e-03, size: 576, ETA: 2:11:53
2025-07-30 03:59:06.427 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, 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: 0.8, lr: 7.910e-03, size: 416, ETA: 2:11:50
2025-07-30 03:59:09.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 128/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.905e-03, size: 448, ETA: 2:11:47
2025-07-30 03:59:10.477 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:59:10.586 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch129
2025-07-30 03:59:13.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 7.898e-03, size: 384, ETA: 2:11:43
2025-07-30 03:59:16.197 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 7.893e-03, size: 416, ETA: 2:11:40
2025-07-30 03:59:18.937 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 7.888e-03, size: 256, ETA: 2:11:37
2025-07-30 03:59:21.684 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, 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: 7.883e-03, size: 384, ETA: 2:11:34
2025-07-30 03:59:24.566 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 7.878e-03, size: 384, ETA: 2:11:32
2025-07-30 03:59:27.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 129/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 7.873e-03, size: 544, ETA: 2:11:29
2025-07-30 03:59:28.638 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:59:28.715 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch130
2025-07-30 03:59:31.587 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.7, cls_loss: 1.2, lr: 7.866e-03, size: 480, ETA: 2:11:25
2025-07-30 03:59:34.349 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 8.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.0, lr: 7.861e-03, size: 416, ETA: 2:11:22
2025-07-30 03:59:37.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 7.857e-03, size: 288, ETA: 2:11:20
2025-07-30 03:59:39.984 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 7.852e-03, size: 416, ETA: 2:11:17
2025-07-30 03:59:42.735 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 7.847e-03, size: 480, ETA: 2:11:14
2025-07-30 03:59:45.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 130/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.011s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 7.842e-03, size: 352, ETA: 2:11:12
2025-07-30 03:59:46.858 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 03:59:53.256 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 03:59:58.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:00:01.593 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4147
2025-07-30 04:00:02.113 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4103
2025-07-30 04:00:02.205 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1638
2025-07-30 04:00:02.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3296
2025-07-30 04:00:02.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:00:02.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.415
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.410
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.164
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.330
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:00:02.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:00:02.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:00:02.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:00:06.354 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:00:10.396 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:00:14.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:00:18.592 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:00:22.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:00:26.670 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:00:30.681 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:00:34.734 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:00:38.832 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:00:38.833 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-07-30 04:00:38.833 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.33
2025-07-30 04:00:38.833 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:00:38.861 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.95 ms, Average inference time: 2.30 ms

2025-07-30 04:00:38.862 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:00:38.892 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:00:38.922 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch131
2025-07-30 04:00:41.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.121s, data_time: 0.030s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.835e-03, size: 576, ETA: 2:11:07
2025-07-30 04:00:44.137 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 7.830e-03, size: 352, ETA: 2:11:05
2025-07-30 04:00:46.951 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.133s, 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: 7.825e-03, size: 384, ETA: 2:11:03
2025-07-30 04:00:49.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 8.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 7.820e-03, size: 480, ETA: 2:11:00
2025-07-30 04:00:52.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.815e-03, size: 288, ETA: 2:10:57
2025-07-30 04:00:55.395 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 131/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.127s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.810e-03, size: 480, ETA: 2:10:55
2025-07-30 04:00:56.523 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:00:56.560 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch132
2025-07-30 04:00:59.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 7.803e-03, size: 320, ETA: 2:10:51
2025-07-30 04:01:02.239 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.122s, data_time: 0.018s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.798e-03, size: 288, ETA: 2:10:48
2025-07-30 04:01:04.936 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.125s, data_time: 0.021s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 7.793e-03, size: 416, ETA: 2:10:45
2025-07-30 04:01:07.726 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.788e-03, size: 480, ETA: 2:10:42
2025-07-30 04:01:10.567 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.012s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.783e-03, size: 256, ETA: 2:10:39
2025-07-30 04:01:13.442 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 132/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.138s, data_time: 0.022s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 7.778e-03, size: 576, ETA: 2:10:37
2025-07-30 04:01:14.603 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:01:14.737 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch133
2025-07-30 04:01:17.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.124s, data_time: 0.020s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.771e-03, size: 448, ETA: 2:10:33
2025-07-30 04:01:20.284 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 7.766e-03, size: 576, ETA: 2:10:29
2025-07-30 04:01:23.089 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.761e-03, size: 384, ETA: 2:10:27
2025-07-30 04:01:25.874 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 7.756e-03, size: 448, ETA: 2:10:24
2025-07-30 04:01:28.702 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 7.751e-03, size: 352, ETA: 2:10:21
2025-07-30 04:01:31.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 133/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.746e-03, size: 320, ETA: 2:10:19
2025-07-30 04:01:32.805 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:01:32.845 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch134
2025-07-30 04:01:35.572 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 7.739e-03, size: 544, ETA: 2:10:14
2025-07-30 04:01:38.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 7.734e-03, size: 416, ETA: 2:10:12
2025-07-30 04:01:41.236 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 7.729e-03, size: 576, ETA: 2:10:09
2025-07-30 04:01:44.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 7.724e-03, size: 576, ETA: 2:10:07
2025-07-30 04:01:46.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 7.719e-03, size: 384, ETA: 2:10:05
2025-07-30 04:01:49.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 134/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 7.714e-03, size: 256, ETA: 2:10:02
2025-07-30 04:01:50.904 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:01:50.964 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch135
2025-07-30 04:01:53.759 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.006s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.3, lr: 7.707e-03, size: 416, ETA: 2:09:58
2025-07-30 04:01:56.528 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.120s, data_time: 0.001s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 7.702e-03, size: 320, ETA: 2:09:55
2025-07-30 04:01:59.390 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.697e-03, size: 416, ETA: 2:09:52
2025-07-30 04:02:02.156 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 7.692e-03, size: 352, ETA: 2:09:50
2025-07-30 04:02:05.053 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.687e-03, size: 416, ETA: 2:09:48
2025-07-30 04:02:07.821 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 135/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.2, lr: 7.682e-03, size: 416, ETA: 2:09:46
2025-07-30 04:02:09.030 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:02:15.391 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:02:16.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:02:17.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4505
2025-07-30 04:02:17.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3956
2025-07-30 04:02:17.943 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2203
2025-07-30 04:02:17.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3555
2025-07-30 04:02:17.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:02:17.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:02:17.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.451
2025-07-30 04:02:17.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.396
2025-07-30 04:02:17.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.220
2025-07-30 04:02:17.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.355
2025-07-30 04:02:17.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:02:17.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:02:17.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:02:17.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:02:17.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:02:17.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:02:17.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:02:17.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:02:17.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:02:19.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:02:20.261 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:02:21.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:02:22.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:02:23.621 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:02:24.727 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:02:25.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:02:26.937 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:02:28.063 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:02:28.064 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 04:02:28.064 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-30 04:02:28.064 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:02:28.071 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.92 ms, Average inference time: 2.27 ms

2025-07-30 04:02:28.073 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:02:28.093 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:02:28.121 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch136
2025-07-30 04:02:30.725 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.120s, data_time: 0.003s, total_loss: 7.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 7.674e-03, size: 544, ETA: 2:09:41
2025-07-30 04:02:33.386 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.669e-03, size: 448, ETA: 2:09:38
2025-07-30 04:02:36.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.664e-03, size: 288, ETA: 2:09:35
2025-07-30 04:02:39.015 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 7.659e-03, size: 480, ETA: 2:09:33
2025-07-30 04:02:41.924 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.654e-03, size: 288, ETA: 2:09:30
2025-07-30 04:02:44.773 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 136/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 7.649e-03, size: 576, ETA: 2:09:27
2025-07-30 04:02:45.954 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:02:46.078 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch137
2025-07-30 04:02:48.899 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 7.642e-03, size: 544, ETA: 2:09:23
2025-07-30 04:02:51.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 7.637e-03, size: 352, ETA: 2:09:20
2025-07-30 04:02:54.554 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 7.632e-03, size: 448, ETA: 2:09:17
2025-07-30 04:02:57.329 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.627e-03, size: 320, ETA: 2:09:14
2025-07-30 04:03:00.248 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.621e-03, size: 320, ETA: 2:09:11
2025-07-30 04:03:03.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 137/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.119s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.616e-03, size: 512, ETA: 2:09:07
2025-07-30 04:03:04.268 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:03:04.306 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch138
2025-07-30 04:03:06.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 7.609e-03, size: 576, ETA: 2:09:03
2025-07-30 04:03:09.799 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.129s, 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: 7.604e-03, size: 384, ETA: 2:09:01
2025-07-30 04:03:12.669 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.599e-03, size: 480, ETA: 2:08:58
2025-07-30 04:03:15.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 7.594e-03, size: 384, ETA: 2:08:56
2025-07-30 04:03:18.375 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 7.589e-03, size: 384, ETA: 2:08:53
2025-07-30 04:03:21.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 138/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.584e-03, size: 320, ETA: 2:08:50
2025-07-30 04:03:22.403 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:03:22.562 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch139
2025-07-30 04:03:25.458 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.7Gb, iter_time: 0.121s, 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: 7.576e-03, size: 320, ETA: 2:08:46
2025-07-30 04:03:28.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.119s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.571e-03, size: 544, ETA: 2:08:42
2025-07-30 04:03:31.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 7.566e-03, size: 352, ETA: 2:08:39
2025-07-30 04:03:33.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 7.561e-03, size: 448, ETA: 2:08:36
2025-07-30 04:03:36.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.123s, data_time: 0.014s, total_loss: 8.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 1.0, lr: 7.556e-03, size: 480, ETA: 2:08:33
2025-07-30 04:03:39.387 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 139/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 7.551e-03, size: 320, ETA: 2:08:30
2025-07-30 04:03:40.603 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:03:40.646 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch140
2025-07-30 04:03:43.396 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 8.4, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 7.543e-03, size: 320, ETA: 2:08:26
2025-07-30 04:03:46.257 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 40/129, gpu mem: 1553Mb, 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: 0.8, lr: 7.538e-03, size: 512, ETA: 2:08:23
2025-07-30 04:03:49.145 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 7.533e-03, size: 256, ETA: 2:08:21
2025-07-30 04:03:51.953 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.008s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 7.528e-03, size: 416, ETA: 2:08:18
2025-07-30 04:03:54.934 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 8.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.9, cls_loss: 0.9, lr: 7.523e-03, size: 544, ETA: 2:08:16
2025-07-30 04:03:57.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 140/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.5, lr: 7.517e-03, size: 480, ETA: 2:08:13
2025-07-30 04:03:59.075 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:04:05.318 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:04:08.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:04:11.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4720
2025-07-30 04:04:11.439 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3706
2025-07-30 04:04:11.560 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2450
2025-07-30 04:04:11.561 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3625
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.472
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.371
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.245
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.363
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:04:11.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:04:11.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:04:11.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:04:11.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:04:11.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:04:11.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:04:14.406 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:04:17.160 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:04:19.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:04:22.823 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:04:25.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:04:28.421 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:04:31.252 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:04:34.128 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:04:37.256 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:04:37.257 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 04:04:37.257 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-30 04:04:37.257 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:04:37.282 | 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: 2.37 ms

2025-07-30 04:04:37.284 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:04:37.315 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:04:37.348 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch141
2025-07-30 04:04:39.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.117s, data_time: 0.013s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 7.510e-03, size: 480, ETA: 2:08:09
2025-07-30 04:04:42.629 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 7.505e-03, size: 320, ETA: 2:08:06
2025-07-30 04:04:45.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 7.500e-03, size: 352, ETA: 2:08:04
2025-07-30 04:04:48.306 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.7, lr: 7.494e-03, size: 576, ETA: 2:08:01
2025-07-30 04:04:51.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 7.489e-03, size: 512, ETA: 2:07:59
2025-07-30 04:04:54.114 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 141/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.132s, 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: 7.484e-03, size: 512, ETA: 2:07:56
2025-07-30 04:04:55.270 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:04:55.310 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch142
2025-07-30 04:04:58.053 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 7.477e-03, size: 384, ETA: 2:07:52
2025-07-30 04:05:00.948 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 7.471e-03, size: 416, ETA: 2:07:50
2025-07-30 04:05:03.787 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.466e-03, size: 352, ETA: 2:07:47
2025-07-30 04:05:06.621 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.461e-03, size: 448, ETA: 2:07:44
2025-07-30 04:05:09.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 7.456e-03, size: 288, ETA: 2:07:41
2025-07-30 04:05:12.216 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 142/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.451e-03, size: 352, ETA: 2:07:38
2025-07-30 04:05:13.422 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:05:13.577 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch143
2025-07-30 04:05:16.388 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.443e-03, size: 320, ETA: 2:07:34
2025-07-30 04:05:19.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.121s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 7.438e-03, size: 352, ETA: 2:07:31
2025-07-30 04:05:21.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.121s, data_time: 0.010s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 7.433e-03, size: 512, ETA: 2:07:27
2025-07-30 04:05:24.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 7.428e-03, size: 544, ETA: 2:07:25
2025-07-30 04:05:27.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.422e-03, size: 320, ETA: 2:07:23
2025-07-30 04:05:30.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 143/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.417e-03, size: 416, ETA: 2:07:21
2025-07-30 04:05:31.554 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:05:31.625 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch144
2025-07-30 04:05:34.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.410e-03, size: 576, ETA: 2:07:17
2025-07-30 04:05:37.222 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.404e-03, size: 544, ETA: 2:07:14
2025-07-30 04:05:39.930 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 7.399e-03, size: 288, ETA: 2:07:12
2025-07-30 04:05:42.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 7.394e-03, size: 512, ETA: 2:07:09
2025-07-30 04:05:45.566 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 7.389e-03, size: 480, ETA: 2:07:07
2025-07-30 04:05:48.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 144/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.384e-03, size: 576, ETA: 2:07:04
2025-07-30 04:05:49.508 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:05:49.573 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch145
2025-07-30 04:05:52.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.376e-03, size: 320, ETA: 2:07:01
2025-07-30 04:05:55.172 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.004s, total_loss: 8.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 0.9, lr: 7.371e-03, size: 512, ETA: 2:06:59
2025-07-30 04:05:58.042 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 8.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.0, lr: 7.365e-03, size: 480, ETA: 2:06:57
2025-07-30 04:06:00.806 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.360e-03, size: 576, ETA: 2:06:55
2025-07-30 04:06:03.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 7.355e-03, size: 384, ETA: 2:06:52
2025-07-30 04:06:06.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 145/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.137s, data_time: 0.006s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.350e-03, size: 352, ETA: 2:06:50
2025-07-30 04:06:07.478 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:06:13.985 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:06:16.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:06:19.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4370
2025-07-30 04:06:19.296 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4247
2025-07-30 04:06:19.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2195
2025-07-30 04:06:19.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3604
2025-07-30 04:06:19.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:06:19.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:06:19.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.437
2025-07-30 04:06:19.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.425
2025-07-30 04:06:19.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.220
2025-07-30 04:06:19.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.360
2025-07-30 04:06:19.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:06:19.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:06:19.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:06:19.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:06:19.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:06:19.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:06:19.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:06:19.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:06:19.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:06:21.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:06:24.312 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:06:26.709 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:06:29.150 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:06:31.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:06:34.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:06:36.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:06:38.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:06:41.337 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:06:41.338 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 04:06:41.338 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-30 04:06:41.338 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:06:41.363 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.97 ms, Average inference time: 2.35 ms

2025-07-30 04:06:41.365 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:06:41.391 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:06:41.440 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch146
2025-07-30 04:06:43.894 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.114s, data_time: 0.005s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 7.342e-03, size: 352, ETA: 2:06:45
2025-07-30 04:06:46.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.337e-03, size: 320, ETA: 2:06:43
2025-07-30 04:06:49.633 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.332e-03, size: 352, ETA: 2:06:40
2025-07-30 04:06:52.456 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.326e-03, size: 384, ETA: 2:06:37
2025-07-30 04:06:55.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.132s, 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: 7.321e-03, size: 352, ETA: 2:06:35
2025-07-30 04:06:58.190 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 146/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.316e-03, size: 512, ETA: 2:06:32
2025-07-30 04:06:59.356 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:06:59.526 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch147
2025-07-30 04:07:02.461 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.308e-03, size: 480, ETA: 2:06:28
2025-07-30 04:07:05.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 7.303e-03, size: 352, ETA: 2:06:25
2025-07-30 04:07:08.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.298e-03, size: 480, ETA: 2:06:22
2025-07-30 04:07:10.801 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.121s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 7.292e-03, size: 512, ETA: 2:06:19
2025-07-30 04:07:13.608 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, 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: 7.287e-03, size: 352, ETA: 2:06:16
2025-07-30 04:07:16.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 147/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.9, lr: 7.282e-03, size: 576, ETA: 2:06:13
2025-07-30 04:07:17.804 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:07:17.843 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch148
2025-07-30 04:07:20.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.121s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.274e-03, size: 480, ETA: 2:06:09
2025-07-30 04:07:23.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.269e-03, size: 416, ETA: 2:06:06
2025-07-30 04:07:26.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.263e-03, size: 352, ETA: 2:06:03
2025-07-30 04:07:28.933 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.258e-03, size: 320, ETA: 2:06:00
2025-07-30 04:07:31.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.134s, 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: 7.253e-03, size: 480, ETA: 2:05:58
2025-07-30 04:07:34.584 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 148/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 7.247e-03, size: 576, ETA: 2:05:56
2025-07-30 04:07:35.792 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:07:35.865 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch149
2025-07-30 04:07:38.656 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 7.240e-03, size: 512, ETA: 2:05:52
2025-07-30 04:07:41.504 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 8.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 7.234e-03, size: 320, ETA: 2:05:49
2025-07-30 04:07:44.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.229e-03, size: 448, ETA: 2:05:47
2025-07-30 04:07:47.113 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.224e-03, size: 384, ETA: 2:05:44
2025-07-30 04:07:49.930 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.218e-03, size: 416, ETA: 2:05:42
2025-07-30 04:07:52.623 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 149/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.119s, data_time: 0.024s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.213e-03, size: 448, ETA: 2:05:38
2025-07-30 04:07:53.821 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:07:53.859 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch150
2025-07-30 04:07:56.587 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.025s, total_loss: 8.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 7.205e-03, size: 448, ETA: 2:05:34
2025-07-30 04:07:59.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.012s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 7.200e-03, size: 576, ETA: 2:05:31
2025-07-30 04:08:02.144 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.195e-03, size: 416, ETA: 2:05:29
2025-07-30 04:08:04.914 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.189e-03, size: 384, ETA: 2:05:26
2025-07-30 04:08:07.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 7.184e-03, size: 256, ETA: 2:05:24
2025-07-30 04:08:10.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 150/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.179e-03, size: 288, ETA: 2:05:21
2025-07-30 04:08:11.738 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:08:18.261 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:08:22.671 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:08:25.907 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4560
2025-07-30 04:08:26.319 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4074
2025-07-30 04:08:26.482 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2121
2025-07-30 04:08:26.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3585
2025-07-30 04:08:26.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:08:26.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:08:26.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.456
2025-07-30 04:08:26.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.407
2025-07-30 04:08:26.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.212
2025-07-30 04:08:26.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.359
2025-07-30 04:08:26.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:08:26.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:08:26.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:08:26.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:08:26.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:08:26.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:08:26.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:08:26.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:08:26.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:08:30.672 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:08:34.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:08:38.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:08:42.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:08:46.153 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:08:49.849 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:08:53.567 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:08:57.209 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:09:00.928 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:09:00.929 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-07-30 04:09:00.929 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-30 04:09:00.929 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:09:00.956 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.96 ms, Average inference time: 2.31 ms

2025-07-30 04:09:00.957 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:09:00.988 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:09:01.017 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch151
2025-07-30 04:09:03.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.119s, data_time: 0.023s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 7.171e-03, size: 544, ETA: 2:05:17
2025-07-30 04:09:06.166 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 7.166e-03, size: 576, ETA: 2:05:14
2025-07-30 04:09:09.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 7.160e-03, size: 416, ETA: 2:05:12
2025-07-30 04:09:11.846 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.155e-03, size: 480, ETA: 2:05:10
2025-07-30 04:09:14.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.149e-03, size: 576, ETA: 2:05:08
2025-07-30 04:09:17.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 151/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 7.144e-03, size: 448, ETA: 2:05:06
2025-07-30 04:09:18.654 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:09:18.796 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch152
2025-07-30 04:09:21.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, 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: 7.136e-03, size: 256, ETA: 2:05:02
2025-07-30 04:09:24.351 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.131e-03, size: 384, ETA: 2:05:00
2025-07-30 04:09:27.184 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.126e-03, size: 288, ETA: 2:04:58
2025-07-30 04:09:29.981 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 7.120e-03, size: 576, ETA: 2:04:55
2025-07-30 04:09:32.750 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 100/129, gpu mem: 1553Mb, 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: 3.2, cls_loss: 1.0, lr: 7.115e-03, size: 576, ETA: 2:04:53
2025-07-30 04:09:35.525 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 152/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 7.109e-03, size: 416, ETA: 2:04:50
2025-07-30 04:09:36.688 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:09:36.745 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch153
2025-07-30 04:09:39.538 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.102e-03, size: 480, ETA: 2:04:46
2025-07-30 04:09:42.428 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.136s, data_time: 0.002s, 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: 352, ETA: 2:04:44
2025-07-30 04:09:45.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 7.091e-03, size: 384, ETA: 2:04:42
2025-07-30 04:09:48.152 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 7.085e-03, size: 288, ETA: 2:04:39
2025-07-30 04:09:51.028 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 7.080e-03, size: 352, ETA: 2:04:37
2025-07-30 04:09:53.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 153/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.075e-03, size: 320, ETA: 2:04:34
2025-07-30 04:09:54.938 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:09:54.981 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch154
2025-07-30 04:09:57.858 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.067e-03, size: 416, ETA: 2:04:31
2025-07-30 04:10:00.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.061e-03, size: 512, ETA: 2:04:28
2025-07-30 04:10:03.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 7.056e-03, size: 480, ETA: 2:04:26
2025-07-30 04:10:06.382 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 7.050e-03, size: 448, ETA: 2:04:23
2025-07-30 04:10:09.194 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.045e-03, size: 480, ETA: 2:04:20
2025-07-30 04:10:12.184 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 154/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 7.040e-03, size: 448, ETA: 2:04:18
2025-07-30 04:10:13.396 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:10:13.533 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch155
2025-07-30 04:10:16.288 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.122s, 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: 7.032e-03, size: 256, ETA: 2:04:13
2025-07-30 04:10:18.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 7.026e-03, size: 288, ETA: 2:04:10
2025-07-30 04:10:21.637 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.7, lr: 7.021e-03, size: 288, ETA: 2:04:07
2025-07-30 04:10:24.430 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 7.015e-03, size: 352, ETA: 2:04:05
2025-07-30 04:10:27.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.010e-03, size: 576, ETA: 2:04:02
2025-07-30 04:10:30.080 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 155/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 7.005e-03, size: 384, ETA: 2:04:00
2025-07-30 04:10:31.344 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:10:37.785 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:10:40.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:10:42.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4770
2025-07-30 04:10:42.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4259
2025-07-30 04:10:43.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2491
2025-07-30 04:10:43.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3840
2025-07-30 04:10:43.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:10:43.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:10:43.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.477
2025-07-30 04:10:43.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.426
2025-07-30 04:10:43.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.249
2025-07-30 04:10:43.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.384
2025-07-30 04:10:43.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:10:43.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:10:43.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:10:43.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:10:43.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:10:43.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:10:43.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:10:43.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:10:43.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:10:45.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:10:47.299 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:10:49.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:10:51.517 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:10:53.590 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:10:55.710 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:10:57.824 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:10:59.886 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:11:01.989 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:11:01.989 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-30 04:11:01.989 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.38
2025-07-30 04:11:01.989 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:11:02.014 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.94 ms, Average inference time: 2.33 ms

2025-07-30 04:11:02.016 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:11:02.044 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:11:02.074 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch156
2025-07-30 04:11:04.574 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.116s, data_time: 0.005s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 6.997e-03, size: 576, ETA: 2:03:55
2025-07-30 04:11:07.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.991e-03, size: 320, ETA: 2:03:53
2025-07-30 04:11:10.182 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.986e-03, size: 448, ETA: 2:03:50
2025-07-30 04:11:13.021 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.980e-03, size: 416, ETA: 2:03:48
2025-07-30 04:11:15.836 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 6.975e-03, size: 576, ETA: 2:03:45
2025-07-30 04:11:18.705 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 156/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, 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: 6.969e-03, size: 352, ETA: 2:03:43
2025-07-30 04:11:19.912 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:11:19.948 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch157
2025-07-30 04:11:22.801 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.135s, 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: 6.961e-03, size: 544, ETA: 2:03:39
2025-07-30 04:11:25.708 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.956e-03, size: 480, ETA: 2:03:37
2025-07-30 04:11:28.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.116s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.951e-03, size: 512, ETA: 2:03:33
2025-07-30 04:11:31.319 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.945e-03, size: 256, ETA: 2:03:31
2025-07-30 04:11:34.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 100/129, gpu mem: 1553Mb, 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: 3.3, cls_loss: 1.0, lr: 6.940e-03, size: 288, ETA: 2:03:28
2025-07-30 04:11:36.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 157/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 10.0, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 5.4, cls_loss: 0.9, lr: 6.934e-03, size: 576, ETA: 2:03:25
2025-07-30 04:11:37.970 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:11:38.005 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch158
2025-07-30 04:11:40.719 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.926e-03, size: 416, ETA: 2:03:21
2025-07-30 04:11:43.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.006s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 6.921e-03, size: 544, ETA: 2:03:18
2025-07-30 04:11:46.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 4.7, cls_loss: 1.0, lr: 6.915e-03, size: 512, ETA: 2:03:15
2025-07-30 04:11:49.017 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 6.910e-03, size: 480, ETA: 2:03:13
2025-07-30 04:11:51.812 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.6, lr: 6.904e-03, size: 448, ETA: 2:03:10
2025-07-30 04:11:54.723 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 158/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 6.899e-03, size: 576, ETA: 2:03:07
2025-07-30 04:11:55.982 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:11:56.021 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch159
2025-07-30 04:11:58.881 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 6.891e-03, size: 352, ETA: 2:03:04
2025-07-30 04:12:01.669 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 6.885e-03, size: 544, ETA: 2:03:02
2025-07-30 04:12:04.608 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.880e-03, size: 384, ETA: 2:03:00
2025-07-30 04:12:07.349 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 6.874e-03, size: 512, ETA: 2:02:58
2025-07-30 04:12:10.110 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.869e-03, size: 320, ETA: 2:02:56
2025-07-30 04:12:12.906 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 159/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.7, lr: 6.863e-03, size: 384, ETA: 2:02:54
2025-07-30 04:12:14.092 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:12:14.230 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch160
2025-07-30 04:12:16.965 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.006s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 6.855e-03, size: 480, ETA: 2:02:50
2025-07-30 04:12:19.752 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 7.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 6.850e-03, size: 576, ETA: 2:02:47
2025-07-30 04:12:22.483 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 6.844e-03, size: 416, ETA: 2:02:45
2025-07-30 04:12:25.216 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.839e-03, size: 384, ETA: 2:02:42
2025-07-30 04:12:27.990 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 6.833e-03, size: 480, ETA: 2:02:39
2025-07-30 04:12:30.806 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 160/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 6.828e-03, size: 544, ETA: 2:02:37
2025-07-30 04:12:32.179 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:12:38.491 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:12:40.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:12:41.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5008
2025-07-30 04:12:41.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4313
2025-07-30 04:12:41.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2152
2025-07-30 04:12:41.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3824
2025-07-30 04:12:41.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:12:41.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:12:41.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.501
2025-07-30 04:12:41.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.431
2025-07-30 04:12:41.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.215
2025-07-30 04:12:41.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.382
2025-07-30 04:12:41.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:12:41.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:12:41.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:12:41.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:12:41.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:12:41.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:12:41.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:12:41.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:12:41.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:12:42.713 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:12:43.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:12:45.290 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:12:46.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:12:47.817 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:12:49.051 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:12:50.308 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:12:51.622 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:12:52.885 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:12:52.885 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-30 04:12:52.886 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.38
2025-07-30 04:12:52.886 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:12:52.892 | 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

2025-07-30 04:12:52.895 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:12:52.916 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:12:52.944 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch161
2025-07-30 04:12:55.399 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.121s, data_time: 0.033s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.820e-03, size: 576, ETA: 2:02:33
2025-07-30 04:12:58.254 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.039s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.814e-03, size: 480, ETA: 2:02:30
2025-07-30 04:13:01.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 6.809e-03, size: 256, ETA: 2:02:28
2025-07-30 04:13:03.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.010s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 6.803e-03, size: 256, ETA: 2:02:25
2025-07-30 04:13:06.555 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.798e-03, size: 576, ETA: 2:02:23
2025-07-30 04:13:09.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 161/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 6.792e-03, size: 448, ETA: 2:02:20
2025-07-30 04:13:10.687 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:13:10.747 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch162
2025-07-30 04:13:13.424 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.784e-03, size: 544, ETA: 2:02:16
2025-07-30 04:13:16.158 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.125s, data_time: 0.013s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.778e-03, size: 320, ETA: 2:02:14
2025-07-30 04:13:18.938 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.122s, data_time: 0.011s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.773e-03, size: 448, ETA: 2:02:11
2025-07-30 04:13:21.806 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.139s, data_time: 0.017s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.767e-03, size: 480, ETA: 2:02:09
2025-07-30 04:13:24.549 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.125s, 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: 6.762e-03, size: 352, ETA: 2:02:06
2025-07-30 04:13:27.421 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 162/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 6.756e-03, size: 512, ETA: 2:02:03
2025-07-30 04:13:28.604 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:13:28.653 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch163
2025-07-30 04:13:31.314 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.123s, data_time: 0.012s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.748e-03, size: 352, ETA: 2:01:59
2025-07-30 04:13:34.256 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 6.743e-03, size: 448, ETA: 2:01:56
2025-07-30 04:13:37.017 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 6.737e-03, size: 384, ETA: 2:01:53
2025-07-30 04:13:39.746 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.731e-03, size: 256, ETA: 2:01:50
2025-07-30 04:13:42.620 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.1, lr: 6.726e-03, size: 576, ETA: 2:01:47
2025-07-30 04:13:45.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 163/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 6.720e-03, size: 576, ETA: 2:01:44
2025-07-30 04:13:46.545 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:13:46.581 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch164
2025-07-30 04:13:49.390 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, 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: 6.712e-03, size: 576, ETA: 2:01:40
2025-07-30 04:13:52.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.707e-03, size: 512, ETA: 2:01:38
2025-07-30 04:13:55.002 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.128s, 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: 6.701e-03, size: 320, ETA: 2:01:35
2025-07-30 04:13:57.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 6.696e-03, size: 320, ETA: 2:01:32
2025-07-30 04:14:00.570 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 6.690e-03, size: 416, ETA: 2:01:30
2025-07-30 04:14:03.418 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 164/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 6.684e-03, size: 480, ETA: 2:01:27
2025-07-30 04:14:04.663 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:14:04.699 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch165
2025-07-30 04:14:07.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 6.676e-03, size: 320, ETA: 2:01:24
2025-07-30 04:14:10.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.143s, data_time: 0.003s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 6.671e-03, size: 544, ETA: 2:01:22
2025-07-30 04:14:13.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 6.665e-03, size: 576, ETA: 2:01:20
2025-07-30 04:14:16.027 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.139s, 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: 6.659e-03, size: 576, ETA: 2:01:18
2025-07-30 04:14:18.923 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.141s, 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: 6.654e-03, size: 384, ETA: 2:01:16
2025-07-30 04:14:21.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 165/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.648e-03, size: 288, ETA: 2:01:14
2025-07-30 04:14:23.096 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:14:29.798 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:14:32.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:14:33.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4436
2025-07-30 04:14:33.454 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3859
2025-07-30 04:14:33.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2586
2025-07-30 04:14:33.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3627
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.444
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.386
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.259
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.363
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:14:33.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:14:33.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:14:33.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:14:33.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:14:33.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:14:33.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:14:34.869 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:14:36.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:14:37.482 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:14:38.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:14:40.075 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:14:41.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:14:42.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:14:44.040 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:14:45.299 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:14:45.300 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 04:14:45.300 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-30 04:14:45.300 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:14:45.309 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.94 ms, Average inference time: 2.30 ms

2025-07-30 04:14:45.310 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:14:45.334 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:14:45.364 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch166
2025-07-30 04:14:47.776 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.111s, data_time: 0.016s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 6.640e-03, size: 544, ETA: 2:01:09
2025-07-30 04:14:50.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.005s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 6.635e-03, size: 512, ETA: 2:01:06
2025-07-30 04:14:53.396 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.133s, 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: 6.629e-03, size: 320, ETA: 2:01:04
2025-07-30 04:14:56.234 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 6.623e-03, size: 544, ETA: 2:01:01
2025-07-30 04:14:59.026 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 6.618e-03, size: 544, ETA: 2:00:58
2025-07-30 04:15:01.781 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 166/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.020s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 6.612e-03, size: 544, ETA: 2:00:56
2025-07-30 04:15:02.972 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:15:03.075 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch167
2025-07-30 04:15:05.858 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 6.604e-03, size: 512, ETA: 2:00:51
2025-07-30 04:15:08.648 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.598e-03, size: 512, ETA: 2:00:49
2025-07-30 04:15:11.486 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.125s, 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: 6.593e-03, size: 512, ETA: 2:00:46
2025-07-30 04:15:14.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, 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: 6.587e-03, size: 288, ETA: 2:00:43
2025-07-30 04:15:17.158 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 6.582e-03, size: 576, ETA: 2:00:40
2025-07-30 04:15:20.024 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 167/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.121s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.6, lr: 6.576e-03, size: 288, ETA: 2:00:37
2025-07-30 04:15:21.146 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:15:21.332 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch168
2025-07-30 04:15:24.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.136s, 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: 6.568e-03, size: 288, ETA: 2:00:33
2025-07-30 04:15:26.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 6.562e-03, size: 576, ETA: 2:00:30
2025-07-30 04:15:29.648 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 8.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.2, lr: 6.557e-03, size: 320, ETA: 2:00:28
2025-07-30 04:15:32.551 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.551e-03, size: 544, ETA: 2:00:26
2025-07-30 04:15:35.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 6.545e-03, size: 352, ETA: 2:00:23
2025-07-30 04:15:38.014 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 168/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.010s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 6.540e-03, size: 320, ETA: 2:00:20
2025-07-30 04:15:39.239 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:15:39.343 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch169
2025-07-30 04:15:42.292 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 6.531e-03, size: 256, ETA: 2:00:17
2025-07-30 04:15:45.162 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.526e-03, size: 448, ETA: 2:00:14
2025-07-30 04:15:48.022 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 6.520e-03, size: 448, ETA: 2:00:11
2025-07-30 04:15:50.767 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 6.515e-03, size: 448, ETA: 2:00:08
2025-07-30 04:15:53.522 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 6.509e-03, size: 480, ETA: 2:00:05
2025-07-30 04:15:56.416 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 169/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 6.503e-03, size: 384, ETA: 2:00:03
2025-07-30 04:15:57.634 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:15:57.670 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch170
2025-07-30 04:16:00.470 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.3, lr: 6.495e-03, size: 416, ETA: 1:59:59
2025-07-30 04:16:03.230 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.125s, data_time: 0.012s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 6.489e-03, size: 480, ETA: 1:59:56
2025-07-30 04:16:05.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.126s, data_time: 0.025s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.484e-03, size: 480, ETA: 1:59:54
2025-07-30 04:16:08.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.007s, total_loss: 8.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.2, lr: 6.478e-03, size: 544, ETA: 1:59:52
2025-07-30 04:16:11.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.8Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 6.472e-03, size: 448, ETA: 1:59:49
2025-07-30 04:16:14.483 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 170/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.135s, data_time: 0.036s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 6.467e-03, size: 288, ETA: 1:59:47
2025-07-30 04:16:15.658 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:16:22.073 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:16:27.134 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:16:30.747 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4806
2025-07-30 04:16:31.389 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4035
2025-07-30 04:16:31.445 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2348
2025-07-30 04:16:31.445 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3730
2025-07-30 04:16:31.445 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.481
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.403
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.235
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.373
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:16:31.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:16:31.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:16:31.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:16:31.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:16:35.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:16:40.119 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:16:44.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:16:48.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:16:53.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:16:57.620 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:17:01.877 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:17:06.134 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:17:10.419 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:17:10.419 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-07-30 04:17:10.419 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-07-30 04:17:10.420 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:17:10.445 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.99 ms, Average inference time: 2.33 ms

2025-07-30 04:17:10.446 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:17:10.482 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:17:10.523 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch171
2025-07-30 04:17:12.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.114s, data_time: 0.026s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 6.459e-03, size: 352, ETA: 1:59:42
2025-07-30 04:17:15.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.139s, data_time: 0.013s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 6.453e-03, size: 448, ETA: 1:59:40
2025-07-30 04:17:18.521 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.017s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 6.447e-03, size: 288, ETA: 1:59:38
2025-07-30 04:17:21.244 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 6.442e-03, size: 320, ETA: 1:59:35
2025-07-30 04:17:24.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 6.436e-03, size: 416, ETA: 1:59:33
2025-07-30 04:17:26.983 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 171/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.430e-03, size: 416, ETA: 1:59:31
2025-07-30 04:17:28.143 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:17:28.311 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch172
2025-07-30 04:17:31.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 6.422e-03, size: 352, ETA: 1:59:27
2025-07-30 04:17:33.844 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.416e-03, size: 544, ETA: 1:59:25
2025-07-30 04:17:36.612 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 6.411e-03, size: 384, ETA: 1:59:22
2025-07-30 04:17:39.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.134s, 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: 6.405e-03, size: 512, ETA: 1:59:20
2025-07-30 04:17:42.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 6.399e-03, size: 384, ETA: 1:59:17
2025-07-30 04:17:45.075 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 172/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.394e-03, size: 512, ETA: 1:59:14
2025-07-30 04:17:46.311 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:17:46.424 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch173
2025-07-30 04:17:49.310 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.385e-03, size: 512, ETA: 1:59:10
2025-07-30 04:17:52.285 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.380e-03, size: 544, ETA: 1:59:07
2025-07-30 04:17:55.058 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.374e-03, size: 480, ETA: 1:59:04
2025-07-30 04:17:57.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 6.368e-03, size: 512, ETA: 1:59:01
2025-07-30 04:18:00.552 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 6.363e-03, size: 352, ETA: 1:58:58
2025-07-30 04:18:03.414 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 173/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, 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: 6.357e-03, size: 288, ETA: 1:58:56
2025-07-30 04:18:04.643 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:18:04.699 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch174
2025-07-30 04:18:07.492 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 6.349e-03, size: 416, ETA: 1:58:52
2025-07-30 04:18:10.382 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.136s, 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: 6.343e-03, size: 512, ETA: 1:58:49
2025-07-30 04:18:13.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 6.337e-03, size: 256, ETA: 1:58:47
2025-07-30 04:18:15.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.331e-03, size: 448, ETA: 1:58:44
2025-07-30 04:18:18.750 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 6.326e-03, size: 512, ETA: 1:58:41
2025-07-30 04:18:21.511 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 174/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 6.320e-03, size: 512, ETA: 1:58:38
2025-07-30 04:18:22.704 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:18:22.865 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch175
2025-07-30 04:18:25.723 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 6.312e-03, size: 352, ETA: 1:58:34
2025-07-30 04:18:28.451 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.114s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.306e-03, size: 320, ETA: 1:58:31
2025-07-30 04:18:31.283 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.123s, 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: 6.300e-03, size: 256, ETA: 1:58:28
2025-07-30 04:18:34.122 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.295e-03, size: 512, ETA: 1:58:25
2025-07-30 04:18:36.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.289e-03, size: 384, ETA: 1:58:23
2025-07-30 04:18:39.840 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 175/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 6.283e-03, size: 512, ETA: 1:58:21
2025-07-30 04:18:41.046 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:18:47.531 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:18:49.102 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:18:49.887 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4616
2025-07-30 04:18:50.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4259
2025-07-30 04:18:50.139 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2292
2025-07-30 04:18:50.139 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3723
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.462
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.426
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.229
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.372
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:18:50.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:18:50.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:18:50.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:18:50.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:18:50.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:18:50.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:18:51.199 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:18:52.233 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:18:53.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:18:54.232 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:18:55.256 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:18:56.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:18:57.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:18:58.306 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:18:59.333 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:18:59.333 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 04:18:59.333 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-07-30 04:18:59.333 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:18:59.341 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.34 ms, Average NMS time: 0.91 ms, Average inference time: 2.25 ms

2025-07-30 04:18:59.346 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:18:59.373 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:18:59.402 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch176
2025-07-30 04:19:01.900 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.117s, data_time: 0.025s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 6.275e-03, size: 384, ETA: 1:58:16
2025-07-30 04:19:04.684 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 6.269e-03, size: 512, ETA: 1:58:14
2025-07-30 04:19:07.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 6.263e-03, size: 384, ETA: 1:58:11
2025-07-30 04:19:10.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 6.258e-03, size: 256, ETA: 1:58:08
2025-07-30 04:19:13.209 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.132s, 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: 6.252e-03, size: 288, ETA: 1:58:06
2025-07-30 04:19:15.994 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 176/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.3, lr: 6.246e-03, size: 256, ETA: 1:58:03
2025-07-30 04:19:17.166 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:19:17.336 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch177
2025-07-30 04:19:20.105 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 6.238e-03, size: 256, ETA: 1:57:59
2025-07-30 04:19:22.957 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.232e-03, size: 480, ETA: 1:57:56
2025-07-30 04:19:25.758 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 6.227e-03, size: 480, ETA: 1:57:53
2025-07-30 04:19:28.573 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.131s, 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: 6.221e-03, size: 384, ETA: 1:57:51
2025-07-30 04:19:31.367 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 6.215e-03, size: 384, ETA: 1:57:48
2025-07-30 04:19:34.036 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 177/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.209e-03, size: 320, ETA: 1:57:46
2025-07-30 04:19:35.376 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:19:35.410 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch178
2025-07-30 04:19:38.239 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 6.201e-03, size: 576, ETA: 1:57:42
2025-07-30 04:19:40.995 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 6.195e-03, size: 416, ETA: 1:57:39
2025-07-30 04:19:43.793 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.129s, 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: 6.190e-03, size: 576, ETA: 1:57:37
2025-07-30 04:19:46.556 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, 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: 6.184e-03, size: 288, ETA: 1:57:34
2025-07-30 04:19:49.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 6.178e-03, size: 512, ETA: 1:57:31
2025-07-30 04:19:52.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 178/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 6.172e-03, size: 448, ETA: 1:57:29
2025-07-30 04:19:53.401 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:19:53.435 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch179
2025-07-30 04:19:56.226 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 6.164e-03, size: 416, ETA: 1:57:25
2025-07-30 04:19:58.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.004s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.158e-03, size: 512, ETA: 1:57:23
2025-07-30 04:20:01.755 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.021s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 6.152e-03, size: 320, ETA: 1:57:20
2025-07-30 04:20:04.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 6.147e-03, size: 544, ETA: 1:57:18
2025-07-30 04:20:07.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 6.141e-03, size: 416, ETA: 1:57:15
2025-07-30 04:20:10.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 179/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 6.135e-03, size: 512, ETA: 1:57:13
2025-07-30 04:20:11.516 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:20:11.575 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch180
2025-07-30 04:20:14.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 6.127e-03, size: 448, ETA: 1:57:10
2025-07-30 04:20:17.263 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 6.121e-03, size: 544, ETA: 1:57:07
2025-07-30 04:20:20.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.134s, 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: 6.115e-03, size: 352, ETA: 1:57:05
2025-07-30 04:20:22.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 6.110e-03, size: 576, ETA: 1:57:02
2025-07-30 04:20:25.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.0, lr: 6.104e-03, size: 256, ETA: 1:57:00
2025-07-30 04:20:28.784 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 180/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.098e-03, size: 512, ETA: 1:56:58
2025-07-30 04:20:30.037 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:20:36.490 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:20:37.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:20:37.775 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4672
2025-07-30 04:20:37.894 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3756
2025-07-30 04:20:37.948 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2341
2025-07-30 04:20:37.949 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3590
2025-07-30 04:20:37.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:20:37.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:20:37.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.467
2025-07-30 04:20:37.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.376
2025-07-30 04:20:37.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.234
2025-07-30 04:20:37.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.359
2025-07-30 04:20:37.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:20:37.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:20:37.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:20:37.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:20:37.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:20:37.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:20:37.955 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:20:37.955 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:20:37.956 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:20:38.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:20:39.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:20:39.858 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:20:40.454 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:20:41.090 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:20:41.689 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:20:42.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:20:42.917 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:20:43.515 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:20:43.515 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 04:20:43.515 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-07-30 04:20:43.515 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:20:43.522 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.93 ms, Average inference time: 2.33 ms

2025-07-30 04:20:43.523 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:20:43.547 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:20:43.573 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch181
2025-07-30 04:20:46.023 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.121s, data_time: 0.012s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 6.090e-03, size: 416, ETA: 1:56:54
2025-07-30 04:20:48.883 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.084e-03, size: 480, ETA: 1:56:51
2025-07-30 04:20:51.620 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.078e-03, size: 288, ETA: 1:56:49
2025-07-30 04:20:54.334 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.011s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 6.072e-03, size: 256, ETA: 1:56:46
2025-07-30 04:20:57.134 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.021s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.067e-03, size: 448, ETA: 1:56:44
2025-07-30 04:21:00.045 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 181/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.143s, data_time: 0.012s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 6.061e-03, size: 384, ETA: 1:56:42
2025-07-30 04:21:01.298 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:21:01.394 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch182
2025-07-30 04:21:04.123 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 6.053e-03, size: 256, ETA: 1:56:39
2025-07-30 04:21:07.042 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.138s, 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: 6.047e-03, size: 256, ETA: 1:56:36
2025-07-30 04:21:09.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 6.041e-03, size: 352, ETA: 1:56:34
2025-07-30 04:21:12.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.134s, 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: 6.035e-03, size: 512, ETA: 1:56:31
2025-07-30 04:21:15.532 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 6.029e-03, size: 448, ETA: 1:56:29
2025-07-30 04:21:18.374 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 182/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 0.9, lr: 6.024e-03, size: 416, ETA: 1:56:26
2025-07-30 04:21:19.532 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:21:19.612 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch183
2025-07-30 04:21:22.367 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.015e-03, size: 288, ETA: 1:56:22
2025-07-30 04:21:25.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 6.009e-03, size: 512, ETA: 1:56:20
2025-07-30 04:21:28.020 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, 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: 1.0, lr: 6.004e-03, size: 288, ETA: 1:56:18
2025-07-30 04:21:30.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.998e-03, size: 512, ETA: 1:56:15
2025-07-30 04:21:33.752 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.7, cls_loss: 1.0, lr: 5.992e-03, size: 352, ETA: 1:56:13
2025-07-30 04:21:36.725 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 183/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.145s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.986e-03, size: 448, ETA: 1:56:11
2025-07-30 04:21:37.885 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:21:37.924 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch184
2025-07-30 04:21:40.659 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.978e-03, size: 416, ETA: 1:56:07
2025-07-30 04:21:43.497 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.972e-03, size: 256, ETA: 1:56:05
2025-07-30 04:21:46.364 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 60/129, gpu mem: 1553Mb, 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: 2.5, cls_loss: 0.9, lr: 5.966e-03, size: 352, ETA: 1:56:02
2025-07-30 04:21:49.003 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.128s, data_time: 0.032s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.961e-03, size: 576, ETA: 1:56:00
2025-07-30 04:21:51.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 5.955e-03, size: 288, ETA: 1:55:57
2025-07-30 04:21:54.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 184/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.044s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 5.949e-03, size: 256, ETA: 1:55:55
2025-07-30 04:21:55.701 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:21:55.770 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch185
2025-07-30 04:21:58.496 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.011s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.941e-03, size: 512, ETA: 1:55:51
2025-07-30 04:22:01.339 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.129s, 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: 5.935e-03, size: 256, ETA: 1:55:48
2025-07-30 04:22:04.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 5.929e-03, size: 416, ETA: 1:55:45
2025-07-30 04:22:07.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.923e-03, size: 320, ETA: 1:55:42
2025-07-30 04:22:09.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 5.917e-03, size: 512, ETA: 1:55:39
2025-07-30 04:22:12.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 185/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.0, lr: 5.912e-03, size: 544, ETA: 1:55:37
2025-07-30 04:22:13.924 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:22:20.552 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:22:23.785 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:22:26.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4695
2025-07-30 04:22:26.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4195
2025-07-30 04:22:26.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2268
2025-07-30 04:22:26.537 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3719
2025-07-30 04:22:26.537 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:22:26.537 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.469
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.419
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.227
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.372
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:22:26.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:22:26.539 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:22:26.539 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:22:29.286 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:22:32.060 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:22:34.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:22:37.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:22:40.267 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:22:42.989 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:22:45.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:22:48.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:22:51.236 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:22:51.236 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-07-30 04:22:51.237 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-07-30 04:22:51.237 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:22:51.261 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.94 ms, Average inference time: 2.32 ms

2025-07-30 04:22:51.263 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:22:51.291 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:22:51.321 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch186
2025-07-30 04:22:53.822 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.111s, data_time: 0.027s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.903e-03, size: 480, ETA: 1:55:32
2025-07-30 04:22:56.552 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 5.897e-03, size: 576, ETA: 1:55:29
2025-07-30 04:22:59.425 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.892e-03, size: 352, ETA: 1:55:26
2025-07-30 04:23:02.263 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.886e-03, size: 448, ETA: 1:55:24
2025-07-30 04:23:05.228 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.880e-03, size: 256, ETA: 1:55:22
2025-07-30 04:23:08.073 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 186/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.874e-03, size: 256, ETA: 1:55:19
2025-07-30 04:23:09.256 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:23:09.290 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch187
2025-07-30 04:23:12.118 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 5.866e-03, size: 352, ETA: 1:55:16
2025-07-30 04:23:14.824 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.020s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 5.860e-03, size: 416, ETA: 1:55:13
2025-07-30 04:23:17.669 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.854e-03, size: 544, ETA: 1:55:11
2025-07-30 04:23:20.416 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.125s, 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: 5.848e-03, size: 288, ETA: 1:55:08
2025-07-30 04:23:23.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.843e-03, size: 288, ETA: 1:55:05
2025-07-30 04:23:25.946 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 187/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.837e-03, size: 512, ETA: 1:55:03
2025-07-30 04:23:27.119 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:23:27.261 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch188
2025-07-30 04:23:30.104 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.828e-03, size: 512, ETA: 1:54:59
2025-07-30 04:23:32.959 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 40/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 5.822e-03, size: 256, ETA: 1:54:57
2025-07-30 04:23:35.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 5.817e-03, size: 480, ETA: 1:54:54
2025-07-30 04:23:38.730 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.811e-03, size: 384, ETA: 1:54:51
2025-07-30 04:23:41.473 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, 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: 5.805e-03, size: 544, ETA: 1:54:49
2025-07-30 04:23:44.281 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 188/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.011s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.799e-03, size: 448, ETA: 1:54:47
2025-07-30 04:23:45.522 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:23:45.556 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch189
2025-07-30 04:23:48.438 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 5.791e-03, size: 480, ETA: 1:54:43
2025-07-30 04:23:51.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 5.785e-03, size: 576, ETA: 1:54:41
2025-07-30 04:23:54.022 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 5.779e-03, size: 544, ETA: 1:54:39
2025-07-30 04:23:56.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.773e-03, size: 352, ETA: 1:54:36
2025-07-30 04:23:59.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.132s, 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: 5.767e-03, size: 576, ETA: 1:54:34
2025-07-30 04:24:02.367 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 189/600, iter: 120/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 5.762e-03, size: 320, ETA: 1:54:31
2025-07-30 04:24:03.615 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:24:03.706 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch190
2025-07-30 04:24:06.396 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.753e-03, size: 448, ETA: 1:54:28
2025-07-30 04:24:09.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 8.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 0.9, lr: 5.747e-03, size: 576, ETA: 1:54:25
2025-07-30 04:24:12.023 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, 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: 5.742e-03, size: 448, ETA: 1:54:23
2025-07-30 04:24:14.792 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.018s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 5.736e-03, size: 352, ETA: 1:54:20
2025-07-30 04:24:17.636 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.730e-03, size: 448, ETA: 1:54:18
2025-07-30 04:24:20.449 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 190/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.130s, 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: 5.724e-03, size: 288, ETA: 1:54:15
2025-07-30 04:24:21.600 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:24:28.062 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:24:32.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:24:35.422 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4900
2025-07-30 04:24:36.070 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4275
2025-07-30 04:24:36.189 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2637
2025-07-30 04:24:36.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3938
2025-07-30 04:24:36.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:24:36.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:24:36.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.490
2025-07-30 04:24:36.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.428
2025-07-30 04:24:36.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.264
2025-07-30 04:24:36.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.394
2025-07-30 04:24:36.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:24:36.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:24:36.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:24:36.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:24:36.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:24:36.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:24:36.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:24:36.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:24:36.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:24:39.914 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:24:43.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:24:47.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:24:50.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:24:54.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:24:58.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:25:01.704 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:25:05.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:25:08.999 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:25:08.999 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-30 04:25:09.000 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-30 04:25:09.000 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:25:09.026 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.99 ms, Average inference time: 2.37 ms

2025-07-30 04:25:09.026 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:25:09.051 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:25:09.080 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch191
2025-07-30 04:25:11.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.118s, data_time: 0.040s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.716e-03, size: 416, ETA: 1:54:11
2025-07-30 04:25:14.386 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.028s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.710e-03, size: 288, ETA: 1:54:08
2025-07-30 04:25:17.215 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.704e-03, size: 288, ETA: 1:54:06
2025-07-30 04:25:19.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 5.698e-03, size: 416, ETA: 1:54:04
2025-07-30 04:25:22.812 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.692e-03, size: 256, ETA: 1:54:02
2025-07-30 04:25:25.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 191/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.686e-03, size: 448, ETA: 1:53:59
2025-07-30 04:25:26.853 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:25:26.980 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch192
2025-07-30 04:25:29.858 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.678e-03, size: 576, ETA: 1:53:56
2025-07-30 04:25:32.696 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.672e-03, size: 320, ETA: 1:53:53
2025-07-30 04:25:35.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.130s, 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: 5.666e-03, size: 320, ETA: 1:53:51
2025-07-30 04:25:38.182 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.661e-03, size: 416, ETA: 1:53:48
2025-07-30 04:25:41.004 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 8.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.2, lr: 5.655e-03, size: 320, ETA: 1:53:46
2025-07-30 04:25:43.675 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 192/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 5.649e-03, size: 384, ETA: 1:53:43
2025-07-30 04:25:44.870 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:25:44.970 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch193
2025-07-30 04:25:47.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.640e-03, size: 416, ETA: 1:53:39
2025-07-30 04:25:50.441 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.635e-03, size: 576, ETA: 1:53:37
2025-07-30 04:25:53.313 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 60/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.131s, data_time: 0.036s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.629e-03, size: 288, ETA: 1:53:34
2025-07-30 04:25:56.089 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, 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: 5.623e-03, size: 512, ETA: 1:53:32
2025-07-30 04:25:58.956 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 100/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.142s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.617e-03, size: 416, ETA: 1:53:30
2025-07-30 04:26:01.830 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 193/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.142s, data_time: 0.001s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 5.611e-03, size: 320, ETA: 1:53:28
2025-07-30 04:26:03.033 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:26:03.209 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch194
2025-07-30 04:26:05.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 5.603e-03, size: 416, ETA: 1:53:24
2025-07-30 04:26:08.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.597e-03, size: 480, ETA: 1:53:21
2025-07-30 04:26:11.573 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 5.591e-03, size: 576, ETA: 1:53:19
2025-07-30 04:26:14.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 80/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.585e-03, size: 352, ETA: 1:53:16
2025-07-30 04:26:17.096 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 5.579e-03, size: 416, ETA: 1:53:13
2025-07-30 04:26:19.988 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 194/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.574e-03, size: 480, ETA: 1:53:11
2025-07-30 04:26:21.171 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:26:21.215 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch195
2025-07-30 04:26:24.057 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.565e-03, size: 416, ETA: 1:53:07
2025-07-30 04:26:26.955 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.559e-03, size: 576, ETA: 1:53:05
2025-07-30 04:26:29.680 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.008s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.553e-03, size: 544, ETA: 1:53:02
2025-07-30 04:26:32.584 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.129s, data_time: 0.006s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.547e-03, size: 352, ETA: 1:53:00
2025-07-30 04:26:35.288 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.542e-03, size: 416, ETA: 1:52:57
2025-07-30 04:26:38.111 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 195/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.536e-03, size: 256, ETA: 1:52:55
2025-07-30 04:26:39.397 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:26:45.960 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:26:51.522 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:26:55.501 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4171
2025-07-30 04:26:56.075 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3933
2025-07-30 04:26:56.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1803
2025-07-30 04:26:56.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3302
2025-07-30 04:26:56.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.417
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.393
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.180
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.330
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:26:56.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:26:56.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:26:56.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:26:56.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:27:00.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:27:05.600 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:27:10.153 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:27:14.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:27:19.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:27:23.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:27:28.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:27:33.113 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:27:37.710 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:27:37.711 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-07-30 04:27:37.711 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.33
2025-07-30 04:27:37.711 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:27:37.736 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.99 ms, Average inference time: 2.37 ms

2025-07-30 04:27:37.737 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:27:37.762 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:27:37.793 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch196
2025-07-30 04:27:40.191 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.117s, data_time: 0.022s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.527e-03, size: 352, ETA: 1:52:51
2025-07-30 04:27:43.042 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.521e-03, size: 288, ETA: 1:52:48
2025-07-30 04:27:45.843 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 5.516e-03, size: 480, ETA: 1:52:45
2025-07-30 04:27:48.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.510e-03, size: 320, ETA: 1:52:43
2025-07-30 04:27:51.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 5.504e-03, size: 480, ETA: 1:52:40
2025-07-30 04:27:54.305 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 196/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 5.498e-03, size: 448, ETA: 1:52:38
2025-07-30 04:27:55.542 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:27:55.645 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch197
2025-07-30 04:27:58.418 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.9, lr: 5.490e-03, size: 384, ETA: 1:52:34
2025-07-30 04:28:01.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.484e-03, size: 320, ETA: 1:52:32
2025-07-30 04:28:04.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 5.478e-03, size: 512, ETA: 1:52:29
2025-07-30 04:28:06.868 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.6, lr: 5.472e-03, size: 288, ETA: 1:52:26
2025-07-30 04:28:09.569 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 5.466e-03, size: 576, ETA: 1:52:24
2025-07-30 04:28:12.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 197/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.460e-03, size: 512, ETA: 1:52:21
2025-07-30 04:28:13.637 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:28:13.781 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch198
2025-07-30 04:28:16.461 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.121s, 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: 5.452e-03, size: 256, ETA: 1:52:17
2025-07-30 04:28:19.290 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, 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: 5.446e-03, size: 288, ETA: 1:52:15
2025-07-30 04:28:22.190 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.440e-03, size: 256, ETA: 1:52:12
2025-07-30 04:28:25.037 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 5.434e-03, size: 576, ETA: 1:52:10
2025-07-30 04:28:27.836 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.428e-03, size: 480, ETA: 1:52:07
2025-07-30 04:28:30.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 198/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.122s, data_time: 0.005s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 5.423e-03, size: 448, ETA: 1:52:04
2025-07-30 04:28:31.761 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:28:31.896 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch199
2025-07-30 04:28:34.797 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.123s, data_time: 0.028s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.414e-03, size: 320, ETA: 1:52:00
2025-07-30 04:28:37.558 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.408e-03, size: 320, ETA: 1:51:57
2025-07-30 04:28:40.399 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.402e-03, size: 352, ETA: 1:51:54
2025-07-30 04:28:43.173 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.120s, data_time: 0.001s, total_loss: 7.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 5.397e-03, size: 256, ETA: 1:51:51
2025-07-30 04:28:45.902 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.391e-03, size: 416, ETA: 1:51:48
2025-07-30 04:28:48.726 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 199/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.385e-03, size: 480, ETA: 1:51:45
2025-07-30 04:28:49.980 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:28:50.012 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch200
2025-07-30 04:28:52.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 5.376e-03, size: 544, ETA: 1:51:41
2025-07-30 04:28:55.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.370e-03, size: 416, ETA: 1:51:39
2025-07-30 04:28:58.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.365e-03, size: 352, ETA: 1:51:36
2025-07-30 04:29:01.226 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, 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: 0.8, lr: 5.359e-03, size: 256, ETA: 1:51:33
2025-07-30 04:29:04.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 5.353e-03, size: 416, ETA: 1:51:31
2025-07-30 04:29:06.855 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 200/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.347e-03, size: 576, ETA: 1:51:29
2025-07-30 04:29:08.043 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:29:14.340 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:29:15.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:29:16.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4671
2025-07-30 04:29:16.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4279
2025-07-30 04:29:16.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2373
2025-07-30 04:29:16.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3774
2025-07-30 04:29:16.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:29:16.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:29:16.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.467
2025-07-30 04:29:16.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.428
2025-07-30 04:29:16.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.237
2025-07-30 04:29:16.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.377
2025-07-30 04:29:16.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:29:16.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:29:16.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:29:16.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:29:16.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:29:16.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:29:16.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:29:16.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:29:16.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:29:17.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:29:18.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:29:19.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:29:20.099 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:29:20.935 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:29:21.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:29:22.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:29:23.600 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:29:24.443 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:29:24.443 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 04:29:24.443 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.38
2025-07-30 04:29:24.443 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:29:24.451 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.95 ms, Average inference time: 2.32 ms

2025-07-30 04:29:24.453 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:29:24.473 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:29:24.501 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch201
2025-07-30 04:29:26.973 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.339e-03, size: 448, ETA: 1:51:24
2025-07-30 04:29:29.836 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 5.333e-03, size: 480, ETA: 1:51:22
2025-07-30 04:29:32.502 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 7.9, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 5.327e-03, size: 256, ETA: 1:51:20
2025-07-30 04:29:35.300 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.321e-03, size: 352, ETA: 1:51:17
2025-07-30 04:29:38.157 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.315e-03, size: 352, ETA: 1:51:15
2025-07-30 04:29:40.906 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 201/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.134s, data_time: 0.007s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.309e-03, size: 320, ETA: 1:51:13
2025-07-30 04:29:42.205 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:29:42.240 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch202
2025-07-30 04:29:45.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 20/129, gpu mem: 1553Mb, mem: 76.9Gb, iter_time: 0.127s, data_time: 0.005s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 5.301e-03, size: 576, ETA: 1:51:09
2025-07-30 04:29:47.881 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 5.295e-03, size: 256, ETA: 1:51:07
2025-07-30 04:29:50.612 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 5.289e-03, size: 320, ETA: 1:51:04
2025-07-30 04:29:53.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.2, lr: 5.283e-03, size: 288, ETA: 1:51:01
2025-07-30 04:29:56.242 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 5.277e-03, size: 512, ETA: 1:50:59
2025-07-30 04:29:59.080 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 202/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.272e-03, size: 384, ETA: 1:50:56
2025-07-30 04:30:00.266 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:30:00.377 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch203
2025-07-30 04:30:03.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.122s, 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: 5.263e-03, size: 352, ETA: 1:50:52
2025-07-30 04:30:05.893 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.257e-03, size: 416, ETA: 1:50:50
2025-07-30 04:30:08.763 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.251e-03, size: 320, ETA: 1:50:47
2025-07-30 04:30:11.517 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.119s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.245e-03, size: 256, ETA: 1:50:44
2025-07-30 04:30:14.260 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.128s, data_time: 0.004s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.240e-03, size: 448, ETA: 1:50:41
2025-07-30 04:30:17.122 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 203/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.234e-03, size: 512, ETA: 1:50:39
2025-07-30 04:30:18.267 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:30:18.392 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch204
2025-07-30 04:30:21.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.129s, data_time: 0.019s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.3, lr: 5.225e-03, size: 384, ETA: 1:50:35
2025-07-30 04:30:23.978 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.009s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.219e-03, size: 512, ETA: 1:50:33
2025-07-30 04:30:26.776 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.9, lr: 5.214e-03, size: 544, ETA: 1:50:30
2025-07-30 04:30:29.561 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.208e-03, size: 544, ETA: 1:50:28
2025-07-30 04:30:32.525 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.202e-03, size: 384, ETA: 1:50:26
2025-07-30 04:30:35.325 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 204/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, 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: 5.196e-03, size: 256, ETA: 1:50:23
2025-07-30 04:30:36.575 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:30:36.609 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch205
2025-07-30 04:30:39.460 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 5.187e-03, size: 416, ETA: 1:50:20
2025-07-30 04:30:42.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.2, lr: 5.182e-03, size: 256, ETA: 1:50:18
2025-07-30 04:30:45.075 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 5.176e-03, size: 320, ETA: 1:50:15
2025-07-30 04:30:47.744 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.019s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.170e-03, size: 384, ETA: 1:50:13
2025-07-30 04:30:50.523 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.164e-03, size: 256, ETA: 1:50:10
2025-07-30 04:30:53.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 205/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.125s, data_time: 0.004s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.158e-03, size: 448, ETA: 1:50:07
2025-07-30 04:30:54.497 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:31:00.976 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:31:02.785 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:31:03.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5035
2025-07-30 04:31:04.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4484
2025-07-30 04:31:04.241 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2284
2025-07-30 04:31:04.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3934
2025-07-30 04:31:04.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:31:04.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:31:04.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.503
2025-07-30 04:31:04.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.448
2025-07-30 04:31:04.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.228
2025-07-30 04:31:04.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.393
2025-07-30 04:31:04.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:31:04.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:31:04.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:31:04.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:31:04.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:31:04.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:31:04.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:31:04.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:31:04.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:31:05.656 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:31:07.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:31:08.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:31:10.003 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:31:11.485 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:31:12.849 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:31:14.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:31:15.656 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:31:16.999 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:31:17.000 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-07-30 04:31:17.000 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-30 04:31:17.000 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:31:17.009 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.93 ms, Average inference time: 2.30 ms

2025-07-30 04:31:17.014 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:31:17.081 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:31:17.112 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch206
2025-07-30 04:31:19.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.115s, data_time: 0.019s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 5.150e-03, size: 544, ETA: 1:50:03
2025-07-30 04:31:22.351 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.005s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 5.144e-03, size: 288, ETA: 1:50:00
2025-07-30 04:31:25.215 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.131s, data_time: 0.012s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 5.138e-03, size: 384, ETA: 1:49:58
2025-07-30 04:31:27.893 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, 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: 5.132e-03, size: 416, ETA: 1:49:55
2025-07-30 04:31:30.782 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.126e-03, size: 512, ETA: 1:49:52
2025-07-30 04:31:33.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 206/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.128s, 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: 5.120e-03, size: 544, ETA: 1:49:50
2025-07-30 04:31:34.724 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:31:34.867 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch207
2025-07-30 04:31:37.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.118s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.112e-03, size: 544, ETA: 1:49:45
2025-07-30 04:31:40.525 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.124s, 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: 5.106e-03, size: 256, ETA: 1:49:42
2025-07-30 04:31:43.341 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 5.100e-03, size: 544, ETA: 1:49:40
2025-07-30 04:31:46.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 5.094e-03, size: 288, ETA: 1:49:37
2025-07-30 04:31:48.990 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 5.089e-03, size: 384, ETA: 1:49:34
2025-07-30 04:31:51.801 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 207/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.083e-03, size: 352, ETA: 1:49:31
2025-07-30 04:31:53.001 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:31:53.038 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch208
2025-07-30 04:31:55.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.074e-03, size: 256, ETA: 1:49:27
2025-07-30 04:31:58.591 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 5.068e-03, size: 288, ETA: 1:49:24
2025-07-30 04:32:01.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 5.062e-03, size: 320, ETA: 1:49:21
2025-07-30 04:32:04.153 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.125s, 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: 5.057e-03, size: 352, ETA: 1:49:19
2025-07-30 04:32:06.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.123s, 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: 5.051e-03, size: 288, ETA: 1:49:16
2025-07-30 04:32:09.750 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 208/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.135s, data_time: 0.006s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.045e-03, size: 320, ETA: 1:49:13
2025-07-30 04:32:11.059 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:32:11.143 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch209
2025-07-30 04:32:13.886 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, 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: 5.036e-03, size: 480, ETA: 1:49:10
2025-07-30 04:32:16.672 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.031e-03, size: 384, ETA: 1:49:07
2025-07-30 04:32:19.549 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 5.025e-03, size: 544, ETA: 1:49:05
2025-07-30 04:32:22.384 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.019e-03, size: 416, ETA: 1:49:03
2025-07-30 04:32:25.172 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 5.013e-03, size: 256, ETA: 1:49:00
2025-07-30 04:32:28.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 209/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.007e-03, size: 384, ETA: 1:48:58
2025-07-30 04:32:29.290 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:32:29.375 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch210
2025-07-30 04:32:32.137 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.7, lr: 4.999e-03, size: 352, ETA: 1:48:54
2025-07-30 04:32:34.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 4.993e-03, size: 384, ETA: 1:48:51
2025-07-30 04:32:37.650 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 4.987e-03, size: 416, ETA: 1:48:48
2025-07-30 04:32:40.559 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.138s, 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: 4.981e-03, size: 448, ETA: 1:48:46
2025-07-30 04:32:43.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.975e-03, size: 416, ETA: 1:48:43
2025-07-30 04:32:46.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 210/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.969e-03, size: 320, ETA: 1:48:41
2025-07-30 04:32:47.423 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:32:53.911 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:32:59.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:33:04.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4810
2025-07-30 04:33:04.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4488
2025-07-30 04:33:05.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2334
2025-07-30 04:33:05.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3877
2025-07-30 04:33:05.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:33:05.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:33:05.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.481
2025-07-30 04:33:05.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.449
2025-07-30 04:33:05.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.233
2025-07-30 04:33:05.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.388
2025-07-30 04:33:05.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:33:05.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:33:05.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:33:05.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:33:05.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:33:05.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:33:05.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:33:05.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:33:05.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:33:09.999 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:33:14.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:33:19.843 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:33:24.775 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:33:29.682 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:33:34.661 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:33:39.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:33:44.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:33:49.414 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:33:49.415 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-07-30 04:33:49.415 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-30 04:33:49.415 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:33:49.443 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.97 ms, Average inference time: 2.36 ms

2025-07-30 04:33:49.444 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:33:49.514 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:33:49.545 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch211
2025-07-30 04:33:51.915 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.117s, data_time: 0.037s, total_loss: 8.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.3, lr: 4.961e-03, size: 576, ETA: 1:48:37
2025-07-30 04:33:54.691 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.049s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 4.955e-03, size: 384, ETA: 1:48:34
2025-07-30 04:33:57.527 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.020s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 4.949e-03, size: 512, ETA: 1:48:32
2025-07-30 04:34:00.268 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.051s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.943e-03, size: 544, ETA: 1:48:30
2025-07-30 04:34:03.067 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.056s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 4.938e-03, size: 256, ETA: 1:48:27
2025-07-30 04:34:05.881 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 211/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 4.932e-03, size: 512, ETA: 1:48:25
2025-07-30 04:34:07.175 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:34:07.218 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch212
2025-07-30 04:34:09.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.052s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.923e-03, size: 480, ETA: 1:48:22
2025-07-30 04:34:12.647 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.014s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 4.917e-03, size: 448, ETA: 1:48:19
2025-07-30 04:34:15.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 4.912e-03, size: 512, ETA: 1:48:17
2025-07-30 04:34:18.269 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 4.906e-03, size: 544, ETA: 1:48:14
2025-07-30 04:34:21.098 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 4.900e-03, size: 544, ETA: 1:48:12
2025-07-30 04:34:23.924 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 212/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, 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: 0.9, lr: 4.894e-03, size: 352, ETA: 1:48:09
2025-07-30 04:34:25.113 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:34:25.204 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch213
2025-07-30 04:34:27.889 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 4.886e-03, size: 352, ETA: 1:48:05
2025-07-30 04:34:30.739 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.007s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 4.880e-03, size: 352, ETA: 1:48:03
2025-07-30 04:34:33.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 4.874e-03, size: 480, ETA: 1:48:00
2025-07-30 04:34:36.418 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 4.868e-03, size: 448, ETA: 1:47:57
2025-07-30 04:34:39.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 4.862e-03, size: 480, ETA: 1:47:54
2025-07-30 04:34:41.916 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 213/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 4.856e-03, size: 480, ETA: 1:47:52
2025-07-30 04:34:43.078 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:34:43.188 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch214
2025-07-30 04:34:45.988 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.848e-03, size: 544, ETA: 1:47:48
2025-07-30 04:34:48.773 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 4.842e-03, size: 448, ETA: 1:47:45
2025-07-30 04:34:51.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 4.836e-03, size: 320, ETA: 1:47:43
2025-07-30 04:34:54.583 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.133s, 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: 4.830e-03, size: 320, ETA: 1:47:40
2025-07-30 04:34:57.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.130s, 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: 4.825e-03, size: 320, ETA: 1:47:38
2025-07-30 04:35:00.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 214/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 4.819e-03, size: 288, ETA: 1:47:35
2025-07-30 04:35:01.428 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:35:01.467 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch215
2025-07-30 04:35:04.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 4.810e-03, size: 256, ETA: 1:47:32
2025-07-30 04:35:07.220 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, 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: 1.0, lr: 4.804e-03, size: 416, ETA: 1:47:29
2025-07-30 04:35:10.049 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 4.799e-03, size: 256, ETA: 1:47:26
2025-07-30 04:35:12.913 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 4.793e-03, size: 544, ETA: 1:47:24
2025-07-30 04:35:15.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.787e-03, size: 480, ETA: 1:47:21
2025-07-30 04:35:18.661 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 215/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.123s, 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: 4.781e-03, size: 320, ETA: 1:47:18
2025-07-30 04:35:19.844 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:35:26.142 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:35:28.285 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:35:29.616 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5156
2025-07-30 04:35:29.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4399
2025-07-30 04:35:29.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2571
2025-07-30 04:35:29.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4042
2025-07-30 04:35:29.974 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:35:29.974 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:35:29.975 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.516
2025-07-30 04:35:29.975 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.440
2025-07-30 04:35:29.975 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.257
2025-07-30 04:35:29.976 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.404
2025-07-30 04:35:29.976 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:35:29.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:35:29.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:35:29.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:35:29.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:35:29.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:35:29.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:35:29.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:35:29.980 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:35:31.961 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:35:33.885 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:35:35.846 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:35:37.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:35:39.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:35:41.520 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:35:43.232 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:35:44.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:35:46.662 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:35:46.663 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-30 04:35:46.663 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-07-30 04:35:46.663 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:35:46.689 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.94 ms, Average inference time: 2.29 ms

2025-07-30 04:35:46.690 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:35:46.716 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:35:46.746 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch216
2025-07-30 04:35:49.146 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.111s, data_time: 0.018s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 4.773e-03, size: 544, ETA: 1:47:13
2025-07-30 04:35:51.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.124s, data_time: 0.008s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.767e-03, size: 448, ETA: 1:47:11
2025-07-30 04:35:54.666 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.009s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 4.761e-03, size: 352, ETA: 1:47:08
2025-07-30 04:35:57.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.044s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.2, lr: 4.755e-03, size: 416, ETA: 1:47:05
2025-07-30 04:36:00.215 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.124s, data_time: 0.015s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 4.749e-03, size: 448, ETA: 1:47:03
2025-07-30 04:36:03.071 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 216/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.744e-03, size: 352, ETA: 1:47:00
2025-07-30 04:36:04.298 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:36:04.499 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch217
2025-07-30 04:36:07.299 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.116s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.735e-03, size: 416, ETA: 1:46:56
2025-07-30 04:36:10.112 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 4.729e-03, size: 288, ETA: 1:46:53
2025-07-30 04:36:12.920 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 4.724e-03, size: 288, ETA: 1:46:50
2025-07-30 04:36:15.710 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 4.718e-03, size: 480, ETA: 1:46:47
2025-07-30 04:36:18.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.0Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 4.712e-03, size: 288, ETA: 1:46:44
2025-07-30 04:36:21.315 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 217/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 4.706e-03, size: 352, ETA: 1:46:41
2025-07-30 04:36:22.444 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:36:22.493 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch218
2025-07-30 04:36:25.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 4.698e-03, size: 512, ETA: 1:46:37
2025-07-30 04:36:28.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 4.692e-03, size: 576, ETA: 1:46:35
2025-07-30 04:36:30.939 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.686e-03, size: 320, ETA: 1:46:32
2025-07-30 04:36:33.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 4.680e-03, size: 448, ETA: 1:46:29
2025-07-30 04:36:36.624 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, 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: 0.9, lr: 4.674e-03, size: 256, ETA: 1:46:27
2025-07-30 04:36:39.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 218/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.669e-03, size: 480, ETA: 1:46:24
2025-07-30 04:36:40.606 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:36:40.639 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch219
2025-07-30 04:36:43.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 4.660e-03, size: 416, ETA: 1:46:21
2025-07-30 04:36:46.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 4.654e-03, size: 256, ETA: 1:46:18
2025-07-30 04:36:49.059 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.011s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 4.648e-03, size: 512, ETA: 1:46:16
2025-07-30 04:36:51.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.643e-03, size: 480, ETA: 1:46:14
2025-07-30 04:36:54.693 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.134s, 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: 4.637e-03, size: 320, ETA: 1:46:11
2025-07-30 04:36:57.592 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 219/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 4.631e-03, size: 416, ETA: 1:46:09
2025-07-30 04:36:58.812 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:36:58.915 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch220
2025-07-30 04:37:01.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 8.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 4.623e-03, size: 416, ETA: 1:46:05
2025-07-30 04:37:04.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 4.617e-03, size: 448, ETA: 1:46:03
2025-07-30 04:37:07.387 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 4.611e-03, size: 320, ETA: 1:46:00
2025-07-30 04:37:10.136 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, 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: 4.605e-03, size: 352, ETA: 1:45:58
2025-07-30 04:37:12.937 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.599e-03, size: 288, ETA: 1:45:55
2025-07-30 04:37:15.622 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 220/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 4.594e-03, size: 320, ETA: 1:45:52
2025-07-30 04:37:16.971 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:37:23.306 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:37:26.252 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:37:28.333 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5191
2025-07-30 04:37:28.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4453
2025-07-30 04:37:28.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2639
2025-07-30 04:37:28.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4094
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.519
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.445
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.264
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.409
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:37:28.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:37:28.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:37:28.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:37:28.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:37:28.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:37:28.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:37:31.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:37:33.677 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:37:36.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:37:38.660 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:37:41.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:37:43.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:37:45.943 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:37:48.342 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:37:50.836 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:37:50.836 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 04:37:50.837 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-07-30 04:37:50.837 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:37:50.863 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.95 ms, Average inference time: 2.35 ms

2025-07-30 04:37:50.863 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:37:50.889 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:37:50.919 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch221
2025-07-30 04:37:53.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.118s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 4.585e-03, size: 448, ETA: 1:45:48
2025-07-30 04:37:56.162 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 4.579e-03, size: 256, ETA: 1:45:46
2025-07-30 04:37:59.032 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 4.574e-03, size: 512, ETA: 1:45:44
2025-07-30 04:38:01.707 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 4.568e-03, size: 576, ETA: 1:45:41
2025-07-30 04:38:04.527 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 4.562e-03, size: 448, ETA: 1:45:39
2025-07-30 04:38:07.463 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 221/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.144s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.556e-03, size: 480, ETA: 1:45:37
2025-07-30 04:38:08.681 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:38:08.814 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch222
2025-07-30 04:38:11.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.134s, 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: 4.548e-03, size: 288, ETA: 1:45:33
2025-07-30 04:38:14.457 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 4.542e-03, size: 576, ETA: 1:45:30
2025-07-30 04:38:17.395 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.536e-03, size: 256, ETA: 1:45:28
2025-07-30 04:38:20.155 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 4.530e-03, size: 480, ETA: 1:45:26
2025-07-30 04:38:23.021 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.525e-03, size: 416, ETA: 1:45:23
2025-07-30 04:38:25.754 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 222/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.131s, 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: 4.519e-03, size: 352, ETA: 1:45:21
2025-07-30 04:38:26.974 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:38:27.109 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch223
2025-07-30 04:38:29.860 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.510e-03, size: 288, ETA: 1:45:16
2025-07-30 04:38:32.650 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.0, lr: 4.505e-03, size: 544, ETA: 1:45:13
2025-07-30 04:38:35.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.499e-03, size: 256, ETA: 1:45:11
2025-07-30 04:38:38.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 4.493e-03, size: 512, ETA: 1:45:08
2025-07-30 04:38:41.203 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.487e-03, size: 512, ETA: 1:45:06
2025-07-30 04:38:44.149 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 223/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.2, lr: 4.482e-03, size: 416, ETA: 1:45:03
2025-07-30 04:38:45.371 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:38:45.477 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch224
2025-07-30 04:38:48.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 4.473e-03, size: 352, ETA: 1:45:00
2025-07-30 04:38:51.173 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 4.467e-03, size: 384, ETA: 1:44:57
2025-07-30 04:38:53.990 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, 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: 0.9, lr: 4.462e-03, size: 352, ETA: 1:44:55
2025-07-30 04:38:56.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 4.456e-03, size: 416, ETA: 1:44:52
2025-07-30 04:38:59.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.034s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.450e-03, size: 352, ETA: 1:44:50
2025-07-30 04:39:02.348 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 224/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.126s, data_time: 0.017s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 4.444e-03, size: 352, ETA: 1:44:47
2025-07-30 04:39:03.559 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:39:03.592 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch225
2025-07-30 04:39:06.325 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.436e-03, size: 544, ETA: 1:44:44
2025-07-30 04:39:09.014 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.012s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 4.430e-03, size: 320, ETA: 1:44:41
2025-07-30 04:39:11.914 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 4.424e-03, size: 320, ETA: 1:44:39
2025-07-30 04:39:14.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 4.419e-03, size: 480, ETA: 1:44:36
2025-07-30 04:39:17.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.135s, 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: 4.413e-03, size: 256, ETA: 1:44:34
2025-07-30 04:39:20.345 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 225/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.407e-03, size: 512, ETA: 1:44:31
2025-07-30 04:39:21.457 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:39:27.960 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:39:29.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:39:31.205 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5133
2025-07-30 04:39:31.366 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4296
2025-07-30 04:39:31.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2344
2025-07-30 04:39:31.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3924
2025-07-30 04:39:31.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:39:31.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:39:31.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.513
2025-07-30 04:39:31.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.430
2025-07-30 04:39:31.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.234
2025-07-30 04:39:31.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.392
2025-07-30 04:39:31.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:39:31.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:39:31.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:39:31.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:39:31.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:39:31.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:39:31.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:39:31.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:39:31.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:39:33.036 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:39:34.609 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:39:36.139 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:39:37.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:39:39.230 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:39:40.807 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:39:42.326 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:39:43.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:39:45.474 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:39:45.475 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-30 04:39:45.475 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-30 04:39:45.475 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:39:45.498 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.96 ms, Average inference time: 2.32 ms

2025-07-30 04:39:45.499 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:39:45.531 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:39:45.560 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch226
2025-07-30 04:39:47.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.111s, data_time: 0.030s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.399e-03, size: 448, ETA: 1:44:27
2025-07-30 04:39:50.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.393e-03, size: 384, ETA: 1:44:24
2025-07-30 04:39:53.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 4.387e-03, size: 352, ETA: 1:44:22
2025-07-30 04:39:56.404 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.124s, 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: 4.381e-03, size: 256, ETA: 1:44:19
2025-07-30 04:39:59.216 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 4.376e-03, size: 544, ETA: 1:44:16
2025-07-30 04:40:02.173 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 226/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, 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: 0.8, lr: 4.370e-03, size: 352, ETA: 1:44:14
2025-07-30 04:40:03.213 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:40:03.345 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch227
2025-07-30 04:40:06.091 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.123s, data_time: 0.018s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 4.362e-03, size: 352, ETA: 1:44:10
2025-07-30 04:40:08.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.030s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 4.356e-03, size: 256, ETA: 1:44:07
2025-07-30 04:40:11.752 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.350e-03, size: 416, ETA: 1:44:04
2025-07-30 04:40:14.550 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.344e-03, size: 480, ETA: 1:44:01
2025-07-30 04:40:17.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 4.339e-03, size: 352, ETA: 1:43:59
2025-07-30 04:40:20.187 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 227/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.137s, 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: 4.333e-03, size: 256, ETA: 1:43:56
2025-07-30 04:40:21.371 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:40:21.447 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch228
2025-07-30 04:40:24.142 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 4.325e-03, size: 448, ETA: 1:43:52
2025-07-30 04:40:27.002 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, 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: 4.319e-03, size: 544, ETA: 1:43:50
2025-07-30 04:40:29.839 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 4.313e-03, size: 480, ETA: 1:43:47
2025-07-30 04:40:32.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 8.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 0.9, lr: 4.307e-03, size: 480, ETA: 1:43:45
2025-07-30 04:40:35.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.302e-03, size: 416, ETA: 1:43:42
2025-07-30 04:40:38.171 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 228/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, 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: 4.296e-03, size: 512, ETA: 1:43:40
2025-07-30 04:40:39.445 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:40:39.518 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch229
2025-07-30 04:40:42.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.287e-03, size: 384, ETA: 1:43:36
2025-07-30 04:40:45.066 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.128s, 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: 4.282e-03, size: 512, ETA: 1:43:33
2025-07-30 04:40:47.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 4.276e-03, size: 288, ETA: 1:43:31
2025-07-30 04:40:50.714 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 4.270e-03, size: 352, ETA: 1:43:28
2025-07-30 04:40:53.470 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 4.265e-03, size: 512, ETA: 1:43:26
2025-07-30 04:40:56.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 229/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.259e-03, size: 544, ETA: 1:43:23
2025-07-30 04:40:57.435 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:40:57.596 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch230
2025-07-30 04:41:00.385 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, 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: 4.251e-03, size: 512, ETA: 1:43:20
2025-07-30 04:41:03.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 4.245e-03, size: 512, ETA: 1:43:17
2025-07-30 04:41:05.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.239e-03, size: 544, ETA: 1:43:15
2025-07-30 04:41:08.703 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 4.233e-03, size: 352, ETA: 1:43:12
2025-07-30 04:41:11.557 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 4.228e-03, size: 512, ETA: 1:43:09
2025-07-30 04:41:14.360 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 230/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.132s, 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: 4.222e-03, size: 288, ETA: 1:43:07
2025-07-30 04:41:15.640 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:41:21.895 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:41:25.672 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:41:28.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4439
2025-07-30 04:41:28.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3880
2025-07-30 04:41:28.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1967
2025-07-30 04:41:28.894 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3429
2025-07-30 04:41:28.895 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:41:28.895 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:41:28.896 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.444
2025-07-30 04:41:28.896 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.388
2025-07-30 04:41:28.896 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.197
2025-07-30 04:41:28.897 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.343
2025-07-30 04:41:28.897 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:41:28.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:41:28.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:41:28.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:41:28.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:41:28.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:41:28.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:41:28.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:41:28.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:41:32.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:41:35.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:41:38.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:41:41.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:41:44.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:41:47.856 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:41:51.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:41:54.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:41:57.295 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:41:57.295 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-07-30 04:41:57.295 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.34
2025-07-30 04:41:57.295 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:41:57.320 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.98 ms, Average inference time: 2.35 ms

2025-07-30 04:41:57.321 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:41:57.340 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:41:57.370 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch231
2025-07-30 04:41:59.944 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.009s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 4.214e-03, size: 480, ETA: 1:43:03
2025-07-30 04:42:02.641 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 4.208e-03, size: 544, ETA: 1:43:01
2025-07-30 04:42:05.457 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.011s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.202e-03, size: 512, ETA: 1:42:58
2025-07-30 04:42:08.088 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.196e-03, size: 576, ETA: 1:42:55
2025-07-30 04:42:10.935 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.191e-03, size: 448, ETA: 1:42:53
2025-07-30 04:42:13.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 231/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 4.185e-03, size: 416, ETA: 1:42:51
2025-07-30 04:42:15.057 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:42:15.155 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch232
2025-07-30 04:42:17.909 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 4.177e-03, size: 416, ETA: 1:42:47
2025-07-30 04:42:20.773 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 4.171e-03, size: 480, ETA: 1:42:45
2025-07-30 04:42:23.716 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 4.165e-03, size: 352, ETA: 1:42:43
2025-07-30 04:42:26.595 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.135s, 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: 4.160e-03, size: 288, ETA: 1:42:40
2025-07-30 04:42:29.377 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 4.154e-03, size: 448, ETA: 1:42:38
2025-07-30 04:42:32.086 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 232/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 4.148e-03, size: 320, ETA: 1:42:35
2025-07-30 04:42:33.253 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:42:33.299 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch233
2025-07-30 04:42:36.008 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 4.140e-03, size: 256, ETA: 1:42:31
2025-07-30 04:42:38.816 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.007s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 4.134e-03, size: 448, ETA: 1:42:29
2025-07-30 04:42:41.634 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.137s, data_time: 0.004s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 4.129e-03, size: 480, ETA: 1:42:26
2025-07-30 04:42:44.363 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.019s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.123e-03, size: 288, ETA: 1:42:24
2025-07-30 04:42:47.272 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.141s, 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: 4.117e-03, size: 352, ETA: 1:42:22
2025-07-30 04:42:50.088 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 233/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 4.112e-03, size: 576, ETA: 1:42:19
2025-07-30 04:42:51.269 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:42:51.429 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch234
2025-07-30 04:42:54.223 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 4.103e-03, size: 480, ETA: 1:42:16
2025-07-30 04:42:56.990 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.098e-03, size: 352, ETA: 1:42:13
2025-07-30 04:42:59.920 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 4.092e-03, size: 352, ETA: 1:42:11
2025-07-30 04:43:02.785 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 4.086e-03, size: 288, ETA: 1:42:08
2025-07-30 04:43:05.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 4.081e-03, size: 320, ETA: 1:42:05
2025-07-30 04:43:08.438 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 234/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 4.075e-03, size: 576, ETA: 1:42:03
2025-07-30 04:43:09.653 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:43:09.781 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch235
2025-07-30 04:43:12.525 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 4.067e-03, size: 544, ETA: 1:41:59
2025-07-30 04:43:15.376 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.061e-03, size: 544, ETA: 1:41:56
2025-07-30 04:43:18.190 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.055e-03, size: 480, ETA: 1:41:53
2025-07-30 04:43:21.072 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 4.050e-03, size: 352, ETA: 1:41:51
2025-07-30 04:43:23.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 4.044e-03, size: 352, ETA: 1:41:48
2025-07-30 04:43:26.624 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 235/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 7.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 4.038e-03, size: 544, ETA: 1:41:45
2025-07-30 04:43:27.793 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:43:34.333 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:43:35.989 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:43:36.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4259
2025-07-30 04:43:37.247 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4037
2025-07-30 04:43:37.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1900
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3399
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.426
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.404
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.190
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.340
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:43:37.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:43:37.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:43:37.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:43:37.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:43:37.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:43:37.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:43:37.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:43:38.676 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:43:40.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:43:41.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:43:42.598 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:43:43.878 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:43:45.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:43:46.517 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:43:47.806 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:43:49.077 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:43:49.077 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-07-30 04:43:49.078 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.34
2025-07-30 04:43:49.078 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:43:49.092 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.89 ms, Average inference time: 2.27 ms

2025-07-30 04:43:49.092 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:43:49.124 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:43:49.164 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch236
2025-07-30 04:43:51.557 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.118s, data_time: 0.038s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 4.030e-03, size: 416, ETA: 1:41:41
2025-07-30 04:43:54.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.031s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 4.024e-03, size: 416, ETA: 1:41:39
2025-07-30 04:43:57.196 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 4.019e-03, size: 512, ETA: 1:41:36
2025-07-30 04:43:59.883 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.125s, 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: 4.013e-03, size: 576, ETA: 1:41:33
2025-07-30 04:44:02.721 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.008e-03, size: 384, ETA: 1:41:31
2025-07-30 04:44:05.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 236/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 4.002e-03, size: 512, ETA: 1:41:28
2025-07-30 04:44:06.656 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:44:06.794 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch237
2025-07-30 04:44:09.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 3.994e-03, size: 512, ETA: 1:41:24
2025-07-30 04:44:12.307 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 3.988e-03, size: 480, ETA: 1:41:21
2025-07-30 04:44:15.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 3.982e-03, size: 576, ETA: 1:41:18
2025-07-30 04:44:17.975 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 3.977e-03, size: 384, ETA: 1:41:16
2025-07-30 04:44:20.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 3.971e-03, size: 288, ETA: 1:41:13
2025-07-30 04:44:23.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 237/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.140s, 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: 3.965e-03, size: 320, ETA: 1:41:11
2025-07-30 04:44:24.896 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:44:25.045 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch238
2025-07-30 04:44:27.874 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 3.957e-03, size: 512, ETA: 1:41:07
2025-07-30 04:44:30.644 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.952e-03, size: 544, ETA: 1:41:05
2025-07-30 04:44:33.423 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.946e-03, size: 256, ETA: 1:41:02
2025-07-30 04:44:36.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.138s, 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: 3.940e-03, size: 480, ETA: 1:41:00
2025-07-30 04:44:39.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 3.935e-03, size: 320, ETA: 1:40:58
2025-07-30 04:44:42.055 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 238/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 3.929e-03, size: 576, ETA: 1:40:55
2025-07-30 04:44:43.307 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:44:43.330 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch239
2025-07-30 04:44:46.083 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 3.921e-03, size: 384, ETA: 1:40:51
2025-07-30 04:44:48.929 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 3.915e-03, size: 352, ETA: 1:40:48
2025-07-30 04:44:51.667 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.910e-03, size: 352, ETA: 1:40:46
2025-07-30 04:44:54.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 3.904e-03, size: 480, ETA: 1:40:43
2025-07-30 04:44:57.355 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.899e-03, size: 544, ETA: 1:40:41
2025-07-30 04:45:00.298 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 239/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.7, lr: 3.893e-03, size: 576, ETA: 1:40:38
2025-07-30 04:45:01.538 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:45:01.586 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch240
2025-07-30 04:45:04.437 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.7, lr: 3.885e-03, size: 512, ETA: 1:40:34
2025-07-30 04:45:07.101 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.126s, data_time: 0.018s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.879e-03, size: 288, ETA: 1:40:32
2025-07-30 04:45:09.980 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 3.874e-03, size: 512, ETA: 1:40:29
2025-07-30 04:45:12.864 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 3.868e-03, size: 352, ETA: 1:40:26
2025-07-30 04:45:15.649 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 3.862e-03, size: 480, ETA: 1:40:24
2025-07-30 04:45:18.379 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 240/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.127s, 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: 3.857e-03, size: 352, ETA: 1:40:21
2025-07-30 04:45:19.704 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:45:26.245 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:45:30.305 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:45:33.310 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5156
2025-07-30 04:45:33.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4579
2025-07-30 04:45:33.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2526
2025-07-30 04:45:33.852 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4087
2025-07-30 04:45:33.852 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:45:33.852 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:45:33.852 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.516
2025-07-30 04:45:33.852 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.458
2025-07-30 04:45:33.852 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.253
2025-07-30 04:45:33.852 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.409
2025-07-30 04:45:33.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:45:33.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:45:33.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:45:33.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:45:33.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:45:33.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:45:33.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:45:33.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:45:33.854 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:45:37.395 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:45:40.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:45:44.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:45:47.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:45:51.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:45:54.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:45:58.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:46:01.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:46:05.154 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:46:05.155 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-30 04:46:05.155 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-07-30 04:46:05.155 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:46:05.180 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.96 ms, Average inference time: 2.32 ms

2025-07-30 04:46:05.181 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:46:05.206 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:46:05.236 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch241
2025-07-30 04:46:07.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.118s, data_time: 0.008s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 3.849e-03, size: 384, ETA: 1:40:17
2025-07-30 04:46:10.422 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 3.843e-03, size: 416, ETA: 1:40:15
2025-07-30 04:46:13.277 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 3.837e-03, size: 480, ETA: 1:40:12
2025-07-30 04:46:16.124 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 3.832e-03, size: 416, ETA: 1:40:10
2025-07-30 04:46:18.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 3.826e-03, size: 256, ETA: 1:40:07
2025-07-30 04:46:21.615 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 241/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 3.821e-03, size: 288, ETA: 1:40:05
2025-07-30 04:46:22.884 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:46:22.979 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch242
2025-07-30 04:46:25.737 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 8.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.3, lr: 3.813e-03, size: 576, ETA: 1:40:01
2025-07-30 04:46:28.582 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 3.807e-03, size: 576, ETA: 1:39:59
2025-07-30 04:46:31.344 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.1Gb, iter_time: 0.126s, data_time: 0.015s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.801e-03, size: 352, ETA: 1:39:56
2025-07-30 04:46:33.994 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.796e-03, size: 320, ETA: 1:39:53
2025-07-30 04:46:36.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 3.790e-03, size: 512, ETA: 1:39:51
2025-07-30 04:46:39.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 242/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.785e-03, size: 256, ETA: 1:39:48
2025-07-30 04:46:40.991 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:46:41.023 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch243
2025-07-30 04:46:43.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 3.777e-03, size: 448, ETA: 1:39:44
2025-07-30 04:46:46.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 3.771e-03, size: 256, ETA: 1:39:42
2025-07-30 04:46:49.505 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 3.765e-03, size: 448, ETA: 1:39:39
2025-07-30 04:46:52.292 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, 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: 3.760e-03, size: 256, ETA: 1:39:37
2025-07-30 04:46:55.104 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.754e-03, size: 352, ETA: 1:39:34
2025-07-30 04:46:57.966 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 243/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 3.749e-03, size: 576, ETA: 1:39:32
2025-07-30 04:46:59.147 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:46:59.249 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch244
2025-07-30 04:47:02.109 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 3.741e-03, size: 576, ETA: 1:39:28
2025-07-30 04:47:04.858 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 8.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 3.735e-03, size: 288, ETA: 1:39:26
2025-07-30 04:47:07.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.730e-03, size: 288, ETA: 1:39:23
2025-07-30 04:47:10.540 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, 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: 3.724e-03, size: 384, ETA: 1:39:20
2025-07-30 04:47:13.315 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.719e-03, size: 352, ETA: 1:39:18
2025-07-30 04:47:16.198 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 244/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 3.713e-03, size: 288, ETA: 1:39:15
2025-07-30 04:47:17.467 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:47:17.559 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch245
2025-07-30 04:47:20.328 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 3.705e-03, size: 512, ETA: 1:39:11
2025-07-30 04:47:23.074 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.122s, 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: 3.699e-03, size: 576, ETA: 1:39:08
2025-07-30 04:47:25.970 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.694e-03, size: 352, ETA: 1:39:05
2025-07-30 04:47:28.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 3.688e-03, size: 384, ETA: 1:39:03
2025-07-30 04:47:31.584 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.683e-03, size: 576, ETA: 1:39:00
2025-07-30 04:47:34.356 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 245/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 3.677e-03, size: 288, ETA: 1:38:57
2025-07-30 04:47:35.481 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:47:41.954 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:47:46.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:47:49.847 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5080
2025-07-30 04:47:50.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4664
2025-07-30 04:47:50.577 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2593
2025-07-30 04:47:50.578 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4113
2025-07-30 04:47:50.578 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:47:50.578 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:47:50.578 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.508
2025-07-30 04:47:50.578 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.466
2025-07-30 04:47:50.578 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.259
2025-07-30 04:47:50.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.411
2025-07-30 04:47:50.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:47:50.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:47:50.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:47:50.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:47:50.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:47:50.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:47:50.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:47:50.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:47:50.580 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:47:54.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:47:58.260 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:48:02.204 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:48:06.038 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:48:09.817 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:48:13.659 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:48:17.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:48:21.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:48:24.947 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:48:24.947 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-30 04:48:24.947 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-07-30 04:48:24.947 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:48:24.975 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.97 ms, Average inference time: 2.32 ms

2025-07-30 04:48:24.976 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:48:25.001 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:48:25.031 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch246
2025-07-30 04:48:27.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.113s, 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: 3.669e-03, size: 544, ETA: 1:38:53
2025-07-30 04:48:30.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.3, lr: 3.664e-03, size: 544, ETA: 1:38:50
2025-07-30 04:48:33.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, 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: 3.658e-03, size: 512, ETA: 1:38:47
2025-07-30 04:48:36.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.653e-03, size: 448, ETA: 1:38:45
2025-07-30 04:48:38.972 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.647e-03, size: 576, ETA: 1:38:43
2025-07-30 04:48:41.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 246/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, 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: 3.642e-03, size: 256, ETA: 1:38:40
2025-07-30 04:48:43.003 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:48:43.121 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch247
2025-07-30 04:48:45.897 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 3.634e-03, size: 512, ETA: 1:38:36
2025-07-30 04:48:48.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, 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: 3.628e-03, size: 256, ETA: 1:38:34
2025-07-30 04:48:51.697 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 3.623e-03, size: 320, ETA: 1:38:31
2025-07-30 04:48:54.593 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.617e-03, size: 576, ETA: 1:38:28
2025-07-30 04:48:57.443 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 3.612e-03, size: 480, ETA: 1:38:26
2025-07-30 04:49:00.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 247/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 3.606e-03, size: 288, ETA: 1:38:23
2025-07-30 04:49:01.617 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:49:01.657 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch248
2025-07-30 04:49:04.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.598e-03, size: 352, ETA: 1:38:19
2025-07-30 04:49:07.255 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.006s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 3.593e-03, size: 512, ETA: 1:38:17
2025-07-30 04:49:09.992 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.587e-03, size: 352, ETA: 1:38:14
2025-07-30 04:49:12.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.582e-03, size: 256, ETA: 1:38:12
2025-07-30 04:49:15.626 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, 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: 3.576e-03, size: 352, ETA: 1:38:09
2025-07-30 04:49:18.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 248/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 3.571e-03, size: 256, ETA: 1:38:06
2025-07-30 04:49:19.835 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:49:19.961 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch249
2025-07-30 04:49:22.657 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.115s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 3.563e-03, size: 352, ETA: 1:38:02
2025-07-30 04:49:25.459 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.118s, data_time: 0.021s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 3.557e-03, size: 352, ETA: 1:37:59
2025-07-30 04:49:28.286 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.121s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.552e-03, size: 512, ETA: 1:37:56
2025-07-30 04:49:30.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 3.546e-03, size: 480, ETA: 1:37:54
2025-07-30 04:49:33.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.541e-03, size: 384, ETA: 1:37:51
2025-07-30 04:49:36.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 249/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 3.536e-03, size: 320, ETA: 1:37:49
2025-07-30 04:49:37.782 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:49:37.903 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch250
2025-07-30 04:49:40.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.528e-03, size: 352, ETA: 1:37:45
2025-07-30 04:49:43.572 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 3.522e-03, size: 256, ETA: 1:37:43
2025-07-30 04:49:46.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 3.517e-03, size: 416, ETA: 1:37:41
2025-07-30 04:49:49.118 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 3.511e-03, size: 416, ETA: 1:37:38
2025-07-30 04:49:51.913 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.506e-03, size: 256, ETA: 1:37:36
2025-07-30 04:49:54.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 250/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 7.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.7, lr: 3.500e-03, size: 448, ETA: 1:37:33
2025-07-30 04:49:56.057 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:50:02.367 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:50:03.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:50:04.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4950
2025-07-30 04:50:04.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4273
2025-07-30 04:50:04.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2329
2025-07-30 04:50:04.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3851
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.495
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.427
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.233
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.385
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:50:04.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:50:04.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:50:04.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:50:04.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:50:04.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:50:04.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:50:05.660 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:50:06.649 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:50:07.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:50:08.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:50:09.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:50:10.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:50:11.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:50:12.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:50:13.444 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:50:13.445 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-07-30 04:50:13.445 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-30 04:50:13.445 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:50:13.452 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.94 ms, Average inference time: 2.31 ms

2025-07-30 04:50:13.454 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:50:13.477 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:50:13.504 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch251
2025-07-30 04:50:16.001 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.119s, data_time: 0.021s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 3.492e-03, size: 544, ETA: 1:37:29
2025-07-30 04:50:18.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 7.7, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 3.487e-03, size: 320, ETA: 1:37:27
2025-07-30 04:50:21.646 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.012s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.482e-03, size: 384, ETA: 1:37:24
2025-07-30 04:50:24.529 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 3.476e-03, size: 480, ETA: 1:37:22
2025-07-30 04:50:27.395 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.471e-03, size: 480, ETA: 1:37:19
2025-07-30 04:50:30.089 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 251/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.131s, 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: 3.465e-03, size: 352, ETA: 1:37:17
2025-07-30 04:50:31.335 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:50:31.498 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch252
2025-07-30 04:50:34.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.457e-03, size: 576, ETA: 1:37:13
2025-07-30 04:50:37.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.452e-03, size: 320, ETA: 1:37:11
2025-07-30 04:50:39.845 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, 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: 3.447e-03, size: 320, ETA: 1:37:08
2025-07-30 04:50:42.635 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.6, lr: 3.441e-03, size: 320, ETA: 1:37:05
2025-07-30 04:50:45.497 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 7.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 3.436e-03, size: 288, ETA: 1:37:03
2025-07-30 04:50:48.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 252/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.430e-03, size: 544, ETA: 1:37:00
2025-07-30 04:50:49.556 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:50:49.682 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch253
2025-07-30 04:50:52.474 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 3.422e-03, size: 256, ETA: 1:36:56
2025-07-30 04:50:55.238 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.417e-03, size: 416, ETA: 1:36:53
2025-07-30 04:50:57.909 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 3.412e-03, size: 384, ETA: 1:36:51
2025-07-30 04:51:00.722 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.139s, 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: 3.406e-03, size: 384, ETA: 1:36:48
2025-07-30 04:51:03.728 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, 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: 3.401e-03, size: 448, ETA: 1:36:46
2025-07-30 04:51:06.502 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 253/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.120s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 3.395e-03, size: 320, ETA: 1:36:43
2025-07-30 04:51:07.653 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:51:07.719 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch254
2025-07-30 04:51:10.487 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 3.388e-03, size: 320, ETA: 1:36:39
2025-07-30 04:51:13.120 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.120s, data_time: 0.009s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 3.382e-03, size: 352, ETA: 1:36:36
2025-07-30 04:51:15.971 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.005s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 3.377e-03, size: 448, ETA: 1:36:34
2025-07-30 04:51:18.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 3.372e-03, size: 352, ETA: 1:36:31
2025-07-30 04:51:21.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.127s, data_time: 0.020s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 3.366e-03, size: 544, ETA: 1:36:28
2025-07-30 04:51:24.398 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 254/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.135s, data_time: 0.006s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 3.361e-03, size: 320, ETA: 1:36:26
2025-07-30 04:51:25.593 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:51:25.808 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch255
2025-07-30 04:51:28.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.353e-03, size: 320, ETA: 1:36:22
2025-07-30 04:51:31.518 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 3.348e-03, size: 320, ETA: 1:36:19
2025-07-30 04:51:34.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 3.342e-03, size: 512, ETA: 1:36:16
2025-07-30 04:51:37.121 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.010s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.337e-03, size: 256, ETA: 1:36:14
2025-07-30 04:51:39.894 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.036s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 3.332e-03, size: 512, ETA: 1:36:11
2025-07-30 04:51:42.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 255/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.019s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 3.326e-03, size: 480, ETA: 1:36:09
2025-07-30 04:51:43.973 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:51:50.574 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:51:53.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:51:54.856 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5286
2025-07-30 04:51:55.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4753
2025-07-30 04:51:55.320 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2830
2025-07-30 04:51:55.321 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4289
2025-07-30 04:51:55.321 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.529
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.475
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.283
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.429
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:51:55.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:51:55.323 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:51:55.323 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:51:55.323 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:51:57.195 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:51:58.988 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:52:00.766 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:52:02.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:52:04.381 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:52:06.170 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:52:07.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:52:09.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:52:11.376 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:52:11.377 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 04:52:11.377 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-30 04:52:11.377 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:52:11.405 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.95 ms, Average inference time: 2.33 ms

2025-07-30 04:52:11.406 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:52:11.444 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:52:11.491 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch256
2025-07-30 04:52:13.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.118s, 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: 3.318e-03, size: 320, ETA: 1:36:05
2025-07-30 04:52:16.858 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 3.313e-03, size: 512, ETA: 1:36:02
2025-07-30 04:52:19.527 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.308e-03, size: 256, ETA: 1:36:00
2025-07-30 04:52:22.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 3.302e-03, size: 352, ETA: 1:35:57
2025-07-30 04:52:25.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, data_time: 0.004s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 3.297e-03, size: 288, ETA: 1:35:54
2025-07-30 04:52:27.963 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 256/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.129s, data_time: 0.031s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 3.292e-03, size: 384, ETA: 1:35:52
2025-07-30 04:52:29.231 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:52:29.301 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch257
2025-07-30 04:52:32.098 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 3.284e-03, size: 480, ETA: 1:35:48
2025-07-30 04:52:34.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 3.279e-03, size: 416, ETA: 1:35:46
2025-07-30 04:52:37.609 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 3.273e-03, size: 288, ETA: 1:35:43
2025-07-30 04:52:40.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, 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: 3.268e-03, size: 480, ETA: 1:35:41
2025-07-30 04:52:43.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.263e-03, size: 352, ETA: 1:35:38
2025-07-30 04:52:46.028 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 257/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 3.257e-03, size: 320, ETA: 1:35:36
2025-07-30 04:52:47.264 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:52:47.311 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch258
2025-07-30 04:52:50.117 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 3.250e-03, size: 544, ETA: 1:35:32
2025-07-30 04:52:53.023 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.244e-03, size: 576, ETA: 1:35:29
2025-07-30 04:52:55.974 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 3.239e-03, size: 448, ETA: 1:35:27
2025-07-30 04:52:58.731 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 3.234e-03, size: 384, ETA: 1:35:24
2025-07-30 04:53:01.511 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 3.228e-03, size: 384, ETA: 1:35:21
2025-07-30 04:53:04.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 258/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.223e-03, size: 576, ETA: 1:35:19
2025-07-30 04:53:05.586 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:53:05.691 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch259
2025-07-30 04:53:08.422 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.126s, 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: 3.215e-03, size: 448, ETA: 1:35:15
2025-07-30 04:53:11.239 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 3.210e-03, size: 576, ETA: 1:35:12
2025-07-30 04:53:13.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.5, lr: 3.205e-03, size: 512, ETA: 1:35:10
2025-07-30 04:53:16.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.131s, data_time: 0.007s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 3.200e-03, size: 288, ETA: 1:35:07
2025-07-30 04:53:19.546 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, data_time: 0.012s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 3.194e-03, size: 576, ETA: 1:35:04
2025-07-30 04:53:22.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 259/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, 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: 3.189e-03, size: 384, ETA: 1:35:02
2025-07-30 04:53:23.530 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:53:23.609 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch260
2025-07-30 04:53:26.466 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 3.181e-03, size: 576, ETA: 1:34:58
2025-07-30 04:53:29.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.176e-03, size: 544, ETA: 1:34:56
2025-07-30 04:53:32.030 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 3.171e-03, size: 256, ETA: 1:34:53
2025-07-30 04:53:34.869 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 3.166e-03, size: 448, ETA: 1:34:50
2025-07-30 04:53:37.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.136s, 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: 3.160e-03, size: 320, ETA: 1:34:48
2025-07-30 04:53:40.469 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 260/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 3.155e-03, size: 320, ETA: 1:34:45
2025-07-30 04:53:41.783 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:53:48.173 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:53:50.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:53:51.068 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5038
2025-07-30 04:53:51.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4203
2025-07-30 04:53:51.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2600
2025-07-30 04:53:51.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3947
2025-07-30 04:53:51.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:53:51.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.504
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.420
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.260
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.395
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:53:51.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:53:51.430 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:53:51.430 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:53:52.768 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:53:54.054 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:53:55.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:53:56.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:53:57.976 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:53:59.314 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:54:00.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:54:01.916 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:54:03.257 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:54:03.257 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-30 04:54:03.257 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-30 04:54:03.257 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:54:03.265 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.94 ms, Average inference time: 2.31 ms

2025-07-30 04:54:03.266 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:54:03.290 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:54:03.319 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch261
2025-07-30 04:54:05.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.115s, data_time: 0.027s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 3.147e-03, size: 384, ETA: 1:34:41
2025-07-30 04:54:08.605 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.131s, data_time: 0.016s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.142e-03, size: 544, ETA: 1:34:39
2025-07-30 04:54:11.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.3, lr: 3.137e-03, size: 416, ETA: 1:34:36
2025-07-30 04:54:14.471 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 3.132e-03, size: 320, ETA: 1:34:34
2025-07-30 04:54:17.095 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.126e-03, size: 320, ETA: 1:34:32
2025-07-30 04:54:19.890 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 261/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.121e-03, size: 576, ETA: 1:34:29
2025-07-30 04:54:21.105 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:54:21.153 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch262
2025-07-30 04:54:23.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.114e-03, size: 352, ETA: 1:34:25
2025-07-30 04:54:26.725 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.108e-03, size: 416, ETA: 1:34:23
2025-07-30 04:54:29.586 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.103e-03, size: 480, ETA: 1:34:20
2025-07-30 04:54:32.473 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 3.098e-03, size: 288, ETA: 1:34:18
2025-07-30 04:54:35.273 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 3.093e-03, size: 288, ETA: 1:34:15
2025-07-30 04:54:38.193 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 262/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.2, lr: 3.087e-03, size: 384, ETA: 1:34:12
2025-07-30 04:54:39.338 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:54:39.537 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch263
2025-07-30 04:54:42.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 3.080e-03, size: 576, ETA: 1:34:08
2025-07-30 04:54:45.108 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 3.075e-03, size: 544, ETA: 1:34:06
2025-07-30 04:54:47.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 3.070e-03, size: 416, ETA: 1:34:03
2025-07-30 04:54:50.564 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.021s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 3.064e-03, size: 416, ETA: 1:34:00
2025-07-30 04:54:53.277 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.012s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 3.059e-03, size: 512, ETA: 1:33:58
2025-07-30 04:54:56.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 263/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.144s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 3.054e-03, size: 512, ETA: 1:33:56
2025-07-30 04:54:57.310 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:54:57.364 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch264
2025-07-30 04:55:00.112 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.046e-03, size: 352, ETA: 1:33:52
2025-07-30 04:55:02.971 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 3.041e-03, size: 448, ETA: 1:33:49
2025-07-30 04:55:05.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, 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: 3.036e-03, size: 384, ETA: 1:33:47
2025-07-30 04:55:08.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 3.031e-03, size: 352, ETA: 1:33:44
2025-07-30 04:55:11.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 3.026e-03, size: 352, ETA: 1:33:41
2025-07-30 04:55:14.127 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 264/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 3.020e-03, size: 256, ETA: 1:33:39
2025-07-30 04:55:15.353 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:55:15.466 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch265
2025-07-30 04:55:18.096 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.112s, data_time: 0.004s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 3.013e-03, size: 480, ETA: 1:33:34
2025-07-30 04:55:20.868 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 3.008e-03, size: 320, ETA: 1:33:32
2025-07-30 04:55:23.687 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 3.003e-03, size: 288, ETA: 1:33:29
2025-07-30 04:55:26.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.998e-03, size: 512, ETA: 1:33:26
2025-07-30 04:55:29.329 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.119s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.992e-03, size: 480, ETA: 1:33:23
2025-07-30 04:55:32.181 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 265/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.987e-03, size: 448, ETA: 1:33:20
2025-07-30 04:55:33.398 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:55:39.943 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:55:43.470 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:55:45.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5234
2025-07-30 04:55:46.188 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4633
2025-07-30 04:55:46.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2828
2025-07-30 04:55:46.367 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4232
2025-07-30 04:55:46.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:55:46.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:55:46.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.523
2025-07-30 04:55:46.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.463
2025-07-30 04:55:46.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.283
2025-07-30 04:55:46.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.423
2025-07-30 04:55:46.371 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:55:46.371 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:55:46.371 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:55:46.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:55:46.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:55:46.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:55:46.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:55:46.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:55:46.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:55:49.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:55:52.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:55:55.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:55:58.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:56:00.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:56:03.749 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:56:06.529 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:56:09.431 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:56:12.297 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:56:12.297 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 04:56:12.297 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-30 04:56:12.297 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:56:12.323 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.95 ms, Average inference time: 2.33 ms

2025-07-30 04:56:12.324 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:56:12.356 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:56:12.386 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch266
2025-07-30 04:56:14.820 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.112s, data_time: 0.025s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 2.980e-03, size: 352, ETA: 1:33:16
2025-07-30 04:56:17.592 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.009s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.975e-03, size: 384, ETA: 1:33:13
2025-07-30 04:56:20.427 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.015s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 2.969e-03, size: 480, ETA: 1:33:11
2025-07-30 04:56:23.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.032s, total_loss: 8.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 0.9, lr: 2.964e-03, size: 512, ETA: 1:33:08
2025-07-30 04:56:26.012 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.959e-03, size: 544, ETA: 1:33:06
2025-07-30 04:56:28.886 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 266/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.6, lr: 2.954e-03, size: 288, ETA: 1:33:03
2025-07-30 04:56:30.171 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:56:30.205 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch267
2025-07-30 04:56:32.974 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.947e-03, size: 448, ETA: 1:33:00
2025-07-30 04:56:35.777 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.942e-03, size: 416, ETA: 1:32:57
2025-07-30 04:56:38.637 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 2.936e-03, size: 384, ETA: 1:32:55
2025-07-30 04:56:41.390 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.6, lr: 2.931e-03, size: 416, ETA: 1:32:52
2025-07-30 04:56:44.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.138s, data_time: 0.016s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.926e-03, size: 512, ETA: 1:32:50
2025-07-30 04:56:47.079 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 267/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.012s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 2.921e-03, size: 544, ETA: 1:32:47
2025-07-30 04:56:48.264 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:56:48.311 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch268
2025-07-30 04:56:51.025 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.914e-03, size: 512, ETA: 1:32:43
2025-07-30 04:56:53.925 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.2Gb, iter_time: 0.133s, 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: 2.909e-03, size: 256, ETA: 1:32:41
2025-07-30 04:56:56.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 2.903e-03, size: 512, ETA: 1:32:38
2025-07-30 04:56:59.480 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.898e-03, size: 256, ETA: 1:32:35
2025-07-30 04:57:02.238 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.893e-03, size: 544, ETA: 1:32:33
2025-07-30 04:57:05.156 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 268/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.888e-03, size: 576, ETA: 1:32:30
2025-07-30 04:57:06.435 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:57:06.490 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch269
2025-07-30 04:57:09.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 2.881e-03, size: 448, ETA: 1:32:26
2025-07-30 04:57:12.166 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 2.876e-03, size: 320, ETA: 1:32:24
2025-07-30 04:57:15.036 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.871e-03, size: 256, ETA: 1:32:22
2025-07-30 04:57:17.739 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 2.866e-03, size: 480, ETA: 1:32:19
2025-07-30 04:57:20.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.861e-03, size: 576, ETA: 1:32:17
2025-07-30 04:57:23.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 269/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.855e-03, size: 544, ETA: 1:32:15
2025-07-30 04:57:24.645 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:57:24.779 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch270
2025-07-30 04:57:27.503 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 2.848e-03, size: 512, ETA: 1:32:11
2025-07-30 04:57:30.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.009s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 2.843e-03, size: 448, ETA: 1:32:08
2025-07-30 04:57:33.082 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 2.838e-03, size: 256, ETA: 1:32:06
2025-07-30 04:57:35.959 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 2.833e-03, size: 352, ETA: 1:32:03
2025-07-30 04:57:38.812 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.131s, 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: 2.828e-03, size: 416, ETA: 1:32:01
2025-07-30 04:57:41.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 270/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.005s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.823e-03, size: 512, ETA: 1:31:58
2025-07-30 04:57:42.770 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:57:49.430 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:57:51.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:57:52.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5054
2025-07-30 04:57:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4486
2025-07-30 04:57:52.458 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2302
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3948
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.505
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.449
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.230
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.395
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:57:52.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:57:52.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:57:52.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:57:52.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:57:52.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:57:52.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:57:52.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:57:53.767 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:57:55.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:57:56.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:57:57.708 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 04:57:58.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 04:58:00.306 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 04:58:01.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 04:58:02.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 04:58:04.206 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 04:58:04.206 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-07-30 04:58:04.206 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-07-30 04:58:04.206 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 04:58:04.214 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.96 ms, Average inference time: 2.32 ms

2025-07-30 04:58:04.215 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:58:04.239 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:58:04.267 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch271
2025-07-30 04:58:06.732 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.120s, data_time: 0.021s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 2.816e-03, size: 384, ETA: 1:31:54
2025-07-30 04:58:09.572 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.007s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 2.811e-03, size: 480, ETA: 1:31:52
2025-07-30 04:58:12.325 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 2.806e-03, size: 288, ETA: 1:31:49
2025-07-30 04:58:15.182 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 2.801e-03, size: 320, ETA: 1:31:47
2025-07-30 04:58:18.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.141s, 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: 2.796e-03, size: 384, ETA: 1:31:45
2025-07-30 04:58:20.771 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 271/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 2.791e-03, size: 320, ETA: 1:31:42
2025-07-30 04:58:22.008 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:58:22.157 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch272
2025-07-30 04:58:24.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 2.783e-03, size: 416, ETA: 1:31:38
2025-07-30 04:58:27.714 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 2.778e-03, size: 288, ETA: 1:31:36
2025-07-30 04:58:30.536 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.773e-03, size: 256, ETA: 1:31:33
2025-07-30 04:58:33.378 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.768e-03, size: 384, ETA: 1:31:31
2025-07-30 04:58:36.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, 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: 2.763e-03, size: 384, ETA: 1:31:29
2025-07-30 04:58:39.004 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 272/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.758e-03, size: 256, ETA: 1:31:26
2025-07-30 04:58:40.170 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:58:40.278 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch273
2025-07-30 04:58:43.097 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.126s, 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: 2.751e-03, size: 352, ETA: 1:31:22
2025-07-30 04:58:45.815 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.125s, data_time: 0.012s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.746e-03, size: 320, ETA: 1:31:19
2025-07-30 04:58:48.838 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.741e-03, size: 384, ETA: 1:31:17
2025-07-30 04:58:51.677 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.736e-03, size: 480, ETA: 1:31:14
2025-07-30 04:58:54.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.120s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.731e-03, size: 320, ETA: 1:31:11
2025-07-30 04:58:57.268 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 273/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 2.726e-03, size: 320, ETA: 1:31:08
2025-07-30 04:58:58.432 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:58:58.485 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch274
2025-07-30 04:59:01.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.719e-03, size: 512, ETA: 1:31:04
2025-07-30 04:59:04.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.2, lr: 2.714e-03, size: 480, ETA: 1:31:02
2025-07-30 04:59:06.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.709e-03, size: 352, ETA: 1:30:59
2025-07-30 04:59:09.648 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 2.704e-03, size: 352, ETA: 1:30:57
2025-07-30 04:59:12.427 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 2.699e-03, size: 544, ETA: 1:30:54
2025-07-30 04:59:15.144 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 274/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.694e-03, size: 416, ETA: 1:30:51
2025-07-30 04:59:16.329 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:59:16.446 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch275
2025-07-30 04:59:19.226 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 9.2, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 4.7, cls_loss: 1.0, lr: 2.687e-03, size: 480, ETA: 1:30:48
2025-07-30 04:59:22.014 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 8.6, iou_loss: 4.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 2.682e-03, size: 448, ETA: 1:30:45
2025-07-30 04:59:24.783 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 2.677e-03, size: 480, ETA: 1:30:42
2025-07-30 04:59:27.687 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 2.672e-03, size: 544, ETA: 1:30:40
2025-07-30 04:59:30.647 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.144s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 2.667e-03, size: 256, ETA: 1:30:38
2025-07-30 04:59:33.404 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 275/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 2.663e-03, size: 448, ETA: 1:30:35
2025-07-30 04:59:34.676 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 04:59:41.248 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 04:59:44.575 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 04:59:46.716 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5266
2025-07-30 04:59:47.112 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4616
2025-07-30 04:59:47.246 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2535
2025-07-30 04:59:47.247 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4139
2025-07-30 04:59:47.247 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 04:59:47.247 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 04:59:47.247 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.527
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.462
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.253
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.414
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 04:59:47.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 04:59:47.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 04:59:47.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 04:59:49.951 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 04:59:52.589 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 04:59:55.297 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 04:59:57.989 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:00:00.622 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:00:03.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:00:05.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:00:08.634 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:00:11.344 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:00:11.344 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 05:00:11.344 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-07-30 05:00:11.344 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:00:11.369 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.95 ms, Average inference time: 2.32 ms

2025-07-30 05:00:11.371 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:00:11.399 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:00:11.437 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch276
2025-07-30 05:00:13.822 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.116s, data_time: 0.018s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 2.655e-03, size: 352, ETA: 1:30:31
2025-07-30 05:00:16.645 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.126s, data_time: 0.036s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.651e-03, size: 384, ETA: 1:30:29
2025-07-30 05:00:19.518 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.646e-03, size: 576, ETA: 1:30:26
2025-07-30 05:00:22.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, 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: 2.641e-03, size: 576, ETA: 1:30:23
2025-07-30 05:00:25.095 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.636e-03, size: 384, ETA: 1:30:21
2025-07-30 05:00:27.886 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 276/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 2.631e-03, size: 384, ETA: 1:30:18
2025-07-30 05:00:29.083 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:00:29.217 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch277
2025-07-30 05:00:32.135 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 2.624e-03, size: 480, ETA: 1:30:14
2025-07-30 05:00:34.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.619e-03, size: 288, ETA: 1:30:11
2025-07-30 05:00:37.645 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.131s, 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: 2.614e-03, size: 288, ETA: 1:30:09
2025-07-30 05:00:40.489 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.133s, 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: 2.609e-03, size: 384, ETA: 1:30:06
2025-07-30 05:00:43.421 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 2.604e-03, size: 416, ETA: 1:30:03
2025-07-30 05:00:46.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 277/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 2.600e-03, size: 512, ETA: 1:30:01
2025-07-30 05:00:47.335 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:00:47.533 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch278
2025-07-30 05:00:50.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 8.1, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.7, lr: 2.592e-03, size: 256, ETA: 1:29:57
2025-07-30 05:00:53.149 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 2.588e-03, size: 512, ETA: 1:29:55
2025-07-30 05:00:55.892 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 2.583e-03, size: 576, ETA: 1:29:52
2025-07-30 05:00:58.646 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 2.578e-03, size: 320, ETA: 1:29:49
2025-07-30 05:01:01.445 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.129s, data_time: 0.018s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 2.573e-03, size: 576, ETA: 1:29:47
2025-07-30 05:01:04.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 278/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.129s, 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: 2.568e-03, size: 256, ETA: 1:29:44
2025-07-30 05:01:05.353 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:01:05.401 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch279
2025-07-30 05:01:08.196 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 2.561e-03, size: 512, ETA: 1:29:40
2025-07-30 05:01:11.105 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.556e-03, size: 480, ETA: 1:29:38
2025-07-30 05:01:13.915 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.552e-03, size: 448, ETA: 1:29:35
2025-07-30 05:01:16.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 2.547e-03, size: 576, ETA: 1:29:33
2025-07-30 05:01:19.512 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 2.542e-03, size: 576, ETA: 1:29:30
2025-07-30 05:01:22.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 279/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.537e-03, size: 256, ETA: 1:29:28
2025-07-30 05:01:23.573 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:01:23.707 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch280
2025-07-30 05:01:26.521 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.530e-03, size: 448, ETA: 1:29:24
2025-07-30 05:01:29.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.525e-03, size: 576, ETA: 1:29:22
2025-07-30 05:01:32.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.007s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 2.521e-03, size: 576, ETA: 1:29:19
2025-07-30 05:01:35.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.516e-03, size: 416, ETA: 1:29:16
2025-07-30 05:01:37.940 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 2.511e-03, size: 480, ETA: 1:29:14
2025-07-30 05:01:40.677 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 280/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 2.506e-03, size: 448, ETA: 1:29:12
2025-07-30 05:01:41.868 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:01:48.120 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:01:50.463 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:01:52.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5206
2025-07-30 05:01:52.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4617
2025-07-30 05:01:52.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2696
2025-07-30 05:01:52.387 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4173
2025-07-30 05:01:52.387 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:01:52.387 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:01:52.387 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.521
2025-07-30 05:01:52.387 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.462
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.270
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.417
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:01:52.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:01:52.389 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:01:54.321 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:01:56.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:01:58.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:02:00.074 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:02:01.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:02:03.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:02:05.751 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:02:07.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:02:09.559 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:02:09.560 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 05:02:09.560 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-30 05:02:09.560 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:02:09.584 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.96 ms, Average inference time: 2.31 ms

2025-07-30 05:02:09.586 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:02:09.607 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:02:09.635 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch281
2025-07-30 05:02:12.133 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.116s, data_time: 0.016s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 2.499e-03, size: 256, ETA: 1:29:07
2025-07-30 05:02:15.070 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.133s, 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: 2.495e-03, size: 352, ETA: 1:29:05
2025-07-30 05:02:17.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 2.490e-03, size: 288, ETA: 1:29:02
2025-07-30 05:02:20.472 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.485e-03, size: 288, ETA: 1:29:00
2025-07-30 05:02:23.284 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.137s, 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: 2.480e-03, size: 448, ETA: 1:28:57
2025-07-30 05:02:26.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 281/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.146s, 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: 2.475e-03, size: 256, ETA: 1:28:55
2025-07-30 05:02:27.561 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:02:27.702 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch282
2025-07-30 05:02:30.602 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.469e-03, size: 384, ETA: 1:28:51
2025-07-30 05:02:33.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 2.464e-03, size: 384, ETA: 1:28:49
2025-07-30 05:02:36.111 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 2.459e-03, size: 512, ETA: 1:28:46
2025-07-30 05:02:38.850 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.454e-03, size: 320, ETA: 1:28:44
2025-07-30 05:02:41.655 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 2.450e-03, size: 288, ETA: 1:28:41
2025-07-30 05:02:44.475 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 282/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.445e-03, size: 576, ETA: 1:28:39
2025-07-30 05:02:45.609 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:02:45.642 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch283
2025-07-30 05:02:48.341 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 2.438e-03, size: 512, ETA: 1:28:35
2025-07-30 05:02:51.121 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.433e-03, size: 256, ETA: 1:28:32
2025-07-30 05:02:53.917 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.429e-03, size: 448, ETA: 1:28:30
2025-07-30 05:02:56.728 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 2.424e-03, size: 256, ETA: 1:28:28
2025-07-30 05:02:59.566 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 2.419e-03, size: 320, ETA: 1:28:25
2025-07-30 05:03:02.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 283/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.414e-03, size: 448, ETA: 1:28:23
2025-07-30 05:03:03.702 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:03:03.737 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch284
2025-07-30 05:03:06.489 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.126s, 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: 2.408e-03, size: 448, ETA: 1:28:19
2025-07-30 05:03:09.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.120s, 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: 2.403e-03, size: 416, ETA: 1:28:16
2025-07-30 05:03:12.045 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 2.398e-03, size: 576, ETA: 1:28:13
2025-07-30 05:03:14.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.4, lr: 2.394e-03, size: 320, ETA: 1:28:11
2025-07-30 05:03:17.638 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.122s, data_time: 0.005s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 2.389e-03, size: 320, ETA: 1:28:08
2025-07-30 05:03:20.432 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 284/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.132s, 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: 2.384e-03, size: 416, ETA: 1:28:05
2025-07-30 05:03:21.615 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:03:21.718 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch285
2025-07-30 05:03:24.561 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.378e-03, size: 544, ETA: 1:28:01
2025-07-30 05:03:27.276 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, 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: 1.0, lr: 2.373e-03, size: 256, ETA: 1:27:59
2025-07-30 05:03:30.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.368e-03, size: 416, ETA: 1:27:56
2025-07-30 05:03:32.900 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.364e-03, size: 384, ETA: 1:27:54
2025-07-30 05:03:35.677 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 2.359e-03, size: 288, ETA: 1:27:51
2025-07-30 05:03:38.396 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 285/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.123s, 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: 2.354e-03, size: 384, ETA: 1:27:48
2025-07-30 05:03:39.623 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:03:46.052 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:03:49.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:03:50.917 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5366
2025-07-30 05:03:51.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4938
2025-07-30 05:03:51.501 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2546
2025-07-30 05:03:51.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4283
2025-07-30 05:03:51.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:03:51.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.537
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.494
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.255
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.428
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:03:51.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:03:51.504 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:03:53.884 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:03:56.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:03:58.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:04:00.858 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:04:03.205 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:04:05.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:04:07.912 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:04:10.252 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:04:12.582 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:04:12.582 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 05:04:12.582 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-30 05:04:12.582 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:04:12.607 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.94 ms, Average inference time: 2.31 ms

2025-07-30 05:04:12.609 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:04:12.633 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:04:12.666 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch286
2025-07-30 05:04:15.038 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.112s, data_time: 0.026s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.348e-03, size: 288, ETA: 1:27:44
2025-07-30 05:04:17.932 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.019s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 2.343e-03, size: 480, ETA: 1:27:42
2025-07-30 05:04:20.809 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.338e-03, size: 448, ETA: 1:27:39
2025-07-30 05:04:23.617 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.005s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 2.334e-03, size: 576, ETA: 1:27:37
2025-07-30 05:04:26.428 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 2.329e-03, size: 512, ETA: 1:27:34
2025-07-30 05:04:29.174 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 286/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 2.324e-03, size: 448, ETA: 1:27:32
2025-07-30 05:04:30.525 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:04:30.559 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch287
2025-07-30 05:04:33.289 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.318e-03, size: 544, ETA: 1:27:28
2025-07-30 05:04:36.143 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.313e-03, size: 480, ETA: 1:27:25
2025-07-30 05:04:38.900 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.308e-03, size: 544, ETA: 1:27:23
2025-07-30 05:04:41.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 2.304e-03, size: 288, ETA: 1:27:20
2025-07-30 05:04:44.507 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.299e-03, size: 448, ETA: 1:27:18
2025-07-30 05:04:47.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 287/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.7, lr: 2.295e-03, size: 544, ETA: 1:27:16
2025-07-30 05:04:48.642 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:04:48.693 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch288
2025-07-30 05:04:51.476 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 2.288e-03, size: 576, ETA: 1:27:12
2025-07-30 05:04:54.090 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 2.283e-03, size: 320, ETA: 1:27:09
2025-07-30 05:04:56.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.6, lr: 2.279e-03, size: 480, ETA: 1:27:06
2025-07-30 05:04:59.758 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.274e-03, size: 416, ETA: 1:27:04
2025-07-30 05:05:02.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 2.270e-03, size: 384, ETA: 1:27:01
2025-07-30 05:05:05.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 288/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 2.265e-03, size: 480, ETA: 1:26:58
2025-07-30 05:05:06.508 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:05:06.653 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch289
2025-07-30 05:05:09.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.259e-03, size: 256, ETA: 1:26:54
2025-07-30 05:05:12.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 2.254e-03, size: 384, ETA: 1:26:52
2025-07-30 05:05:15.288 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 2.250e-03, size: 256, ETA: 1:26:49
2025-07-30 05:05:18.125 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.245e-03, size: 512, ETA: 1:26:46
2025-07-30 05:05:20.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.6, lr: 2.240e-03, size: 448, ETA: 1:26:43
2025-07-30 05:05:23.773 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 289/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 2.236e-03, size: 384, ETA: 1:26:41
2025-07-30 05:05:24.981 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:05:25.030 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch290
2025-07-30 05:05:27.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 2.229e-03, size: 448, ETA: 1:26:37
2025-07-30 05:05:30.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.011s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 2.225e-03, size: 384, ETA: 1:26:34
2025-07-30 05:05:33.435 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.129s, 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: 2.220e-03, size: 352, ETA: 1:26:32
2025-07-30 05:05:36.165 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.025s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.216e-03, size: 448, ETA: 1:26:29
2025-07-30 05:05:38.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.009s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 2.211e-03, size: 416, ETA: 1:26:26
2025-07-30 05:05:41.772 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 290/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.207e-03, size: 288, ETA: 1:26:24
2025-07-30 05:05:43.127 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:05:49.504 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:05:53.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:05:55.284 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5369
2025-07-30 05:05:55.773 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4713
2025-07-30 05:05:55.873 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2775
2025-07-30 05:05:55.874 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4286
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.537
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.471
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.278
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.429
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:05:55.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:05:55.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:05:55.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:05:55.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:05:58.674 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:06:01.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:06:04.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:06:06.996 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:06:09.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:06:12.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:06:15.331 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:06:18.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:06:20.954 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:06:20.955 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 05:06:20.955 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-30 05:06:20.955 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:06:20.982 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.96 ms, Average inference time: 2.32 ms

2025-07-30 05:06:20.983 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:06:21.012 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:06:21.040 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch291
2025-07-30 05:06:23.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.120s, data_time: 0.032s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.200e-03, size: 480, ETA: 1:26:20
2025-07-30 05:06:26.290 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.137s, data_time: 0.016s, total_loss: 9.1, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 0.8, lr: 2.196e-03, size: 544, ETA: 1:26:17
2025-07-30 05:06:29.212 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.008s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 2.191e-03, size: 576, ETA: 1:26:15
2025-07-30 05:06:31.999 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, 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: 2.187e-03, size: 384, ETA: 1:26:12
2025-07-30 05:06:34.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, 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: 0.8, lr: 2.182e-03, size: 512, ETA: 1:26:10
2025-07-30 05:06:37.759 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 291/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.178e-03, size: 288, ETA: 1:26:07
2025-07-30 05:06:38.978 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:06:39.096 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch292
2025-07-30 05:06:41.776 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.3Gb, iter_time: 0.130s, 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: 2.171e-03, size: 576, ETA: 1:26:04
2025-07-30 05:06:44.627 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.021s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 2.167e-03, size: 256, ETA: 1:26:01
2025-07-30 05:06:47.420 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.163e-03, size: 512, ETA: 1:25:59
2025-07-30 05:06:50.244 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.158e-03, size: 544, ETA: 1:25:56
2025-07-30 05:06:52.994 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.154e-03, size: 288, ETA: 1:25:53
2025-07-30 05:06:55.753 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 292/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.130s, data_time: 0.015s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.149e-03, size: 544, ETA: 1:25:51
2025-07-30 05:06:57.050 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:06:57.128 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch293
2025-07-30 05:06:59.742 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.122s, data_time: 0.018s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 2.143e-03, size: 480, ETA: 1:25:47
2025-07-30 05:07:02.459 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.022s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 2.138e-03, size: 576, ETA: 1:25:44
2025-07-30 05:07:05.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 2.134e-03, size: 480, ETA: 1:25:42
2025-07-30 05:07:08.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, 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: 2.130e-03, size: 256, ETA: 1:25:39
2025-07-30 05:07:11.141 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 2.125e-03, size: 544, ETA: 1:25:36
2025-07-30 05:07:13.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 293/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.121e-03, size: 288, ETA: 1:25:34
2025-07-30 05:07:15.151 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:07:15.192 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch294
2025-07-30 05:07:17.973 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.114e-03, size: 576, ETA: 1:25:30
2025-07-30 05:07:20.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.110e-03, size: 384, ETA: 1:25:27
2025-07-30 05:07:23.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 2.106e-03, size: 384, ETA: 1:25:25
2025-07-30 05:07:26.217 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 2.101e-03, size: 384, ETA: 1:25:22
2025-07-30 05:07:29.096 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 2.097e-03, size: 480, ETA: 1:25:19
2025-07-30 05:07:31.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 294/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 2.092e-03, size: 448, ETA: 1:25:17
2025-07-30 05:07:33.072 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:07:33.215 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch295
2025-07-30 05:07:35.913 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 2.086e-03, size: 480, ETA: 1:25:13
2025-07-30 05:07:38.736 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.082e-03, size: 544, ETA: 1:25:10
2025-07-30 05:07:41.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.077e-03, size: 352, ETA: 1:25:08
2025-07-30 05:07:44.379 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.011s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.073e-03, size: 288, ETA: 1:25:05
2025-07-30 05:07:47.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.069e-03, size: 512, ETA: 1:25:03
2025-07-30 05:07:50.034 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 295/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 2.064e-03, size: 576, ETA: 1:25:00
2025-07-30 05:07:51.172 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:07:57.676 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:08:00.091 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:08:01.720 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4831
2025-07-30 05:08:01.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4323
2025-07-30 05:08:02.071 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2184
2025-07-30 05:08:02.072 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3779
2025-07-30 05:08:02.072 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.483
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.432
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.218
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.378
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:08:02.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:08:02.074 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:08:02.074 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:08:02.074 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:08:04.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:08:05.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:08:08.147 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:08:10.082 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:08:12.027 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:08:13.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:08:15.919 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:08:17.916 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:08:19.854 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:08:19.854 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-07-30 05:08:19.855 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.38
2025-07-30 05:08:19.855 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:08:19.881 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.95 ms, Average inference time: 2.32 ms

2025-07-30 05:08:19.882 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:08:19.922 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:08:19.969 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch296
2025-07-30 05:08:22.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.115s, data_time: 0.025s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.058e-03, size: 352, ETA: 1:24:56
2025-07-30 05:08:25.279 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 2.054e-03, size: 576, ETA: 1:24:54
2025-07-30 05:08:28.028 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 2.049e-03, size: 320, ETA: 1:24:51
2025-07-30 05:08:30.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.045e-03, size: 352, ETA: 1:24:48
2025-07-30 05:08:33.578 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.126s, data_time: 0.017s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 2.041e-03, size: 480, ETA: 1:24:45
2025-07-30 05:08:36.375 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 296/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.126s, data_time: 0.023s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 2.036e-03, size: 416, ETA: 1:24:43
2025-07-30 05:08:37.742 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:08:37.851 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch297
2025-07-30 05:08:40.678 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.030e-03, size: 256, ETA: 1:24:39
2025-07-30 05:08:43.327 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 2.026e-03, size: 544, ETA: 1:24:36
2025-07-30 05:08:46.098 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 2.021e-03, size: 352, ETA: 1:24:33
2025-07-30 05:08:48.904 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 2.017e-03, size: 544, ETA: 1:24:31
2025-07-30 05:08:51.519 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 2.013e-03, size: 288, ETA: 1:24:28
2025-07-30 05:08:54.350 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 297/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.120s, data_time: 0.006s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.009e-03, size: 512, ETA: 1:24:25
2025-07-30 05:08:55.568 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:08:55.633 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch298
2025-07-30 05:08:58.463 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 2.002e-03, size: 352, ETA: 1:24:22
2025-07-30 05:09:01.394 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.998e-03, size: 544, ETA: 1:24:19
2025-07-30 05:09:04.291 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 1.994e-03, size: 576, ETA: 1:24:17
2025-07-30 05:09:06.981 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.4, lr: 1.990e-03, size: 416, ETA: 1:24:14
2025-07-30 05:09:09.694 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.121s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.985e-03, size: 384, ETA: 1:24:11
2025-07-30 05:09:12.442 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 298/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.981e-03, size: 544, ETA: 1:24:09
2025-07-30 05:09:13.833 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:09:13.902 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch299
2025-07-30 05:09:16.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 1.975e-03, size: 480, ETA: 1:24:05
2025-07-30 05:09:19.544 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 1.971e-03, size: 544, ETA: 1:24:02
2025-07-30 05:09:22.411 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 1.966e-03, size: 544, ETA: 1:23:59
2025-07-30 05:09:25.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.130s, 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: 1.962e-03, size: 512, ETA: 1:23:57
2025-07-30 05:09:27.873 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.958e-03, size: 320, ETA: 1:23:54
2025-07-30 05:09:30.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 299/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.145s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.954e-03, size: 448, ETA: 1:23:52
2025-07-30 05:09:32.017 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:09:32.145 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch300
2025-07-30 05:09:34.868 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 1.948e-03, size: 576, ETA: 1:23:48
2025-07-30 05:09:37.703 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 1.943e-03, size: 448, ETA: 1:23:46
2025-07-30 05:09:40.600 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.939e-03, size: 576, ETA: 1:23:43
2025-07-30 05:09:43.413 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.935e-03, size: 416, ETA: 1:23:41
2025-07-30 05:09:46.427 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.145s, data_time: 0.001s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 1.931e-03, size: 352, ETA: 1:23:39
2025-07-30 05:09:49.141 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 300/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 1.1, lr: 1.927e-03, size: 288, ETA: 1:23:36
2025-07-30 05:09:50.423 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:09:56.842 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:09:59.458 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:10:01.233 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5295
2025-07-30 05:10:01.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4554
2025-07-30 05:10:01.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2608
2025-07-30 05:10:01.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4153
2025-07-30 05:10:01.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:10:01.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:10:01.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.530
2025-07-30 05:10:01.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.455
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.261
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.415
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:10:01.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:10:03.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:10:06.131 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:10:08.267 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:10:10.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:10:12.570 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:10:14.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:10:16.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:10:18.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:10:21.121 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:10:21.121 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-30 05:10:21.121 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-30 05:10:21.121 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:10:21.146 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.99 ms, Average inference time: 2.36 ms

2025-07-30 05:10:21.152 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:10:21.176 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:10:21.205 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch301
2025-07-30 05:10:23.727 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.117s, data_time: 0.005s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 1.921e-03, size: 512, ETA: 1:23:32
2025-07-30 05:10:26.621 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.916e-03, size: 576, ETA: 1:23:30
2025-07-30 05:10:29.531 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.130s, 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: 1.912e-03, size: 480, ETA: 1:23:27
2025-07-30 05:10:32.204 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.908e-03, size: 320, ETA: 1:23:24
2025-07-30 05:10:34.998 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.904e-03, size: 384, ETA: 1:23:22
2025-07-30 05:10:37.957 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 301/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.900e-03, size: 544, ETA: 1:23:20
2025-07-30 05:10:39.193 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:10:39.240 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch302
2025-07-30 05:10:42.057 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.130s, data_time: 0.001s, 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: 480, ETA: 1:23:16
2025-07-30 05:10:44.781 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.890e-03, size: 480, ETA: 1:23:13
2025-07-30 05:10:47.552 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 1.886e-03, size: 416, ETA: 1:23:11
2025-07-30 05:10:50.411 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.881e-03, size: 352, ETA: 1:23:08
2025-07-30 05:10:53.183 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.005s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.877e-03, size: 544, ETA: 1:23:05
2025-07-30 05:10:55.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 302/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 1.873e-03, size: 576, ETA: 1:23:03
2025-07-30 05:10:57.262 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:10:57.337 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch303
2025-07-30 05:11:00.100 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.6, lr: 1.867e-03, size: 544, ETA: 1:22:59
2025-07-30 05:11:02.883 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.863e-03, size: 352, ETA: 1:22:56
2025-07-30 05:11:05.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.128s, 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: 1.859e-03, size: 288, ETA: 1:22:54
2025-07-30 05:11:08.338 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.855e-03, size: 352, ETA: 1:22:51
2025-07-30 05:11:11.172 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.851e-03, size: 384, ETA: 1:22:48
2025-07-30 05:11:14.110 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 303/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 1.847e-03, size: 480, ETA: 1:22:46
2025-07-30 05:11:15.311 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:11:15.362 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch304
2025-07-30 05:11:18.145 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.129s, 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: 1.841e-03, size: 288, ETA: 1:22:42
2025-07-30 05:11:20.982 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.040s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 1.837e-03, size: 576, ETA: 1:22:40
2025-07-30 05:11:23.708 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.005s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.833e-03, size: 256, ETA: 1:22:37
2025-07-30 05:11:26.397 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.008s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.829e-03, size: 256, ETA: 1:22:35
2025-07-30 05:11:29.147 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.824e-03, size: 384, ETA: 1:22:32
2025-07-30 05:11:31.965 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 304/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, 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: 1.820e-03, size: 512, ETA: 1:22:29
2025-07-30 05:11:33.259 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:11:33.294 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch305
2025-07-30 05:11:36.050 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.815e-03, size: 416, ETA: 1:22:26
2025-07-30 05:11:38.860 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.811e-03, size: 256, ETA: 1:22:23
2025-07-30 05:11:41.527 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.806e-03, size: 352, ETA: 1:22:21
2025-07-30 05:11:44.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.140s, data_time: 0.005s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 1.802e-03, size: 384, ETA: 1:22:18
2025-07-30 05:11:47.141 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 1.798e-03, size: 320, ETA: 1:22:16
2025-07-30 05:11:50.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 305/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.794e-03, size: 352, ETA: 1:22:13
2025-07-30 05:11:51.311 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:11:57.566 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:11:59.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:12:01.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5241
2025-07-30 05:12:01.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4593
2025-07-30 05:12:01.624 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2850
2025-07-30 05:12:01.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4228
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.524
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.459
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.285
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.423
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:12:01.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:12:01.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:12:01.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:12:01.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:12:01.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:12:01.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:12:03.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:12:05.282 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:12:07.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:12:08.885 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:12:10.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:12:12.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:12:14.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:12:16.393 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:12:18.211 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:12:18.212 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-07-30 05:12:18.212 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-30 05:12:18.212 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:12:18.237 | 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

2025-07-30 05:12:18.238 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:12:18.261 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:12:18.293 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch306
2025-07-30 05:12:20.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.107s, data_time: 0.025s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 1.789e-03, size: 576, ETA: 1:22:09
2025-07-30 05:12:23.538 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.018s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.785e-03, size: 416, ETA: 1:22:07
2025-07-30 05:12:26.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.781e-03, size: 576, ETA: 1:22:04
2025-07-30 05:12:29.181 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.777e-03, size: 416, ETA: 1:22:02
2025-07-30 05:12:32.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.142s, data_time: 0.001s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.773e-03, size: 288, ETA: 1:21:59
2025-07-30 05:12:35.020 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 306/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.122s, 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: 1.769e-03, size: 448, ETA: 1:21:56
2025-07-30 05:12:36.163 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:12:36.327 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch307
2025-07-30 05:12:39.124 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 1.763e-03, size: 416, ETA: 1:21:52
2025-07-30 05:12:41.922 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.759e-03, size: 512, ETA: 1:21:50
2025-07-30 05:12:44.751 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.755e-03, size: 352, ETA: 1:21:47
2025-07-30 05:12:47.551 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 1.751e-03, size: 544, ETA: 1:21:44
2025-07-30 05:12:50.297 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.119s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 1.747e-03, size: 576, ETA: 1:21:42
2025-07-30 05:12:53.204 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 307/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.743e-03, size: 448, ETA: 1:21:39
2025-07-30 05:12:54.382 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:12:54.428 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch308
2025-07-30 05:12:57.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.737e-03, size: 480, ETA: 1:21:35
2025-07-30 05:13:00.083 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.733e-03, size: 320, ETA: 1:21:32
2025-07-30 05:13:02.890 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 1.729e-03, size: 512, ETA: 1:21:30
2025-07-30 05:13:05.846 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 1.725e-03, size: 544, ETA: 1:21:27
2025-07-30 05:13:08.694 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.722e-03, size: 512, ETA: 1:21:25
2025-07-30 05:13:11.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 308/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 1.718e-03, size: 544, ETA: 1:21:22
2025-07-30 05:13:12.790 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:13:12.909 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch309
2025-07-30 05:13:15.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 1.712e-03, size: 256, ETA: 1:21:18
2025-07-30 05:13:18.574 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 1.708e-03, size: 320, ETA: 1:21:16
2025-07-30 05:13:21.382 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.5, lr: 1.704e-03, size: 544, ETA: 1:21:13
2025-07-30 05:13:24.206 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.700e-03, size: 256, ETA: 1:21:10
2025-07-30 05:13:27.024 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.696e-03, size: 416, ETA: 1:21:08
2025-07-30 05:13:29.884 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 309/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 1.692e-03, size: 352, ETA: 1:21:06
2025-07-30 05:13:31.077 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:13:31.179 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch310
2025-07-30 05:13:33.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.687e-03, size: 416, ETA: 1:21:02
2025-07-30 05:13:36.824 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.683e-03, size: 256, ETA: 1:20:59
2025-07-30 05:13:39.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 1.679e-03, size: 512, ETA: 1:20:57
2025-07-30 05:13:42.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.011s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.675e-03, size: 448, ETA: 1:20:54
2025-07-30 05:13:45.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.671e-03, size: 448, ETA: 1:20:52
2025-07-30 05:13:47.969 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 310/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.668e-03, size: 384, ETA: 1:20:49
2025-07-30 05:13:49.219 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:13:55.607 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:13:59.689 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:14:01.806 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5260
2025-07-30 05:14:02.352 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4633
2025-07-30 05:14:02.410 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2684
2025-07-30 05:14:02.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4192
2025-07-30 05:14:02.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:14:02.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:14:02.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.526
2025-07-30 05:14:02.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.463
2025-07-30 05:14:02.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.268
2025-07-30 05:14:02.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.419
2025-07-30 05:14:02.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:14:02.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:14:02.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:14:02.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:14:02.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:14:02.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:14:02.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:14:02.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:14:02.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:14:05.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:14:07.975 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:14:10.716 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:14:13.570 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:14:16.070 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:14:18.591 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:14:21.096 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:14:23.541 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:14:26.024 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:14:26.025 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 05:14:26.025 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-30 05:14:26.025 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:14:26.050 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.95 ms, Average inference time: 2.30 ms

2025-07-30 05:14:26.052 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:14:26.078 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:14:26.108 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch311
2025-07-30 05:14:28.567 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.118s, data_time: 0.004s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.662e-03, size: 416, ETA: 1:20:45
2025-07-30 05:14:31.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.658e-03, size: 512, ETA: 1:20:43
2025-07-30 05:14:34.284 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.654e-03, size: 448, ETA: 1:20:40
2025-07-30 05:14:37.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.650e-03, size: 512, ETA: 1:20:38
2025-07-30 05:14:39.888 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.647e-03, size: 352, ETA: 1:20:35
2025-07-30 05:14:42.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 311/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.643e-03, size: 576, ETA: 1:20:32
2025-07-30 05:14:43.850 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:14:43.885 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch312
2025-07-30 05:14:46.610 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 1.637e-03, size: 512, ETA: 1:20:29
2025-07-30 05:14:49.418 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.131s, 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: 1.634e-03, size: 320, ETA: 1:20:26
2025-07-30 05:14:52.222 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.630e-03, size: 512, ETA: 1:20:23
2025-07-30 05:14:55.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.626e-03, size: 576, ETA: 1:20:21
2025-07-30 05:14:57.831 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.622e-03, size: 352, ETA: 1:20:18
2025-07-30 05:15:00.512 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 312/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.121s, data_time: 0.007s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 1.618e-03, size: 288, ETA: 1:20:15
2025-07-30 05:15:01.739 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:15:01.889 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch313
2025-07-30 05:15:04.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.613e-03, size: 544, ETA: 1:20:11
2025-07-30 05:15:07.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.4, lr: 1.609e-03, size: 320, ETA: 1:20:09
2025-07-30 05:15:10.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 1.605e-03, size: 384, ETA: 1:20:07
2025-07-30 05:15:13.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.602e-03, size: 384, ETA: 1:20:04
2025-07-30 05:15:16.127 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.144s, 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: 1.598e-03, size: 512, ETA: 1:20:02
2025-07-30 05:15:18.879 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 313/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.594e-03, size: 448, ETA: 1:19:59
2025-07-30 05:15:20.152 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:15:20.274 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch314
2025-07-30 05:15:22.999 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.589e-03, size: 320, ETA: 1:19:56
2025-07-30 05:15:25.911 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.137s, 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: 1.585e-03, size: 288, ETA: 1:19:53
2025-07-30 05:15:28.604 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 1.581e-03, size: 416, ETA: 1:19:51
2025-07-30 05:15:31.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.578e-03, size: 256, ETA: 1:19:48
2025-07-30 05:15:34.172 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.574e-03, size: 288, ETA: 1:19:45
2025-07-30 05:15:37.041 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 314/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.570e-03, size: 384, ETA: 1:19:43
2025-07-30 05:15:38.252 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:15:38.359 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch315
2025-07-30 05:15:41.198 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.565e-03, size: 512, ETA: 1:19:39
2025-07-30 05:15:43.951 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.561e-03, size: 480, ETA: 1:19:36
2025-07-30 05:15:46.786 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.557e-03, size: 480, ETA: 1:19:34
2025-07-30 05:15:49.642 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.554e-03, size: 256, ETA: 1:19:31
2025-07-30 05:15:52.447 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.550e-03, size: 256, ETA: 1:19:29
2025-07-30 05:15:55.214 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 315/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.546e-03, size: 288, ETA: 1:19:26
2025-07-30 05:15:56.481 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:16:03.074 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:16:06.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:16:08.230 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5354
2025-07-30 05:16:08.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4636
2025-07-30 05:16:08.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2552
2025-07-30 05:16:08.739 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4181
2025-07-30 05:16:08.739 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:16:08.739 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:16:08.739 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.535
2025-07-30 05:16:08.739 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.464
2025-07-30 05:16:08.739 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.255
2025-07-30 05:16:08.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.418
2025-07-30 05:16:08.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:16:08.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:16:08.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:16:08.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:16:08.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:16:08.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:16:08.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:16:08.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:16:08.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:16:11.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:16:13.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:16:16.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:16:18.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:16:21.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:16:24.091 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:16:26.635 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:16:29.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:16:31.732 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:16:31.732 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 05:16:31.732 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-30 05:16:31.732 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:16:31.757 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.97 ms, Average inference time: 2.36 ms

2025-07-30 05:16:31.758 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:16:31.783 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:16:31.814 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch316
2025-07-30 05:16:34.222 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.117s, data_time: 0.029s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.541e-03, size: 320, ETA: 1:19:22
2025-07-30 05:16:37.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.137s, data_time: 0.012s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 1.537e-03, size: 320, ETA: 1:19:20
2025-07-30 05:16:39.969 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.534e-03, size: 384, ETA: 1:19:17
2025-07-30 05:16:42.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.130s, 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: 1.530e-03, size: 256, ETA: 1:19:15
2025-07-30 05:16:45.688 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 1.526e-03, size: 448, ETA: 1:19:12
2025-07-30 05:16:48.440 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 316/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 1.523e-03, size: 288, ETA: 1:19:09
2025-07-30 05:16:49.669 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:16:49.788 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch317
2025-07-30 05:16:52.631 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.127s, 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: 1.518e-03, size: 384, ETA: 1:19:05
2025-07-30 05:16:55.504 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.127s, 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: 1.514e-03, size: 384, ETA: 1:19:03
2025-07-30 05:16:58.244 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 1.510e-03, size: 352, ETA: 1:19:00
2025-07-30 05:17:01.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 1.507e-03, size: 416, ETA: 1:18:57
2025-07-30 05:17:03.790 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.008s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.503e-03, size: 256, ETA: 1:18:55
2025-07-30 05:17:06.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 317/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.500e-03, size: 320, ETA: 1:18:52
2025-07-30 05:17:07.792 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:17:07.900 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch318
2025-07-30 05:17:10.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.494e-03, size: 288, ETA: 1:18:48
2025-07-30 05:17:13.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 1.491e-03, size: 576, ETA: 1:18:45
2025-07-30 05:17:16.189 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.015s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.487e-03, size: 448, ETA: 1:18:43
2025-07-30 05:17:19.153 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.135s, 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: 1.484e-03, size: 256, ETA: 1:18:40
2025-07-30 05:17:21.963 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.2, lr: 1.480e-03, size: 256, ETA: 1:18:38
2025-07-30 05:17:24.592 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 318/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.123s, 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: 1.476e-03, size: 416, ETA: 1:18:35
2025-07-30 05:17:25.871 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:17:26.007 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch319
2025-07-30 05:17:28.699 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.118s, 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: 1.471e-03, size: 416, ETA: 1:18:31
2025-07-30 05:17:31.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.122s, 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: 1.468e-03, size: 576, ETA: 1:18:28
2025-07-30 05:17:34.335 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 1.464e-03, size: 384, ETA: 1:18:26
2025-07-30 05:17:37.157 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.4, lr: 1.461e-03, size: 352, ETA: 1:18:23
2025-07-30 05:17:39.934 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.123s, 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: 1.457e-03, size: 576, ETA: 1:18:20
2025-07-30 05:17:42.745 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 319/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.454e-03, size: 480, ETA: 1:18:18
2025-07-30 05:17:43.961 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:17:44.007 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch320
2025-07-30 05:17:46.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.4Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.449e-03, size: 416, ETA: 1:18:14
2025-07-30 05:17:49.808 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 1.445e-03, size: 576, ETA: 1:18:11
2025-07-30 05:17:52.639 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.442e-03, size: 576, ETA: 1:18:09
2025-07-30 05:17:55.486 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 1.438e-03, size: 576, ETA: 1:18:06
2025-07-30 05:17:58.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.132s, data_time: 0.020s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.435e-03, size: 576, ETA: 1:18:04
2025-07-30 05:18:00.906 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 320/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.017s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.431e-03, size: 384, ETA: 1:18:01
2025-07-30 05:18:02.147 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:18:08.652 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:18:11.111 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:18:12.683 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5385
2025-07-30 05:18:13.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4666
2025-07-30 05:18:13.189 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2769
2025-07-30 05:18:13.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4274
2025-07-30 05:18:13.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:18:13.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.539
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.467
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.277
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.427
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:18:13.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:18:13.192 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:18:15.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:18:17.104 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:18:19.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:18:21.072 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:18:23.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:18:25.091 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:18:27.034 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:18:29.016 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:18:30.943 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:18:30.944 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 05:18:30.944 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-30 05:18:30.944 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:18:30.969 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.93 ms, Average inference time: 2.33 ms

2025-07-30 05:18:30.970 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:18:30.991 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:18:31.019 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch321
2025-07-30 05:18:33.418 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.114s, data_time: 0.006s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.426e-03, size: 256, ETA: 1:17:57
2025-07-30 05:18:36.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.423e-03, size: 384, ETA: 1:17:55
2025-07-30 05:18:39.095 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.419e-03, size: 576, ETA: 1:17:52
2025-07-30 05:18:41.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.7, lr: 1.416e-03, size: 352, ETA: 1:17:50
2025-07-30 05:18:44.590 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.123s, data_time: 0.005s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 1.412e-03, size: 288, ETA: 1:17:47
2025-07-30 05:18:47.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 321/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.127s, data_time: 0.004s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 1.409e-03, size: 480, ETA: 1:17:44
2025-07-30 05:18:48.526 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:18:48.663 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch322
2025-07-30 05:18:51.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 1.404e-03, size: 320, ETA: 1:17:41
2025-07-30 05:18:54.306 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.400e-03, size: 352, ETA: 1:17:38
2025-07-30 05:18:57.067 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 1.397e-03, size: 448, ETA: 1:17:35
2025-07-30 05:18:59.938 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 1.393e-03, size: 352, ETA: 1:17:33
2025-07-30 05:19:02.721 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 1.390e-03, size: 448, ETA: 1:17:30
2025-07-30 05:19:05.495 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 322/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.387e-03, size: 512, ETA: 1:17:28
2025-07-30 05:19:06.670 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:19:06.835 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch323
2025-07-30 05:19:09.563 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.382e-03, size: 448, ETA: 1:17:24
2025-07-30 05:19:12.395 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 1.378e-03, size: 416, ETA: 1:17:21
2025-07-30 05:19:15.169 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.375e-03, size: 448, ETA: 1:17:18
2025-07-30 05:19:17.959 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.131s, data_time: 0.006s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.372e-03, size: 416, ETA: 1:17:16
2025-07-30 05:19:20.718 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 1.368e-03, size: 480, ETA: 1:17:13
2025-07-30 05:19:23.428 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 323/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.365e-03, size: 480, ETA: 1:17:10
2025-07-30 05:19:24.619 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:19:24.755 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch324
2025-07-30 05:19:27.493 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, 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: 1.360e-03, size: 256, ETA: 1:17:07
2025-07-30 05:19:30.457 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.357e-03, size: 384, ETA: 1:17:04
2025-07-30 05:19:33.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 1.353e-03, size: 256, ETA: 1:17:01
2025-07-30 05:19:35.875 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 1.350e-03, size: 320, ETA: 1:16:59
2025-07-30 05:19:38.718 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 7.3, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.346e-03, size: 384, ETA: 1:16:56
2025-07-30 05:19:41.542 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 324/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.343e-03, size: 256, ETA: 1:16:54
2025-07-30 05:19:42.758 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:19:42.809 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch325
2025-07-30 05:19:45.543 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 1.338e-03, size: 288, ETA: 1:16:50
2025-07-30 05:19:48.423 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.335e-03, size: 448, ETA: 1:16:48
2025-07-30 05:19:51.389 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.332e-03, size: 576, ETA: 1:16:45
2025-07-30 05:19:54.041 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.328e-03, size: 448, ETA: 1:16:43
2025-07-30 05:19:56.840 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.139s, 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: 1.325e-03, size: 512, ETA: 1:16:40
2025-07-30 05:19:59.773 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 325/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 1.322e-03, size: 576, ETA: 1:16:38
2025-07-30 05:20:00.958 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:20:07.381 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:20:10.637 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:20:12.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5406
2025-07-30 05:20:12.663 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4979
2025-07-30 05:20:12.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2852
2025-07-30 05:20:12.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4412
2025-07-30 05:20:12.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:20:12.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:20:12.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.541
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.498
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.285
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.441
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:20:12.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:20:12.815 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:20:12.815 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:20:14.964 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:20:17.122 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:20:19.294 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:20:21.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:20:23.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:20:25.299 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:20:27.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:20:29.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:20:31.112 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:20:31.113 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 05:20:31.113 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-30 05:20:31.114 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:20:31.147 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.92 ms, Average inference time: 2.28 ms

2025-07-30 05:20:31.148 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:20:31.183 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:20:31.283 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch326
2025-07-30 05:20:33.641 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.117s, data_time: 0.028s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.317e-03, size: 256, ETA: 1:16:34
2025-07-30 05:20:36.362 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 1.314e-03, size: 352, ETA: 1:16:31
2025-07-30 05:20:39.223 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 1.310e-03, size: 512, ETA: 1:16:29
2025-07-30 05:20:41.987 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 1.307e-03, size: 320, ETA: 1:16:26
2025-07-30 05:20:44.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.304e-03, size: 544, ETA: 1:16:23
2025-07-30 05:20:47.556 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 326/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.301e-03, size: 352, ETA: 1:16:21
2025-07-30 05:20:48.760 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:20:48.890 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch327
2025-07-30 05:20:51.600 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.296e-03, size: 448, ETA: 1:16:17
2025-07-30 05:20:54.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 1.293e-03, size: 288, ETA: 1:16:14
2025-07-30 05:20:57.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.289e-03, size: 448, ETA: 1:16:12
2025-07-30 05:20:59.951 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.286e-03, size: 512, ETA: 1:16:09
2025-07-30 05:21:02.662 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.033s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.283e-03, size: 352, ETA: 1:16:07
2025-07-30 05:21:05.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 327/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.137s, 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: 1.280e-03, size: 384, ETA: 1:16:04
2025-07-30 05:21:06.808 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:21:06.905 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch328
2025-07-30 05:21:09.554 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.120s, data_time: 0.024s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.275e-03, size: 576, ETA: 1:16:00
2025-07-30 05:21:12.384 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, 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: 1.272e-03, size: 448, ETA: 1:15:58
2025-07-30 05:21:15.283 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.269e-03, size: 288, ETA: 1:15:55
2025-07-30 05:21:18.064 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, 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: 1.266e-03, size: 416, ETA: 1:15:52
2025-07-30 05:21:20.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.262e-03, size: 320, ETA: 1:15:50
2025-07-30 05:21:23.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 328/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.259e-03, size: 352, ETA: 1:15:47
2025-07-30 05:21:24.934 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:21:25.094 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch329
2025-07-30 05:21:27.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.255e-03, size: 288, ETA: 1:15:43
2025-07-30 05:21:30.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.130s, data_time: 0.020s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.251e-03, size: 448, ETA: 1:15:41
2025-07-30 05:21:33.416 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 1.248e-03, size: 448, ETA: 1:15:38
2025-07-30 05:21:36.291 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 1.245e-03, size: 384, ETA: 1:15:36
2025-07-30 05:21:39.223 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.242e-03, size: 320, ETA: 1:15:34
2025-07-30 05:21:41.990 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 329/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.239e-03, size: 512, ETA: 1:15:31
2025-07-30 05:21:43.260 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:21:43.394 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch330
2025-07-30 05:21:46.185 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.133s, 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: 1.234e-03, size: 480, ETA: 1:15:27
2025-07-30 05:21:48.967 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.231e-03, size: 448, ETA: 1:15:25
2025-07-30 05:21:51.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.228e-03, size: 288, ETA: 1:15:22
2025-07-30 05:21:54.540 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 1.225e-03, size: 544, ETA: 1:15:20
2025-07-30 05:21:57.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 1.222e-03, size: 544, ETA: 1:15:17
2025-07-30 05:22:00.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 330/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, 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: 1.219e-03, size: 288, ETA: 1:15:15
2025-07-30 05:22:01.303 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:22:07.760 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:22:10.486 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:22:12.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5489
2025-07-30 05:22:12.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4666
2025-07-30 05:22:12.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2986
2025-07-30 05:22:12.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4380
2025-07-30 05:22:12.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:22:12.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:22:12.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.549
2025-07-30 05:22:12.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.467
2025-07-30 05:22:12.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.299
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.438
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:22:12.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:22:14.874 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:22:17.067 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:22:19.282 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:22:21.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:22:23.659 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:22:25.854 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:22:28.013 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:22:30.229 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:22:32.445 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:22:32.445 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:22:32.446 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-30 05:22:32.446 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:22:32.474 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.95 ms, Average inference time: 2.33 ms

2025-07-30 05:22:32.475 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:22:32.507 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:22:32.547 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch331
2025-07-30 05:22:35.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.121s, data_time: 0.041s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.214e-03, size: 544, ETA: 1:15:11
2025-07-30 05:22:37.753 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.047s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.211e-03, size: 512, ETA: 1:15:08
2025-07-30 05:22:40.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.012s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 1.208e-03, size: 256, ETA: 1:15:06
2025-07-30 05:22:43.318 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.1, lr: 1.205e-03, size: 320, ETA: 1:15:03
2025-07-30 05:22:46.086 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 1.202e-03, size: 288, ETA: 1:15:01
2025-07-30 05:22:48.783 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 331/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.199e-03, size: 384, ETA: 1:14:58
2025-07-30 05:22:49.932 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:22:50.076 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch332
2025-07-30 05:22:52.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.194e-03, size: 512, ETA: 1:14:55
2025-07-30 05:22:55.679 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, 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: 1.191e-03, size: 576, ETA: 1:14:52
2025-07-30 05:22:58.461 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 1.188e-03, size: 320, ETA: 1:14:49
2025-07-30 05:23:01.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, 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: 1.185e-03, size: 448, ETA: 1:14:47
2025-07-30 05:23:04.268 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 1.182e-03, size: 544, ETA: 1:14:44
2025-07-30 05:23:07.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 332/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.126s, 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: 1.179e-03, size: 576, ETA: 1:14:42
2025-07-30 05:23:08.288 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:23:08.416 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch333
2025-07-30 05:23:11.174 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.117s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.175e-03, size: 416, ETA: 1:14:38
2025-07-30 05:23:13.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 1.172e-03, size: 416, ETA: 1:14:35
2025-07-30 05:23:16.796 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.169e-03, size: 480, ETA: 1:14:32
2025-07-30 05:23:19.559 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 1.166e-03, size: 416, ETA: 1:14:30
2025-07-30 05:23:22.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.163e-03, size: 384, ETA: 1:14:27
2025-07-30 05:23:25.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 333/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.160e-03, size: 288, ETA: 1:14:24
2025-07-30 05:23:26.350 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:23:26.470 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch334
2025-07-30 05:23:29.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.156e-03, size: 512, ETA: 1:14:21
2025-07-30 05:23:32.120 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.153e-03, size: 544, ETA: 1:14:18
2025-07-30 05:23:34.940 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 1.150e-03, size: 448, ETA: 1:14:15
2025-07-30 05:23:37.737 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.128s, 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: 1.147e-03, size: 448, ETA: 1:14:13
2025-07-30 05:23:40.478 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.144e-03, size: 480, ETA: 1:14:10
2025-07-30 05:23:43.349 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 334/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.141e-03, size: 512, ETA: 1:14:08
2025-07-30 05:23:44.611 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:23:44.736 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch335
2025-07-30 05:23:47.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.137e-03, size: 384, ETA: 1:14:04
2025-07-30 05:23:50.395 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.134e-03, size: 320, ETA: 1:14:01
2025-07-30 05:23:53.153 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.119s, data_time: 0.003s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 1.131e-03, size: 256, ETA: 1:13:58
2025-07-30 05:23:55.916 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.128e-03, size: 320, ETA: 1:13:56
2025-07-30 05:23:58.696 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, 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: 1.125e-03, size: 480, ETA: 1:13:53
2025-07-30 05:24:01.505 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 335/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.122e-03, size: 352, ETA: 1:13:51
2025-07-30 05:24:02.607 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:24:08.912 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:24:11.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:24:12.748 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5385
2025-07-30 05:24:13.066 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4885
2025-07-30 05:24:13.160 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2905
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4392
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.539
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.489
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.290
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.439
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:24:13.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:24:13.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:24:13.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:24:13.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:24:13.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:24:13.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:24:13.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:24:15.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:24:16.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:24:18.776 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:24:20.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:24:22.652 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:24:24.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:24:26.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:24:28.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:24:30.517 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:24:30.517 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 05:24:30.518 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-30 05:24:30.518 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:24:30.545 | 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

2025-07-30 05:24:30.547 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:24:30.585 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:24:30.634 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch336
2025-07-30 05:24:33.042 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.113s, data_time: 0.032s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.118e-03, size: 576, ETA: 1:13:47
2025-07-30 05:24:35.847 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.125s, data_time: 0.026s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 1.115e-03, size: 512, ETA: 1:13:44
2025-07-30 05:24:38.679 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 1.112e-03, size: 448, ETA: 1:13:42
2025-07-30 05:24:41.518 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 1.109e-03, size: 416, ETA: 1:13:39
2025-07-30 05:24:44.463 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 1.106e-03, size: 480, ETA: 1:13:37
2025-07-30 05:24:47.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 336/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.022s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 1.103e-03, size: 448, ETA: 1:13:34
2025-07-30 05:24:48.365 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:24:48.401 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch337
2025-07-30 05:24:51.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.133s, data_time: 0.021s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.099e-03, size: 352, ETA: 1:13:30
2025-07-30 05:24:53.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 8.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 0.9, lr: 1.096e-03, size: 576, ETA: 1:13:28
2025-07-30 05:24:56.657 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 1.094e-03, size: 320, ETA: 1:13:25
2025-07-30 05:24:59.475 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 1.091e-03, size: 384, ETA: 1:13:23
2025-07-30 05:25:02.251 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.088e-03, size: 352, ETA: 1:13:20
2025-07-30 05:25:05.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 337/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.085e-03, size: 352, ETA: 1:13:18
2025-07-30 05:25:06.361 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:25:06.408 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch338
2025-07-30 05:25:09.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 1.081e-03, size: 288, ETA: 1:13:14
2025-07-30 05:25:12.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 1.078e-03, size: 512, ETA: 1:13:11
2025-07-30 05:25:14.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.075e-03, size: 544, ETA: 1:13:09
2025-07-30 05:25:17.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 1.073e-03, size: 288, ETA: 1:13:06
2025-07-30 05:25:20.524 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.127s, 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: 1.070e-03, size: 512, ETA: 1:13:03
2025-07-30 05:25:23.237 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 338/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.067e-03, size: 320, ETA: 1:13:01
2025-07-30 05:25:24.461 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:25:24.505 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch339
2025-07-30 05:25:27.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.011s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.063e-03, size: 320, ETA: 1:12:57
2025-07-30 05:25:30.154 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.060e-03, size: 384, ETA: 1:12:55
2025-07-30 05:25:33.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 1.058e-03, size: 416, ETA: 1:12:52
2025-07-30 05:25:35.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 1.055e-03, size: 512, ETA: 1:12:50
2025-07-30 05:25:38.685 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, 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: 1.052e-03, size: 352, ETA: 1:12:47
2025-07-30 05:25:41.469 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 339/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.049e-03, size: 288, ETA: 1:12:44
2025-07-30 05:25:42.761 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:25:42.802 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch340
2025-07-30 05:25:45.699 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.131s, 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: 1.045e-03, size: 352, ETA: 1:12:40
2025-07-30 05:25:48.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 1.043e-03, size: 576, ETA: 1:12:38
2025-07-30 05:25:51.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.040e-03, size: 384, ETA: 1:12:35
2025-07-30 05:25:54.027 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 1.037e-03, size: 544, ETA: 1:12:33
2025-07-30 05:25:56.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 9.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 5.6, cls_loss: 0.9, lr: 1.035e-03, size: 480, ETA: 1:12:30
2025-07-30 05:25:59.686 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 340/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.032e-03, size: 480, ETA: 1:12:27
2025-07-30 05:26:01.128 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:26:07.596 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:26:10.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:26:11.600 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5564
2025-07-30 05:26:11.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4935
2025-07-30 05:26:12.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2810
2025-07-30 05:26:12.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4436
2025-07-30 05:26:12.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:26:12.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:26:12.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.556
2025-07-30 05:26:12.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.493
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.281
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.444
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:26:12.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:26:12.044 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:26:14.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:26:16.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:26:18.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:26:20.050 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:26:21.990 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:26:23.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:26:25.857 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:26:27.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:26:29.747 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:26:29.747 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 05:26:29.747 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-30 05:26:29.747 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:26:29.774 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.34 ms, Average NMS time: 0.95 ms, Average inference time: 2.29 ms

2025-07-30 05:26:29.775 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:26:29.805 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:26:29.836 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch341
2025-07-30 05:26:32.229 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.118s, data_time: 0.022s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 1.028e-03, size: 512, ETA: 1:12:23
2025-07-30 05:26:35.075 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.025e-03, size: 320, ETA: 1:12:21
2025-07-30 05:26:37.972 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.023e-03, size: 416, ETA: 1:12:19
2025-07-30 05:26:40.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.020e-03, size: 256, ETA: 1:12:16
2025-07-30 05:26:43.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 1.017e-03, size: 288, ETA: 1:12:13
2025-07-30 05:26:46.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 341/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.015e-03, size: 544, ETA: 1:12:11
2025-07-30 05:26:47.379 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:26:47.494 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch342
2025-07-30 05:26:50.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.015s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 1.011e-03, size: 544, ETA: 1:12:07
2025-07-30 05:26:52.997 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.008e-03, size: 480, ETA: 1:12:04
2025-07-30 05:26:55.831 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, 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: 1.006e-03, size: 256, ETA: 1:12:02
2025-07-30 05:26:58.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, 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: 1.003e-03, size: 544, ETA: 1:11:59
2025-07-30 05:27:01.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.5Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.000e-03, size: 384, ETA: 1:11:57
2025-07-30 05:27:04.199 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 342/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.977e-04, size: 352, ETA: 1:11:54
2025-07-30 05:27:05.414 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:27:05.549 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch343
2025-07-30 05:27:08.325 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 8.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 1.0, lr: 9.939e-04, size: 576, ETA: 1:11:50
2025-07-30 05:27:11.031 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.913e-04, size: 288, ETA: 1:11:47
2025-07-30 05:27:13.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.128s, 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: 9.887e-04, size: 320, ETA: 1:11:45
2025-07-30 05:27:16.611 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.122s, data_time: 0.008s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.861e-04, size: 544, ETA: 1:11:42
2025-07-30 05:27:19.464 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.835e-04, size: 512, ETA: 1:11:40
2025-07-30 05:27:22.171 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 343/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.022s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 9.810e-04, size: 416, ETA: 1:11:37
2025-07-30 05:27:23.389 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:27:23.497 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch344
2025-07-30 05:27:26.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.772e-04, size: 320, ETA: 1:11:33
2025-07-30 05:27:29.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.747e-04, size: 384, ETA: 1:11:31
2025-07-30 05:27:31.986 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.721e-04, size: 512, ETA: 1:11:28
2025-07-30 05:27:34.887 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, 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: 9.696e-04, size: 512, ETA: 1:11:25
2025-07-30 05:27:37.685 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.671e-04, size: 448, ETA: 1:11:23
2025-07-30 05:27:40.349 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 344/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.120s, data_time: 0.007s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 9.645e-04, size: 320, ETA: 1:11:20
2025-07-30 05:27:41.520 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:27:41.682 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch345
2025-07-30 05:27:44.480 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.609e-04, size: 512, ETA: 1:11:16
2025-07-30 05:27:47.197 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.118s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.584e-04, size: 256, ETA: 1:11:13
2025-07-30 05:27:50.012 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.122s, data_time: 0.003s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 9.559e-04, size: 480, ETA: 1:11:11
2025-07-30 05:27:52.883 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.534e-04, size: 544, ETA: 1:11:08
2025-07-30 05:27:55.697 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 9.509e-04, size: 416, ETA: 1:11:05
2025-07-30 05:27:58.527 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 345/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.126s, 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: 9.484e-04, size: 352, ETA: 1:11:03
2025-07-30 05:27:59.679 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:28:06.430 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:28:09.378 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:28:11.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5474
2025-07-30 05:28:11.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4969
2025-07-30 05:28:11.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2870
2025-07-30 05:28:11.833 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4438
2025-07-30 05:28:11.833 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:28:11.833 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:28:11.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.547
2025-07-30 05:28:11.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.497
2025-07-30 05:28:11.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.287
2025-07-30 05:28:11.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.444
2025-07-30 05:28:11.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:28:11.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:28:11.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:28:11.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:28:11.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:28:11.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:28:11.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:28:11.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:28:11.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:28:14.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:28:16.677 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:28:19.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:28:21.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:28:24.268 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:28:26.713 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:28:29.267 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:28:31.726 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:28:34.143 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:28:34.143 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:28:34.144 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-30 05:28:34.144 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:28:34.172 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.96 ms, Average inference time: 2.34 ms

2025-07-30 05:28:34.173 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:28:34.199 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:28:34.229 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch346
2025-07-30 05:28:36.600 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.113s, data_time: 0.028s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.448e-04, size: 288, ETA: 1:10:59
2025-07-30 05:28:39.457 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.007s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 9.423e-04, size: 576, ETA: 1:10:56
2025-07-30 05:28:42.286 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.007s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.398e-04, size: 480, ETA: 1:10:54
2025-07-30 05:28:45.188 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 9.374e-04, size: 288, ETA: 1:10:51
2025-07-30 05:28:48.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.349e-04, size: 256, ETA: 1:10:49
2025-07-30 05:28:50.897 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 346/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.137s, 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: 9.325e-04, size: 480, ETA: 1:10:46
2025-07-30 05:28:52.158 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:28:52.203 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch347
2025-07-30 05:28:54.875 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, 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: 9.290e-04, size: 320, ETA: 1:10:42
2025-07-30 05:28:57.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 9.265e-04, size: 448, ETA: 1:10:40
2025-07-30 05:29:00.605 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.241e-04, size: 544, ETA: 1:10:37
2025-07-30 05:29:03.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.217e-04, size: 288, ETA: 1:10:35
2025-07-30 05:29:06.131 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.3, lr: 9.193e-04, size: 576, ETA: 1:10:32
2025-07-30 05:29:08.871 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 347/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, 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: 9.169e-04, size: 384, ETA: 1:10:30
2025-07-30 05:29:10.217 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:29:10.271 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch348
2025-07-30 05:29:13.112 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.0, lr: 9.134e-04, size: 352, ETA: 1:10:26
2025-07-30 05:29:16.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 9.110e-04, size: 480, ETA: 1:10:24
2025-07-30 05:29:18.727 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.086e-04, size: 576, ETA: 1:10:21
2025-07-30 05:29:21.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.013s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.063e-04, size: 576, ETA: 1:10:19
2025-07-30 05:29:24.272 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.034s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.039e-04, size: 576, ETA: 1:10:16
2025-07-30 05:29:27.115 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 348/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.022s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.015e-04, size: 288, ETA: 1:10:14
2025-07-30 05:29:28.419 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:29:28.457 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch349
2025-07-30 05:29:31.216 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.981e-04, size: 320, ETA: 1:10:10
2025-07-30 05:29:34.095 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.958e-04, size: 512, ETA: 1:10:08
2025-07-30 05:29:36.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.934e-04, size: 256, ETA: 1:10:05
2025-07-30 05:29:39.719 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.142s, data_time: 0.004s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.3, lr: 8.911e-04, size: 576, ETA: 1:10:03
2025-07-30 05:29:42.419 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.888e-04, size: 384, ETA: 1:10:00
2025-07-30 05:29:45.190 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 349/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.865e-04, size: 352, ETA: 1:09:58
2025-07-30 05:29:46.366 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:29:46.520 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch350
2025-07-30 05:29:49.199 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.015s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.831e-04, size: 576, ETA: 1:09:54
2025-07-30 05:29:51.981 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.010s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.808e-04, size: 576, ETA: 1:09:51
2025-07-30 05:29:54.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 8.785e-04, size: 288, ETA: 1:09:49
2025-07-30 05:29:57.634 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 8.762e-04, size: 448, ETA: 1:09:46
2025-07-30 05:30:00.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.7, lr: 8.740e-04, size: 352, ETA: 1:09:44
2025-07-30 05:30:03.278 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 350/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.717e-04, size: 544, ETA: 1:09:41
2025-07-30 05:30:04.413 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:30:10.695 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:30:12.747 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:30:13.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5412
2025-07-30 05:30:14.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4786
2025-07-30 05:30:14.333 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2653
2025-07-30 05:30:14.334 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4284
2025-07-30 05:30:14.334 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:30:14.334 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:30:14.334 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.541
2025-07-30 05:30:14.334 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.479
2025-07-30 05:30:14.334 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.265
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.428
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:30:14.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:30:15.991 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:30:17.609 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:30:19.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:30:20.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:30:22.419 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:30:23.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:30:25.592 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:30:27.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:30:28.761 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:30:28.761 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 05:30:28.761 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-30 05:30:28.761 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:30:28.782 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.93 ms, Average inference time: 2.32 ms

2025-07-30 05:30:28.783 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:30:28.808 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:30:28.884 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch351
2025-07-30 05:30:31.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.118s, data_time: 0.034s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 8.684e-04, size: 384, ETA: 1:09:37
2025-07-30 05:30:34.095 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.040s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.661e-04, size: 480, ETA: 1:09:35
2025-07-30 05:30:37.028 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.142s, 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: 8.639e-04, size: 320, ETA: 1:09:32
2025-07-30 05:30:39.864 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 8.616e-04, size: 416, ETA: 1:09:30
2025-07-30 05:30:42.649 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.005s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.594e-04, size: 384, ETA: 1:09:27
2025-07-30 05:30:45.452 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 351/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.572e-04, size: 576, ETA: 1:09:24
2025-07-30 05:30:46.693 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:30:46.728 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch352
2025-07-30 05:30:49.584 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 5.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.8, lr: 8.539e-04, size: 288, ETA: 1:09:21
2025-07-30 05:30:52.424 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.517e-04, size: 288, ETA: 1:09:18
2025-07-30 05:30:55.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.495e-04, size: 384, ETA: 1:09:16
2025-07-30 05:30:58.247 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.473e-04, size: 512, ETA: 1:09:13
2025-07-30 05:31:01.144 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.451e-04, size: 288, ETA: 1:09:11
2025-07-30 05:31:03.859 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 352/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.429e-04, size: 384, ETA: 1:09:08
2025-07-30 05:31:05.028 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:31:05.062 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch353
2025-07-30 05:31:07.801 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.008s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 8.398e-04, size: 416, ETA: 1:09:04
2025-07-30 05:31:10.591 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 8.376e-04, size: 256, ETA: 1:09:02
2025-07-30 05:31:13.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 8.354e-04, size: 448, ETA: 1:08:59
2025-07-30 05:31:16.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.5, lr: 8.333e-04, size: 416, ETA: 1:08:57
2025-07-30 05:31:19.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.3, lr: 8.311e-04, size: 256, ETA: 1:08:54
2025-07-30 05:31:21.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 353/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.005s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.290e-04, size: 352, ETA: 1:08:52
2025-07-30 05:31:23.191 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:31:23.250 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch354
2025-07-30 05:31:26.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.259e-04, size: 544, ETA: 1:08:48
2025-07-30 05:31:28.887 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 8.238e-04, size: 384, ETA: 1:08:45
2025-07-30 05:31:31.642 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.123s, 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: 8.216e-04, size: 256, ETA: 1:08:43
2025-07-30 05:31:34.429 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 8.195e-04, size: 480, ETA: 1:08:40
2025-07-30 05:31:37.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.174e-04, size: 512, ETA: 1:08:37
2025-07-30 05:31:40.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 354/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.153e-04, size: 544, ETA: 1:08:35
2025-07-30 05:31:41.321 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:31:41.451 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch355
2025-07-30 05:31:44.276 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.123e-04, size: 544, ETA: 1:08:31
2025-07-30 05:31:47.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.102e-04, size: 544, ETA: 1:08:28
2025-07-30 05:31:50.045 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.081e-04, size: 480, ETA: 1:08:26
2025-07-30 05:31:52.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 8.060e-04, size: 288, ETA: 1:08:23
2025-07-30 05:31:55.610 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.7, lr: 8.040e-04, size: 544, ETA: 1:08:20
2025-07-30 05:31:58.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 355/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 8.019e-04, size: 576, ETA: 1:08:18
2025-07-30 05:31:59.541 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:32:06.053 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:32:08.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:32:09.809 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5657
2025-07-30 05:32:10.156 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5017
2025-07-30 05:32:10.309 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3113
2025-07-30 05:32:10.310 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4596
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.566
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.502
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.311
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.460
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:32:10.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:32:10.312 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:32:10.312 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:32:10.312 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:32:10.312 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:32:10.312 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:32:12.264 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:32:14.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:32:15.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:32:17.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:32:19.680 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:32:21.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:32:23.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:32:25.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:32:27.254 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:32:27.255 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:32:27.255 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-30 05:32:27.255 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:32:27.281 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.96 ms, Average inference time: 2.34 ms

2025-07-30 05:32:27.290 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:32:27.311 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:32:27.341 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch356
2025-07-30 05:32:29.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.120s, 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: 7.989e-04, size: 352, ETA: 1:08:14
2025-07-30 05:32:32.647 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.969e-04, size: 384, ETA: 1:08:11
2025-07-30 05:32:35.492 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 9.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 0.9, lr: 7.949e-04, size: 544, ETA: 1:08:09
2025-07-30 05:32:38.277 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 7.928e-04, size: 352, ETA: 1:08:06
2025-07-30 05:32:41.082 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.124s, 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: 7.908e-04, size: 384, ETA: 1:08:03
2025-07-30 05:32:43.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 356/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.888e-04, size: 480, ETA: 1:08:01
2025-07-30 05:32:45.096 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:32:45.204 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch357
2025-07-30 05:32:47.907 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.119s, 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: 7.859e-04, size: 352, ETA: 1:07:57
2025-07-30 05:32:50.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.839e-04, size: 576, ETA: 1:07:54
2025-07-30 05:32:53.583 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.819e-04, size: 352, ETA: 1:07:52
2025-07-30 05:32:56.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.116s, data_time: 0.005s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.799e-04, size: 480, ETA: 1:07:49
2025-07-30 05:32:59.104 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.124s, 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: 7.779e-04, size: 288, ETA: 1:07:46
2025-07-30 05:33:01.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 357/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 7.760e-04, size: 544, ETA: 1:07:43
2025-07-30 05:33:03.105 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:33:03.136 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch358
2025-07-30 05:33:05.940 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.731e-04, size: 288, ETA: 1:07:40
2025-07-30 05:33:08.855 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 7.712e-04, size: 384, ETA: 1:07:37
2025-07-30 05:33:11.638 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 7.692e-04, size: 544, ETA: 1:07:34
2025-07-30 05:33:14.478 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.128s, 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: 7.673e-04, size: 352, ETA: 1:07:32
2025-07-30 05:33:17.418 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 0.7, lr: 7.653e-04, size: 576, ETA: 1:07:29
2025-07-30 05:33:20.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 358/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 7.634e-04, size: 448, ETA: 1:07:27
2025-07-30 05:33:21.516 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:33:21.605 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch359
2025-07-30 05:33:24.306 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.123s, data_time: 0.010s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 7.606e-04, size: 448, ETA: 1:07:23
2025-07-30 05:33:27.141 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 7.587e-04, size: 384, ETA: 1:07:20
2025-07-30 05:33:30.012 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.568e-04, size: 512, ETA: 1:07:18
2025-07-30 05:33:32.916 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 7.549e-04, size: 544, ETA: 1:07:15
2025-07-30 05:33:35.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.530e-04, size: 384, ETA: 1:07:12
2025-07-30 05:33:38.624 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 359/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.123s, 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: 7.512e-04, size: 576, ETA: 1:07:10
2025-07-30 05:33:39.837 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:33:39.881 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch360
2025-07-30 05:33:42.658 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 7.484e-04, size: 512, ETA: 1:07:06
2025-07-30 05:33:45.533 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.466e-04, size: 512, ETA: 1:07:03
2025-07-30 05:33:48.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.3, lr: 7.447e-04, size: 576, ETA: 1:07:01
2025-07-30 05:33:51.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.129s, data_time: 0.016s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 7.429e-04, size: 352, ETA: 1:06:58
2025-07-30 05:33:53.813 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, data_time: 0.051s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.410e-04, size: 352, ETA: 1:06:56
2025-07-30 05:33:56.657 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 360/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.132s, data_time: 0.048s, total_loss: 7.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 0.9, lr: 7.392e-04, size: 448, ETA: 1:06:53
2025-07-30 05:33:57.955 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:34:04.326 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:34:06.842 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:34:08.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5547
2025-07-30 05:34:08.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4850
2025-07-30 05:34:08.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3086
2025-07-30 05:34:08.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4494
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.555
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.485
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.309
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.449
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:34:08.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:34:08.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:34:08.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:34:08.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:34:08.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:34:08.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:34:10.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:34:12.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:34:14.996 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:34:17.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:34:19.091 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:34:21.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:34:23.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:34:25.177 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:34:27.219 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:34:27.219 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:34:27.219 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 05:34:27.219 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:34:27.244 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.96 ms, Average inference time: 2.32 ms

2025-07-30 05:34:27.245 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:34:27.272 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:34:27.301 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch361
2025-07-30 05:34:29.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.122s, data_time: 0.032s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 7.365e-04, size: 320, ETA: 1:06:49
2025-07-30 05:34:32.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.141s, data_time: 0.005s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.347e-04, size: 576, ETA: 1:06:47
2025-07-30 05:34:35.414 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, 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: 7.329e-04, size: 480, ETA: 1:06:44
2025-07-30 05:34:38.230 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 7.311e-04, size: 576, ETA: 1:06:42
2025-07-30 05:34:41.078 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.293e-04, size: 384, ETA: 1:06:40
2025-07-30 05:34:44.017 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 361/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.275e-04, size: 256, ETA: 1:06:37
2025-07-30 05:34:45.217 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:34:45.281 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch362
2025-07-30 05:34:48.214 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.249e-04, size: 480, ETA: 1:06:34
2025-07-30 05:34:51.111 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.231e-04, size: 576, ETA: 1:06:31
2025-07-30 05:34:53.986 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.213e-04, size: 384, ETA: 1:06:29
2025-07-30 05:34:56.738 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.196e-04, size: 416, ETA: 1:06:26
2025-07-30 05:34:59.458 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.178e-04, size: 448, ETA: 1:06:23
2025-07-30 05:35:02.345 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 362/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.161e-04, size: 576, ETA: 1:06:21
2025-07-30 05:35:03.508 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:35:03.618 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch363
2025-07-30 05:35:06.483 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 7.136e-04, size: 544, ETA: 1:06:17
2025-07-30 05:35:09.262 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.121s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.118e-04, size: 448, ETA: 1:06:14
2025-07-30 05:35:12.027 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.101e-04, size: 544, ETA: 1:06:12
2025-07-30 05:35:14.836 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 7.084e-04, size: 384, ETA: 1:06:09
2025-07-30 05:35:17.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.067e-04, size: 416, ETA: 1:06:07
2025-07-30 05:35:20.678 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 363/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 7.050e-04, size: 384, ETA: 1:06:04
2025-07-30 05:35:21.966 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:35:22.000 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch364
2025-07-30 05:35:24.852 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.4, lr: 7.025e-04, size: 384, ETA: 1:06:00
2025-07-30 05:35:27.600 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.124s, data_time: 0.009s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 7.008e-04, size: 320, ETA: 1:05:58
2025-07-30 05:35:30.313 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.021s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.991e-04, size: 256, ETA: 1:05:55
2025-07-30 05:35:33.147 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 6.975e-04, size: 544, ETA: 1:05:53
2025-07-30 05:35:35.950 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.958e-04, size: 480, ETA: 1:05:50
2025-07-30 05:35:38.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 364/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 6.941e-04, size: 288, ETA: 1:05:47
2025-07-30 05:35:39.981 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:35:40.104 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch365
2025-07-30 05:35:42.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 6.917e-04, size: 480, ETA: 1:05:43
2025-07-30 05:35:45.679 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.901e-04, size: 512, ETA: 1:05:41
2025-07-30 05:35:48.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.884e-04, size: 576, ETA: 1:05:38
2025-07-30 05:35:51.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.868e-04, size: 512, ETA: 1:05:35
2025-07-30 05:35:53.892 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 6.852e-04, size: 512, ETA: 1:05:33
2025-07-30 05:35:56.659 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 365/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.117s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 6.836e-04, size: 416, ETA: 1:05:30
2025-07-30 05:35:57.839 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:36:04.390 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:36:06.793 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:36:08.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5609
2025-07-30 05:36:08.718 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5003
2025-07-30 05:36:08.780 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3042
2025-07-30 05:36:08.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4551
2025-07-30 05:36:08.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:36:08.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:36:08.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.561
2025-07-30 05:36:08.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.500
2025-07-30 05:36:08.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.304
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.455
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:36:08.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:36:10.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:36:12.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:36:14.620 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:36:16.539 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:36:18.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:36:20.371 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:36:22.288 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:36:24.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:36:26.122 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:36:26.123 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:36:26.123 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-30 05:36:26.123 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:36:26.150 | 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: 2.32 ms

2025-07-30 05:36:26.151 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:36:26.224 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:36:26.255 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch366
2025-07-30 05:36:28.728 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.121s, data_time: 0.042s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.812e-04, size: 416, ETA: 1:05:26
2025-07-30 05:36:31.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.033s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 6.796e-04, size: 320, ETA: 1:05:23
2025-07-30 05:36:34.310 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.781e-04, size: 448, ETA: 1:05:21
2025-07-30 05:36:37.080 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 6.765e-04, size: 512, ETA: 1:05:18
2025-07-30 05:36:39.869 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, 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: 6.749e-04, size: 288, ETA: 1:05:16
2025-07-30 05:36:42.615 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 366/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.006s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.733e-04, size: 320, ETA: 1:05:13
2025-07-30 05:36:43.756 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:36:43.876 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch367
2025-07-30 05:36:46.617 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.121s, data_time: 0.009s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.711e-04, size: 448, ETA: 1:05:09
2025-07-30 05:36:49.386 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.695e-04, size: 416, ETA: 1:05:06
2025-07-30 05:36:52.286 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.143s, data_time: 0.011s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.680e-04, size: 512, ETA: 1:05:04
2025-07-30 05:36:55.068 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.136s, 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: 6.664e-04, size: 448, ETA: 1:05:01
2025-07-30 05:36:57.808 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.649e-04, size: 416, ETA: 1:04:59
2025-07-30 05:37:00.652 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 367/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.140s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.634e-04, size: 352, ETA: 1:04:56
2025-07-30 05:37:01.835 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:37:01.995 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch368
2025-07-30 05:37:04.766 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.612e-04, size: 320, ETA: 1:04:53
2025-07-30 05:37:07.570 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 6.596e-04, size: 352, ETA: 1:04:50
2025-07-30 05:37:10.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.023s, total_loss: 5.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 6.581e-04, size: 320, ETA: 1:04:48
2025-07-30 05:37:13.184 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.132s, data_time: 0.048s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 6.566e-04, size: 416, ETA: 1:04:45
2025-07-30 05:37:15.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.127s, 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: 6.552e-04, size: 480, ETA: 1:04:42
2025-07-30 05:37:18.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 368/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.6Gb, iter_time: 0.134s, data_time: 0.020s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.537e-04, size: 480, ETA: 1:04:40
2025-07-30 05:37:19.878 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:37:19.927 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch369
2025-07-30 05:37:22.725 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 6.515e-04, size: 576, ETA: 1:04:36
2025-07-30 05:37:25.445 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.501e-04, size: 512, ETA: 1:04:34
2025-07-30 05:37:28.204 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 6.486e-04, size: 384, ETA: 1:04:31
2025-07-30 05:37:30.984 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.472e-04, size: 544, ETA: 1:04:29
2025-07-30 05:37:33.797 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.457e-04, size: 448, ETA: 1:04:26
2025-07-30 05:37:36.658 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 369/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 6.443e-04, size: 544, ETA: 1:04:24
2025-07-30 05:37:37.851 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:37:37.981 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch370
2025-07-30 05:37:40.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.422e-04, size: 256, ETA: 1:04:20
2025-07-30 05:37:43.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 6.408e-04, size: 512, ETA: 1:04:17
2025-07-30 05:37:46.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.126s, 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: 6.394e-04, size: 416, ETA: 1:04:15
2025-07-30 05:37:49.141 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.380e-04, size: 480, ETA: 1:04:12
2025-07-30 05:37:51.988 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.010s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.366e-04, size: 512, ETA: 1:04:09
2025-07-30 05:37:54.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 370/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 6.352e-04, size: 416, ETA: 1:04:07
2025-07-30 05:37:56.052 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:38:02.203 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:38:04.286 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:38:05.472 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5520
2025-07-30 05:38:05.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5101
2025-07-30 05:38:05.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3023
2025-07-30 05:38:05.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4548
2025-07-30 05:38:05.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:38:05.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:38:05.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.552
2025-07-30 05:38:05.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.510
2025-07-30 05:38:05.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.302
2025-07-30 05:38:05.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.455
2025-07-30 05:38:05.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:38:05.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:38:05.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:38:05.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:38:05.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:38:05.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:38:05.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:38:05.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:38:05.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:38:07.578 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:38:09.237 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:38:10.893 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:38:12.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:38:14.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:38:15.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:38:17.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:38:19.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:38:20.845 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:38:20.846 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:38:20.846 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 05:38:20.846 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:38:20.872 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.34 ms, Average NMS time: 0.94 ms, Average inference time: 2.28 ms

2025-07-30 05:38:20.873 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:38:20.904 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:38:20.933 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch371
2025-07-30 05:38:23.366 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.116s, data_time: 0.014s, total_loss: 8.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 6.332e-04, size: 544, ETA: 1:04:03
2025-07-30 05:38:26.253 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.006s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 6.318e-04, size: 288, ETA: 1:04:00
2025-07-30 05:38:29.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.304e-04, size: 320, ETA: 1:03:58
2025-07-30 05:38:31.844 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, 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: 0.8, lr: 6.291e-04, size: 448, ETA: 1:03:55
2025-07-30 05:38:34.733 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.277e-04, size: 416, ETA: 1:03:53
2025-07-30 05:38:37.545 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 371/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.264e-04, size: 384, ETA: 1:03:50
2025-07-30 05:38:38.671 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:38:38.811 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch372
2025-07-30 05:38:41.505 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.245e-04, size: 320, ETA: 1:03:46
2025-07-30 05:38:44.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 6.231e-04, size: 448, ETA: 1:03:44
2025-07-30 05:38:47.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 6.218e-04, size: 320, ETA: 1:03:41
2025-07-30 05:38:50.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 6.205e-04, size: 576, ETA: 1:03:39
2025-07-30 05:38:52.948 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.192e-04, size: 416, ETA: 1:03:36
2025-07-30 05:38:55.662 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 372/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.018s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.179e-04, size: 352, ETA: 1:03:34
2025-07-30 05:38:56.863 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:38:56.921 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch373
2025-07-30 05:38:59.811 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 6.160e-04, size: 448, ETA: 1:03:30
2025-07-30 05:39:02.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.147e-04, size: 288, ETA: 1:03:28
2025-07-30 05:39:05.332 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.134e-04, size: 320, ETA: 1:03:25
2025-07-30 05:39:08.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.122e-04, size: 352, ETA: 1:03:23
2025-07-30 05:39:10.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 6.109e-04, size: 352, ETA: 1:03:20
2025-07-30 05:39:13.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 373/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 6.097e-04, size: 384, ETA: 1:03:17
2025-07-30 05:39:14.915 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:39:15.002 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch374
2025-07-30 05:39:17.893 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.132s, 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: 6.079e-04, size: 384, ETA: 1:03:14
2025-07-30 05:39:20.692 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 6.066e-04, size: 320, ETA: 1:03:11
2025-07-30 05:39:23.476 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 6.054e-04, size: 352, ETA: 1:03:08
2025-07-30 05:39:26.343 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 6.042e-04, size: 480, ETA: 1:03:06
2025-07-30 05:39:29.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 8.0, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 6.029e-04, size: 256, ETA: 1:03:03
2025-07-30 05:39:32.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 374/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.017e-04, size: 512, ETA: 1:03:01
2025-07-30 05:39:33.115 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:39:33.287 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch375
2025-07-30 05:39:36.065 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.120s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 6.000e-04, size: 512, ETA: 1:02:57
2025-07-30 05:39:38.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 5.988e-04, size: 448, ETA: 1:02:54
2025-07-30 05:39:41.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.976e-04, size: 256, ETA: 1:02:52
2025-07-30 05:39:44.308 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 5.964e-04, size: 480, ETA: 1:02:49
2025-07-30 05:39:47.052 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 5.953e-04, size: 352, ETA: 1:02:47
2025-07-30 05:39:49.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 375/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 5.941e-04, size: 416, ETA: 1:02:44
2025-07-30 05:39:51.033 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:39:57.492 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:39:59.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:40:00.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5602
2025-07-30 05:40:01.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4983
2025-07-30 05:40:01.277 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3085
2025-07-30 05:40:01.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4557
2025-07-30 05:40:01.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:40:01.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.560
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.498
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.309
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.456
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:40:01.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:40:01.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:40:01.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:40:01.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:40:02.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:40:04.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:40:06.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:40:07.884 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:40:09.517 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:40:11.211 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:40:12.895 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:40:14.505 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:40:16.188 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:40:16.188 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 05:40:16.188 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-30 05:40:16.188 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:40:16.213 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.97 ms, Average inference time: 2.37 ms

2025-07-30 05:40:16.214 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:40:16.234 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:40:16.263 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch376
2025-07-30 05:40:18.732 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.116s, data_time: 0.037s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.924e-04, size: 320, ETA: 1:02:40
2025-07-30 05:40:21.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.124s, data_time: 0.011s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 5.913e-04, size: 480, ETA: 1:02:37
2025-07-30 05:40:24.267 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.901e-04, size: 512, ETA: 1:02:35
2025-07-30 05:40:27.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 5.890e-04, size: 544, ETA: 1:02:32
2025-07-30 05:40:29.914 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.879e-04, size: 544, ETA: 1:02:30
2025-07-30 05:40:32.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 376/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.868e-04, size: 448, ETA: 1:02:27
2025-07-30 05:40:33.849 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:40:34.036 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch377
2025-07-30 05:40:36.913 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.852e-04, size: 448, ETA: 1:02:23
2025-07-30 05:40:39.640 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.122s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 5.841e-04, size: 544, ETA: 1:02:21
2025-07-30 05:40:42.383 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.120s, data_time: 0.005s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 5.830e-04, size: 320, ETA: 1:02:18
2025-07-30 05:40:45.366 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 5.819e-04, size: 448, ETA: 1:02:15
2025-07-30 05:40:48.133 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.808e-04, size: 256, ETA: 1:02:13
2025-07-30 05:40:50.915 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 377/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 5.797e-04, size: 448, ETA: 1:02:10
2025-07-30 05:40:52.114 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:40:52.156 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch378
2025-07-30 05:40:54.876 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.782e-04, size: 320, ETA: 1:02:06
2025-07-30 05:40:57.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.126s, data_time: 0.005s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.771e-04, size: 512, ETA: 1:02:03
2025-07-30 05:41:00.631 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.761e-04, size: 512, ETA: 1:02:01
2025-07-30 05:41:03.299 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.121s, data_time: 0.006s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 5.750e-04, size: 288, ETA: 1:01:58
2025-07-30 05:41:06.088 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.740e-04, size: 544, ETA: 1:01:55
2025-07-30 05:41:08.960 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 378/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.730e-04, size: 576, ETA: 1:01:53
2025-07-30 05:41:10.168 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:41:10.205 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch379
2025-07-30 05:41:12.946 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.715e-04, size: 448, ETA: 1:01:49
2025-07-30 05:41:15.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.705e-04, size: 512, ETA: 1:01:47
2025-07-30 05:41:18.613 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.146s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.695e-04, size: 352, ETA: 1:01:44
2025-07-30 05:41:21.509 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.685e-04, size: 448, ETA: 1:01:42
2025-07-30 05:41:24.252 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.005s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.675e-04, size: 576, ETA: 1:01:39
2025-07-30 05:41:27.220 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 379/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.1, lr: 5.665e-04, size: 544, ETA: 1:01:37
2025-07-30 05:41:28.423 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:41:28.456 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch380
2025-07-30 05:41:31.246 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.651e-04, size: 320, ETA: 1:01:33
2025-07-30 05:41:33.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.642e-04, size: 352, ETA: 1:01:30
2025-07-30 05:41:36.935 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.130s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.632e-04, size: 320, ETA: 1:01:28
2025-07-30 05:41:39.682 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 5.623e-04, size: 480, ETA: 1:01:25
2025-07-30 05:41:42.472 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, 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: 5.613e-04, size: 576, ETA: 1:01:22
2025-07-30 05:41:45.173 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 380/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.604e-04, size: 480, ETA: 1:01:20
2025-07-30 05:41:46.599 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:41:52.918 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:41:55.221 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:41:56.702 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5476
2025-07-30 05:41:57.044 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4936
2025-07-30 05:41:57.119 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2999
2025-07-30 05:41:57.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4470
2025-07-30 05:41:57.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:41:57.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:41:57.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.548
2025-07-30 05:41:57.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.494
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.300
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.447
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:41:57.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:41:58.988 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:42:00.858 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:42:02.725 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:42:04.607 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:42:06.503 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:42:08.363 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:42:10.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:42:12.101 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:42:13.928 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:42:13.928 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:42:13.928 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 05:42:13.928 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:42:13.956 | 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

2025-07-30 05:42:13.957 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:42:13.981 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:42:14.009 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch381
2025-07-30 05:42:16.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.123s, data_time: 0.025s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.590e-04, size: 384, ETA: 1:01:16
2025-07-30 05:42:19.403 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.581e-04, size: 256, ETA: 1:01:13
2025-07-30 05:42:22.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.572e-04, size: 288, ETA: 1:01:11
2025-07-30 05:42:25.042 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.3, lr: 5.563e-04, size: 416, ETA: 1:01:08
2025-07-30 05:42:27.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 5.554e-04, size: 384, ETA: 1:01:06
2025-07-30 05:42:30.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 381/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.147s, 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: 5.545e-04, size: 352, ETA: 1:01:03
2025-07-30 05:42:32.034 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:42:32.138 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch382
2025-07-30 05:42:34.902 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 8.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.2, lr: 5.533e-04, size: 480, ETA: 1:01:00
2025-07-30 05:42:37.718 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 40/129, gpu mem: 1553Mb, 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: 2.7, cls_loss: 0.9, lr: 5.524e-04, size: 256, ETA: 1:00:57
2025-07-30 05:42:40.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.515e-04, size: 320, ETA: 1:00:55
2025-07-30 05:42:43.388 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 5.507e-04, size: 288, ETA: 1:00:52
2025-07-30 05:42:46.131 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.127s, 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: 5.498e-04, size: 352, ETA: 1:00:49
2025-07-30 05:42:49.003 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 382/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.490e-04, size: 352, ETA: 1:00:47
2025-07-30 05:42:50.185 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:42:50.321 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch383
2025-07-30 05:42:53.109 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.122s, 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: 5.478e-04, size: 288, ETA: 1:00:43
2025-07-30 05:42:55.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.469e-04, size: 288, ETA: 1:00:40
2025-07-30 05:42:58.844 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 5.461e-04, size: 288, ETA: 1:00:38
2025-07-30 05:43:01.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.122s, 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: 5.453e-04, size: 256, ETA: 1:00:35
2025-07-30 05:43:04.462 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.122s, 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: 5.445e-04, size: 448, ETA: 1:00:32
2025-07-30 05:43:07.345 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 383/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.123s, 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: 5.437e-04, size: 576, ETA: 1:00:30
2025-07-30 05:43:08.610 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:43:08.646 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch384
2025-07-30 05:43:11.346 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.6, lr: 5.426e-04, size: 576, ETA: 1:00:26
2025-07-30 05:43:14.157 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.418e-04, size: 288, ETA: 1:00:23
2025-07-30 05:43:16.895 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, 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: 5.410e-04, size: 512, ETA: 1:00:20
2025-07-30 05:43:19.906 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 5.403e-04, size: 480, ETA: 1:00:18
2025-07-30 05:43:22.738 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.395e-04, size: 448, ETA: 1:00:15
2025-07-30 05:43:25.584 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 384/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.387e-04, size: 576, ETA: 1:00:13
2025-07-30 05:43:26.780 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:43:26.883 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch385
2025-07-30 05:43:29.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.127s, 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: 5.377e-04, size: 384, ETA: 1:00:09
2025-07-30 05:43:32.599 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.369e-04, size: 256, ETA: 1:00:06
2025-07-30 05:43:35.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.362e-04, size: 416, ETA: 1:00:03
2025-07-30 05:43:38.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.355e-04, size: 352, ETA: 1:00:01
2025-07-30 05:43:41.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.4, lr: 5.348e-04, size: 256, ETA: 0:59:58
2025-07-30 05:43:43.978 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 385/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, 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: 5.341e-04, size: 448, ETA: 0:59:56
2025-07-30 05:43:45.037 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:43:51.572 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:43:53.580 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:43:54.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5556
2025-07-30 05:43:55.112 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4848
2025-07-30 05:43:55.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3044
2025-07-30 05:43:55.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4483
2025-07-30 05:43:55.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:43:55.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:43:55.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.556
2025-07-30 05:43:55.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.485
2025-07-30 05:43:55.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.304
2025-07-30 05:43:55.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.448
2025-07-30 05:43:55.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:43:55.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:43:55.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:43:55.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:43:55.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:43:55.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:43:55.177 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:43:55.177 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:43:55.177 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:43:56.845 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:43:58.474 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:44:00.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:44:01.671 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:44:03.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:44:04.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:44:06.577 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:44:08.243 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:44:09.812 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:44:09.812 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 05:44:09.812 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 05:44:09.812 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:44:09.837 | 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

2025-07-30 05:44:09.838 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:44:09.870 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:44:09.900 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch386
2025-07-30 05:44:12.300 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.117s, data_time: 0.037s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.331e-04, size: 320, ETA: 0:59:51
2025-07-30 05:44:15.130 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.040s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.324e-04, size: 256, ETA: 0:59:49
2025-07-30 05:44:17.955 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.016s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.317e-04, size: 448, ETA: 0:59:46
2025-07-30 05:44:20.841 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.310e-04, size: 512, ETA: 0:59:44
2025-07-30 05:44:23.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 5.304e-04, size: 352, ETA: 0:59:41
2025-07-30 05:44:26.389 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 386/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.123s, 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: 5.297e-04, size: 448, ETA: 0:59:38
2025-07-30 05:44:27.689 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:44:27.799 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch387
2025-07-30 05:44:30.517 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.288e-04, size: 480, ETA: 0:59:35
2025-07-30 05:44:33.219 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.129s, data_time: 0.010s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.281e-04, size: 352, ETA: 0:59:32
2025-07-30 05:44:36.126 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.275e-04, size: 256, ETA: 0:59:29
2025-07-30 05:44:38.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.7, lr: 5.269e-04, size: 352, ETA: 0:59:27
2025-07-30 05:44:41.634 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, 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: 5.263e-04, size: 512, ETA: 0:59:24
2025-07-30 05:44:44.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 387/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.3, lr: 5.256e-04, size: 256, ETA: 0:59:22
2025-07-30 05:44:45.599 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:44:45.780 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch388
2025-07-30 05:44:48.582 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.248e-04, size: 288, ETA: 0:59:18
2025-07-30 05:44:51.349 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.126s, data_time: 0.007s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 5.242e-04, size: 416, ETA: 0:59:16
2025-07-30 05:44:54.144 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 5.236e-04, size: 352, ETA: 0:59:13
2025-07-30 05:44:56.953 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.127s, 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: 5.230e-04, size: 480, ETA: 0:59:10
2025-07-30 05:44:59.710 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.224e-04, size: 416, ETA: 0:59:08
2025-07-30 05:45:02.537 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 388/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.219e-04, size: 256, ETA: 0:59:05
2025-07-30 05:45:03.656 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:45:03.708 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch389
2025-07-30 05:45:06.448 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.117s, data_time: 0.001s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.211e-04, size: 256, ETA: 0:59:01
2025-07-30 05:45:09.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.205e-04, size: 288, ETA: 0:58:59
2025-07-30 05:45:12.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.200e-04, size: 448, ETA: 0:58:56
2025-07-30 05:45:14.865 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.194e-04, size: 480, ETA: 0:58:53
2025-07-30 05:45:17.661 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.189e-04, size: 352, ETA: 0:58:51
2025-07-30 05:45:20.387 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 389/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.184e-04, size: 512, ETA: 0:58:48
2025-07-30 05:45:21.649 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:45:21.745 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch390
2025-07-30 05:45:24.591 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 5.177e-04, size: 576, ETA: 0:58:44
2025-07-30 05:45:27.408 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.135s, 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: 5.172e-04, size: 512, ETA: 0:58:42
2025-07-30 05:45:30.134 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.167e-04, size: 448, ETA: 0:58:39
2025-07-30 05:45:32.983 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 5.162e-04, size: 544, ETA: 0:58:37
2025-07-30 05:45:35.808 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.126s, 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: 5.157e-04, size: 352, ETA: 0:58:34
2025-07-30 05:45:38.546 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 390/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 5.152e-04, size: 480, ETA: 0:58:31
2025-07-30 05:45:39.788 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:45:46.178 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:45:48.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:45:50.148 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5473
2025-07-30 05:45:50.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4988
2025-07-30 05:45:50.648 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3067
2025-07-30 05:45:50.649 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4509
2025-07-30 05:45:50.649 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.547
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.499
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.307
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.451
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:45:50.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:45:50.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:45:50.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:45:52.598 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:45:54.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:45:56.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:45:58.516 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:46:00.463 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:46:02.423 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:46:04.389 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:46:06.316 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:46:08.271 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:46:08.272 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:46:08.272 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 05:46:08.272 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:46:08.297 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.32 ms, Average NMS time: 0.95 ms, Average inference time: 2.27 ms

2025-07-30 05:46:08.298 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:46:08.318 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:46:08.347 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch391
2025-07-30 05:46:10.843 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.123s, data_time: 0.020s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.9, lr: 5.146e-04, size: 480, ETA: 0:58:28
2025-07-30 05:46:13.652 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.138s, data_time: 0.007s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.141e-04, size: 512, ETA: 0:58:25
2025-07-30 05:46:16.426 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.132s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.137e-04, size: 576, ETA: 0:58:23
2025-07-30 05:46:19.272 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.132e-04, size: 448, ETA: 0:58:20
2025-07-30 05:46:22.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.128e-04, size: 480, ETA: 0:58:17
2025-07-30 05:46:25.026 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 391/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 5.124e-04, size: 352, ETA: 0:58:15
2025-07-30 05:46:26.239 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:46:26.275 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch392
2025-07-30 05:46:29.034 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.117e-04, size: 512, ETA: 0:58:11
2025-07-30 05:46:31.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.113e-04, size: 320, ETA: 0:58:08
2025-07-30 05:46:34.582 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.109e-04, size: 288, ETA: 0:58:06
2025-07-30 05:46:37.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 5.105e-04, size: 384, ETA: 0:58:03
2025-07-30 05:46:40.136 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.102e-04, size: 288, ETA: 0:58:01
2025-07-30 05:46:43.030 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 392/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 5.098e-04, size: 448, ETA: 0:57:58
2025-07-30 05:46:44.206 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:46:44.290 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch393
2025-07-30 05:46:47.147 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.092e-04, size: 544, ETA: 0:57:54
2025-07-30 05:46:49.970 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.089e-04, size: 416, ETA: 0:57:52
2025-07-30 05:46:52.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.085e-04, size: 320, ETA: 0:57:49
2025-07-30 05:46:55.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 5.082e-04, size: 288, ETA: 0:57:46
2025-07-30 05:46:58.473 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.119s, 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: 5.078e-04, size: 512, ETA: 0:57:44
2025-07-30 05:47:01.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 393/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.075e-04, size: 576, ETA: 0:57:41
2025-07-30 05:47:02.335 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:47:02.398 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch394
2025-07-30 05:47:05.192 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.070e-04, size: 384, ETA: 0:57:37
2025-07-30 05:47:08.001 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.067e-04, size: 544, ETA: 0:57:35
2025-07-30 05:47:10.781 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.064e-04, size: 384, ETA: 0:57:32
2025-07-30 05:47:13.546 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.061e-04, size: 320, ETA: 0:57:29
2025-07-30 05:47:16.341 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.058e-04, size: 576, ETA: 0:57:27
2025-07-30 05:47:19.146 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 394/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 5.055e-04, size: 256, ETA: 0:57:24
2025-07-30 05:47:20.369 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:47:20.518 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch395
2025-07-30 05:47:23.195 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.116s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.051e-04, size: 352, ETA: 0:57:20
2025-07-30 05:47:26.004 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.128s, 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: 5.049e-04, size: 480, ETA: 0:57:18
2025-07-30 05:47:28.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.046e-04, size: 416, ETA: 0:57:15
2025-07-30 05:47:31.594 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.121s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 5.043e-04, size: 544, ETA: 0:57:12
2025-07-30 05:47:34.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.041e-04, size: 576, ETA: 0:57:10
2025-07-30 05:47:37.204 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 395/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.139s, 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: 5.039e-04, size: 352, ETA: 0:57:07
2025-07-30 05:47:38.434 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:47:44.803 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:47:46.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:47:48.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5522
2025-07-30 05:47:48.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5043
2025-07-30 05:47:48.634 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3037
2025-07-30 05:47:48.635 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4534
2025-07-30 05:47:48.635 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:47:48.635 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:47:48.635 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.552
2025-07-30 05:47:48.635 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.504
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.304
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.453
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:47:48.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:47:48.637 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:47:50.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:47:52.012 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:47:53.734 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:47:55.622 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:47:57.333 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:47:59.066 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:48:00.759 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:48:02.471 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:48:04.145 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:48:04.145 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 05:48:04.145 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 05:48:04.146 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:48:04.171 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.97 ms, Average inference time: 2.33 ms

2025-07-30 05:48:04.172 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:48:04.203 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:48:04.233 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch396
2025-07-30 05:48:06.682 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.116s, data_time: 0.025s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.035e-04, size: 352, ETA: 0:57:04
2025-07-30 05:48:09.434 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.131s, data_time: 0.006s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.033e-04, size: 480, ETA: 0:57:01
2025-07-30 05:48:12.182 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.031e-04, size: 320, ETA: 0:56:58
2025-07-30 05:48:15.010 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.7, lr: 5.029e-04, size: 576, ETA: 0:56:56
2025-07-30 05:48:17.903 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.130s, 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: 5.027e-04, size: 320, ETA: 0:56:53
2025-07-30 05:48:20.654 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 396/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.124s, 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: 5.025e-04, size: 352, ETA: 0:56:50
2025-07-30 05:48:21.867 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:48:21.959 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch397
2025-07-30 05:48:24.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.022e-04, size: 288, ETA: 0:56:47
2025-07-30 05:48:27.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.126s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.020e-04, size: 288, ETA: 0:56:44
2025-07-30 05:48:30.479 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.118s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.019e-04, size: 384, ETA: 0:56:41
2025-07-30 05:48:33.346 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.122s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.017e-04, size: 544, ETA: 0:56:39
2025-07-30 05:48:36.184 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.016e-04, size: 576, ETA: 0:56:36
2025-07-30 05:48:39.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 397/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.014e-04, size: 576, ETA: 0:56:33
2025-07-30 05:48:40.184 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:48:40.211 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch398
2025-07-30 05:48:43.075 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.012e-04, size: 480, ETA: 0:56:30
2025-07-30 05:48:45.875 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.011e-04, size: 352, ETA: 0:56:27
2025-07-30 05:48:48.698 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.010e-04, size: 480, ETA: 0:56:25
2025-07-30 05:48:51.483 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.133s, 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: 5.009e-04, size: 480, ETA: 0:56:22
2025-07-30 05:48:54.345 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.007e-04, size: 288, ETA: 0:56:19
2025-07-30 05:48:57.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 398/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.006e-04, size: 288, ETA: 0:56:17
2025-07-30 05:48:58.287 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:48:58.343 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch399
2025-07-30 05:49:01.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 7.7, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 5.005e-04, size: 256, ETA: 0:56:13
2025-07-30 05:49:03.951 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.140s, data_time: 0.010s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.004e-04, size: 544, ETA: 0:56:11
2025-07-30 05:49:06.867 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.143s, 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: 5.004e-04, size: 416, ETA: 0:56:08
2025-07-30 05:49:09.598 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.003e-04, size: 384, ETA: 0:56:06
2025-07-30 05:49:12.377 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.002e-04, size: 256, ETA: 0:56:03
2025-07-30 05:49:15.233 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 399/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.002e-04, size: 320, ETA: 0:56:01
2025-07-30 05:49:16.478 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:49:16.659 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch400
2025-07-30 05:49:16.659 | INFO     | yolox_microbt.core.trainer:before_epoch:208 - --->No mosaic aug now!
2025-07-30 05:49:16.660 | INFO     | yolox_microbt.core.trainer:before_epoch:210 - --->Add additional L1 loss now!
2025-07-30 05:49:16.660 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:49:18.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 3.5, cls_loss: 0.8, lr: 5.001e-04, size: 256, ETA: 0:55:57
2025-07-30 05:49:20.286 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.8, lr: 5.001e-04, size: 320, ETA: 0:55:53
2025-07-30 05:49:22.028 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:55:50
2025-07-30 05:49:23.791 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:55:47
2025-07-30 05:49:25.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:55:44
2025-07-30 05:49:27.315 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 400/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.9, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 4.5, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:55:41
2025-07-30 05:49:28.124 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:49:34.569 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:49:35.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:49:35.811 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5654
2025-07-30 05:49:35.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5093
2025-07-30 05:49:36.005 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2913
2025-07-30 05:49:36.006 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4553
2025-07-30 05:49:36.006 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:49:36.006 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.565
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.509
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.291
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.455
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:49:36.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:49:36.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:49:36.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:49:36.008 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:49:36.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:49:37.277 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:49:37.885 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:49:38.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:49:39.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:49:39.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:49:40.366 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:49:41.012 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:49:41.620 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:49:41.620 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:49:41.620 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-30 05:49:41.620 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:49:41.627 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.34 ms, Average NMS time: 0.88 ms, Average inference time: 2.22 ms

2025-07-30 05:49:41.628 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:49:41.652 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:49:41.680 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch401
2025-07-30 05:49:43.394 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:55:37
2025-07-30 05:49:45.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:55:34
2025-07-30 05:49:46.861 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:55:31
2025-07-30 05:49:48.621 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:55:28
2025-07-30 05:49:50.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:55:25
2025-07-30 05:49:52.283 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 401/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:55:22
2025-07-30 05:49:53.098 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:49:53.149 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch402
2025-07-30 05:49:54.912 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.9, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 1.1, lr: 5.000e-04, size: 416, ETA: 0:55:17
2025-07-30 05:49:56.664 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:55:14
2025-07-30 05:49:58.385 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 6.1, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:55:11
2025-07-30 05:50:00.165 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.0, l1_loss: 1.3, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:55:08
2025-07-30 05:50:02.032 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:55:05
2025-07-30 05:50:03.884 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 402/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 9.1, iou_loss: 3.0, l1_loss: 1.5, conf_loss: 3.8, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:55:02
2025-07-30 05:50:04.677 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:50:04.739 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch403
2025-07-30 05:50:06.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 1.1, lr: 5.000e-04, size: 288, ETA: 0:54:58
2025-07-30 05:50:08.202 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:54:55
2025-07-30 05:50:09.987 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:54:52
2025-07-30 05:50:11.771 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:54:49
2025-07-30 05:50:13.607 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:54:46
2025-07-30 05:50:15.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 403/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.9, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:54:43
2025-07-30 05:50:16.200 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:50:16.243 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch404
2025-07-30 05:50:18.066 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:54:39
2025-07-30 05:50:19.827 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:54:36
2025-07-30 05:50:21.596 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:54:33
2025-07-30 05:50:23.406 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:54:30
2025-07-30 05:50:25.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:54:27
2025-07-30 05:50:26.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 404/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:54:24
2025-07-30 05:50:27.728 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:50:27.770 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch405
2025-07-30 05:50:29.614 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 1.0, lr: 5.000e-04, size: 576, ETA: 0:54:19
2025-07-30 05:50:31.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:54:16
2025-07-30 05:50:33.280 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:54:13
2025-07-30 05:50:35.093 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:54:10
2025-07-30 05:50:36.797 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:54:07
2025-07-30 05:50:38.655 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 405/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:54:04
2025-07-30 05:50:39.417 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:50:45.757 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:50:46.656 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:50:47.226 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5677
2025-07-30 05:50:47.357 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5145
2025-07-30 05:50:47.397 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3040
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4621
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.568
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.515
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.304
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.462
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:50:47.398 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:50:47.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:50:47.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:50:47.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:50:47.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:50:47.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:50:47.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:50:48.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:50:48.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:50:49.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:50:50.392 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:50:51.130 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:50:51.833 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:50:52.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:50:53.332 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:50:54.034 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:50:54.034 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:50:54.034 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-30 05:50:54.034 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:50:54.043 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.92 ms, Average inference time: 2.31 ms

2025-07-30 05:50:54.043 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:50:54.069 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:50:54.102 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch406
2025-07-30 05:50:55.725 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 9.2, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 3.7, cls_loss: 1.6, lr: 5.000e-04, size: 352, ETA: 0:54:00
2025-07-30 05:50:57.537 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:53:57
2025-07-30 05:50:59.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, 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: 352, ETA: 0:53:54
2025-07-30 05:51:01.025 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:53:51
2025-07-30 05:51:02.705 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:53:48
2025-07-30 05:51:04.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 406/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 7.8, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 3.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:53:45
2025-07-30 05:51:05.306 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:51:05.355 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch407
2025-07-30 05:51:07.207 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.005s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:53:41
2025-07-30 05:51:08.956 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:53:38
2025-07-30 05:51:10.754 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:53:35
2025-07-30 05:51:12.518 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:53:32
2025-07-30 05:51:14.329 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:53:29
2025-07-30 05:51:16.173 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 407/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 8.6, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 3.8, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:53:26
2025-07-30 05:51:17.002 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:51:17.042 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch408
2025-07-30 05:51:18.787 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:53:21
2025-07-30 05:51:20.605 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 18.7, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 18.7, cls_loss: 0.0, lr: 5.000e-04, size: 416, ETA: 0:53:18
2025-07-30 05:51:22.360 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:53:15
2025-07-30 05:51:24.080 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 1.3, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:53:12
2025-07-30 05:51:25.893 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:53:09
2025-07-30 05:51:27.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 408/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:53:06
2025-07-30 05:51:28.419 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:51:28.463 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch409
2025-07-30 05:51:30.256 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.6, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 3.7, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:53:02
2025-07-30 05:51:32.031 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, 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: 0:52:59
2025-07-30 05:51:33.762 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 4.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:52:56
2025-07-30 05:51:35.524 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:52:53
2025-07-30 05:51:37.344 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:52:50
2025-07-30 05:51:39.083 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 409/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:52:47
2025-07-30 05:51:39.893 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:51:39.934 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch410
2025-07-30 05:51:41.664 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 1.5, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:52:43
2025-07-30 05:51:43.334 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:52:40
2025-07-30 05:51:45.077 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, 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: 416, ETA: 0:52:37
2025-07-30 05:51:46.796 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:52:34
2025-07-30 05:51:48.640 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:52:31
2025-07-30 05:51:50.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 410/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:52:28
2025-07-30 05:51:51.155 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:51:57.551 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:51:58.244 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:51:58.681 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5426
2025-07-30 05:51:58.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4491
2025-07-30 05:51:58.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2670
2025-07-30 05:51:58.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4195
2025-07-30 05:51:58.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:51:58.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:51:58.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.543
2025-07-30 05:51:58.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.449
2025-07-30 05:51:58.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.267
2025-07-30 05:51:58.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.420
2025-07-30 05:51:58.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:51:58.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:51:58.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:51:58.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:51:58.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:51:58.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:51:58.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:51:58.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:51:58.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:51:59.377 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:51:59.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:52:00.442 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:52:00.984 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:52:01.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:52:02.074 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:52:02.593 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:52:03.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:52:03.683 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:52:03.683 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 05:52:03.683 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-07-30 05:52:03.683 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:52:03.690 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.91 ms, Average inference time: 2.29 ms

2025-07-30 05:52:03.690 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:52:03.716 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:52:03.743 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch411
2025-07-30 05:52:05.405 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:52:24
2025-07-30 05:52:07.133 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:52:21
2025-07-30 05:52:08.935 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.3, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:52:18
2025-07-30 05:52:10.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:52:15
2025-07-30 05:52:12.533 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:52:12
2025-07-30 05:52:14.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 411/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 1.1, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:52:09
2025-07-30 05:52:15.111 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:52:15.156 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch412
2025-07-30 05:52:16.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:52:05
2025-07-30 05:52:18.675 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:52:02
2025-07-30 05:52:20.510 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 9.3, iou_loss: 2.8, l1_loss: 1.7, conf_loss: 4.0, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:51:59
2025-07-30 05:52:22.279 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 1.5, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:51:56
2025-07-30 05:52:24.095 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:51:53
2025-07-30 05:52:25.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 412/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:51:50
2025-07-30 05:52:26.626 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:52:26.660 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch413
2025-07-30 05:52:28.485 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:51:46
2025-07-30 05:52:30.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:51:43
2025-07-30 05:52:32.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, 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: 544, ETA: 0:51:40
2025-07-30 05:52:33.844 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.5, l1_loss: 1.6, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:51:37
2025-07-30 05:52:35.661 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:51:34
2025-07-30 05:52:37.458 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 413/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 7.9, iou_loss: 3.4, l1_loss: 1.4, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:51:31
2025-07-30 05:52:38.256 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:52:38.296 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch414
2025-07-30 05:52:40.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:51:27
2025-07-30 05:52:41.897 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 8.8, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 4.7, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:51:24
2025-07-30 05:52:43.652 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:51:21
2025-07-30 05:52:45.373 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:51:18
2025-07-30 05:52:47.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:51:15
2025-07-30 05:52:48.894 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 414/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:51:12
2025-07-30 05:52:49.651 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:52:49.688 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch415
2025-07-30 05:52:51.509 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:51:08
2025-07-30 05:52:53.343 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.1, l1_loss: 1.9, conf_loss: 2.8, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:51:05
2025-07-30 05:52:55.113 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:51:02
2025-07-30 05:52:56.835 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 8.3, iou_loss: 3.3, l1_loss: 1.6, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:50:59
2025-07-30 05:52:58.550 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 3.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:50:56
2025-07-30 05:53:00.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 415/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:50:53
2025-07-30 05:53:01.211 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:53:07.501 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:53:08.531 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:53:09.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5709
2025-07-30 05:53:09.299 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4990
2025-07-30 05:53:09.338 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3332
2025-07-30 05:53:09.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4677
2025-07-30 05:53:09.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:53:09.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:53:09.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.571
2025-07-30 05:53:09.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.499
2025-07-30 05:53:09.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.333
2025-07-30 05:53:09.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.468
2025-07-30 05:53:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:53:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:53:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:53:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:53:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:53:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:53:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:53:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:53:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:53:10.192 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:53:10.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:53:11.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:53:12.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:53:13.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:53:14.298 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:53:15.082 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:53:15.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:53:16.687 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:53:16.688 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 05:53:16.688 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-30 05:53:16.688 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:53:16.695 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.95 ms, Average inference time: 2.31 ms

2025-07-30 05:53:16.696 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:53:16.724 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:53:16.752 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch416
2025-07-30 05:53:18.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.003s, 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: 512, ETA: 0:50:49
2025-07-30 05:53:20.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:50:46
2025-07-30 05:53:22.019 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.4, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:50:43
2025-07-30 05:53:23.874 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.5, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:50:40
2025-07-30 05:53:25.721 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:50:37
2025-07-30 05:53:27.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 416/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:50:34
2025-07-30 05:53:28.257 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:53:28.291 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch417
2025-07-30 05:53:30.064 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 4.6, iou_loss: 1.5, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:50:30
2025-07-30 05:53:31.975 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.7Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:50:27
2025-07-30 05:53:33.732 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 2.9, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:50:24
2025-07-30 05:53:35.471 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 9.5, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 4.8, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:50:21
2025-07-30 05:53:37.297 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.2, iou_loss: 1.9, l1_loss: 1.2, conf_loss: 2.1, cls_loss: 1.0, lr: 5.000e-04, size: 576, ETA: 0:50:18
2025-07-30 05:53:39.102 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 417/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.001s, total_loss: 6.1, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:50:15
2025-07-30 05:53:39.898 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:53:39.952 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch418
2025-07-30 05:53:41.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:50:11
2025-07-30 05:53:43.621 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 9.2, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 3.9, cls_loss: 1.7, lr: 5.000e-04, size: 512, ETA: 0:50:08
2025-07-30 05:53:45.346 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:50:05
2025-07-30 05:53:47.126 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:50:02
2025-07-30 05:53:48.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:49:59
2025-07-30 05:53:50.651 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 418/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:49:56
2025-07-30 05:53:51.494 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:53:51.530 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch419
2025-07-30 05:53:53.249 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.003s, total_loss: 7.5, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:49:52
2025-07-30 05:53:55.048 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 1.0, lr: 5.000e-04, size: 576, ETA: 0:49:49
2025-07-30 05:53:56.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:49:46
2025-07-30 05:53:58.587 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:49:43
2025-07-30 05:54:00.393 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:49:40
2025-07-30 05:54:02.194 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 419/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:49:38
2025-07-30 05:54:02.980 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:54:03.019 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch420
2025-07-30 05:54:04.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:49:33
2025-07-30 05:54:06.592 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:49:30
2025-07-30 05:54:08.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:49:28
2025-07-30 05:54:10.087 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 10.1, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 5.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:49:25
2025-07-30 05:54:11.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:49:22
2025-07-30 05:54:13.621 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 420/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.1, l1_loss: 0.3, conf_loss: 1.6, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:49:19
2025-07-30 05:54:14.412 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:54:20.713 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:54:21.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:54:22.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5806
2025-07-30 05:54:22.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5122
2025-07-30 05:54:22.352 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3334
2025-07-30 05:54:22.352 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4754
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.581
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.512
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.333
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.475
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:54:22.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:54:22.354 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:54:22.354 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:54:22.354 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:54:22.354 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:54:22.354 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:54:23.053 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:54:23.771 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:54:24.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:54:25.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:54:25.859 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:54:26.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:54:27.211 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:54:27.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:54:28.606 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:54:28.606 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 05:54:28.606 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-30 05:54:28.606 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:54:28.613 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.92 ms, Average inference time: 2.28 ms

2025-07-30 05:54:28.615 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:54:28.636 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:54:28.665 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch421
2025-07-30 05:54:30.423 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:49:15
2025-07-30 05:54:32.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:49:12
2025-07-30 05:54:33.941 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:49:09
2025-07-30 05:54:35.699 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:49:06
2025-07-30 05:54:37.491 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:49:03
2025-07-30 05:54:39.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 421/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.2, cls_loss: 1.1, lr: 5.000e-04, size: 256, ETA: 0:49:00
2025-07-30 05:54:39.962 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:54:39.999 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch422
2025-07-30 05:54:41.750 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:48:56
2025-07-30 05:54:43.575 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 11.8, iou_loss: 2.7, l1_loss: 2.1, conf_loss: 6.2, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:48:53
2025-07-30 05:54:45.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:48:50
2025-07-30 05:54:47.131 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:48:47
2025-07-30 05:54:48.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:48:44
2025-07-30 05:54:50.641 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 422/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:48:41
2025-07-30 05:54:51.441 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:54:51.493 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch423
2025-07-30 05:54:53.302 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.005s, 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: 0:48:37
2025-07-30 05:54:55.076 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:48:34
2025-07-30 05:54:56.804 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 10.0, iou_loss: 3.1, l1_loss: 1.1, conf_loss: 4.9, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:48:31
2025-07-30 05:54:58.556 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:48:28
2025-07-30 05:55:00.396 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 3.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:48:26
2025-07-30 05:55:02.106 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 423/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.5, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:48:23
2025-07-30 05:55:02.879 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:55:02.946 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch424
2025-07-30 05:55:04.693 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 1.1, lr: 5.000e-04, size: 384, ETA: 0:48:18
2025-07-30 05:55:06.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.4, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 4.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:48:16
2025-07-30 05:55:08.252 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:48:13
2025-07-30 05:55:10.027 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:48:10
2025-07-30 05:55:11.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:48:07
2025-07-30 05:55:13.567 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 424/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.7, l1_loss: 1.6, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:48:04
2025-07-30 05:55:14.325 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:55:14.359 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch425
2025-07-30 05:55:16.064 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:48:00
2025-07-30 05:55:17.828 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 10.5, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 5.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:47:57
2025-07-30 05:55:19.608 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.8, iou_loss: 2.8, l1_loss: 1.6, conf_loss: 3.4, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:47:54
2025-07-30 05:55:21.416 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.001s, 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: 256, ETA: 0:47:51
2025-07-30 05:55:23.117 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 1.1, lr: 5.000e-04, size: 320, ETA: 0:47:48
2025-07-30 05:55:24.816 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 425/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, 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: 256, ETA: 0:47:45
2025-07-30 05:55:25.684 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:55:32.015 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:55:32.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:55:33.521 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5810
2025-07-30 05:55:33.748 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5136
2025-07-30 05:55:33.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3299
2025-07-30 05:55:33.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4748
2025-07-30 05:55:33.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:55:33.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:55:33.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.581
2025-07-30 05:55:33.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.514
2025-07-30 05:55:33.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.330
2025-07-30 05:55:33.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.475
2025-07-30 05:55:33.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:55:33.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:55:33.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:55:33.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:55:33.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:55:33.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:55:33.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:55:33.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:55:33.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:55:34.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:55:35.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:55:36.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:55:36.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:55:37.575 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:55:38.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:55:39.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:55:39.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:55:40.507 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:55:40.507 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 05:55:40.507 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-30 05:55:40.507 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:55:40.515 | 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: 2.32 ms

2025-07-30 05:55:40.516 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:55:40.541 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:55:40.571 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch426
2025-07-30 05:55:42.283 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:47:41
2025-07-30 05:55:44.125 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:47:38
2025-07-30 05:55:45.964 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:47:35
2025-07-30 05:55:47.843 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 1.5, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:47:33
2025-07-30 05:55:49.617 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:47:30
2025-07-30 05:55:51.401 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 426/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:47:27
2025-07-30 05:55:52.176 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:55:52.228 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch427
2025-07-30 05:55:54.027 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 12.8, iou_loss: 2.9, l1_loss: 1.5, conf_loss: 7.7, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:47:23
2025-07-30 05:55:55.838 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:47:20
2025-07-30 05:55:57.682 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:47:17
2025-07-30 05:55:59.426 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:47:14
2025-07-30 05:56:01.226 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:47:11
2025-07-30 05:56:02.965 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 427/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 8.8, iou_loss: 2.8, l1_loss: 1.6, conf_loss: 3.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:47:08
2025-07-30 05:56:03.821 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:56:03.865 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch428
2025-07-30 05:56:05.654 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:47:04
2025-07-30 05:56:07.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 1.3, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:47:01
2025-07-30 05:56:09.108 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:46:58
2025-07-30 05:56:10.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:46:56
2025-07-30 05:56:12.597 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:46:53
2025-07-30 05:56:14.341 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 428/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:46:50
2025-07-30 05:56:15.184 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:56:15.220 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch429
2025-07-30 05:56:16.983 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:46:46
2025-07-30 05:56:18.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:46:43
2025-07-30 05:56:20.518 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.7, iou_loss: 2.8, l1_loss: 1.4, conf_loss: 3.9, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:46:40
2025-07-30 05:56:22.297 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:46:37
2025-07-30 05:56:24.080 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:46:34
2025-07-30 05:56:25.790 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 429/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:46:31
2025-07-30 05:56:26.666 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:56:26.772 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch430
2025-07-30 05:56:28.413 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 1.0, lr: 5.000e-04, size: 288, ETA: 0:46:27
2025-07-30 05:56:30.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:46:24
2025-07-30 05:56:31.984 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 3.5, cls_loss: 1.1, lr: 5.000e-04, size: 352, ETA: 0:46:21
2025-07-30 05:56:33.744 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:46:19
2025-07-30 05:56:35.523 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:46:16
2025-07-30 05:56:37.313 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 430/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:46:13
2025-07-30 05:56:38.109 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:56:44.448 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:56:45.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:56:46.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5728
2025-07-30 05:56:46.350 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5188
2025-07-30 05:56:46.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3236
2025-07-30 05:56:46.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4717
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.573
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.519
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.324
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.472
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:56:46.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:56:46.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:56:46.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:56:46.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:56:46.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:56:46.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:56:47.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:56:48.238 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:56:49.128 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:56:49.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:56:50.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:56:51.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:56:52.683 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:56:53.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:56:54.434 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:56:54.434 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 05:56:54.434 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-30 05:56:54.434 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:56:54.441 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.34 ms, Average NMS time: 0.92 ms, Average inference time: 2.26 ms

2025-07-30 05:56:54.442 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:56:54.468 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:56:54.497 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch431
2025-07-30 05:56:56.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:46:09
2025-07-30 05:56:57.929 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:46:06
2025-07-30 05:56:59.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:46:03
2025-07-30 05:57:01.623 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:46:00
2025-07-30 05:57:03.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.9, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 3.4, cls_loss: 1.0, lr: 5.000e-04, size: 448, ETA: 0:45:57
2025-07-30 05:57:05.214 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 431/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:45:55
2025-07-30 05:57:06.041 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:57:06.081 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch432
2025-07-30 05:57:07.827 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:45:50
2025-07-30 05:57:09.612 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 3.2, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:45:48
2025-07-30 05:57:11.456 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:45:45
2025-07-30 05:57:13.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 10.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 6.1, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:45:42
2025-07-30 05:57:14.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 2.7, cls_loss: 1.2, lr: 5.000e-04, size: 288, ETA: 0:45:39
2025-07-30 05:57:16.836 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 432/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:45:36
2025-07-30 05:57:17.694 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:57:17.745 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch433
2025-07-30 05:57:19.503 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:45:32
2025-07-30 05:57:21.303 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:45:29
2025-07-30 05:57:23.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:45:27
2025-07-30 05:57:24.736 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.1, iou_loss: 1.4, l1_loss: 0.6, conf_loss: 3.6, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:45:24
2025-07-30 05:57:26.477 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 1.2, lr: 5.000e-04, size: 416, ETA: 0:45:21
2025-07-30 05:57:28.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 433/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:45:18
2025-07-30 05:57:29.037 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:57:29.089 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch434
2025-07-30 05:57:30.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, 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: 352, ETA: 0:45:14
2025-07-30 05:57:32.583 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:45:11
2025-07-30 05:57:34.355 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 2.8, iou_loss: 0.6, l1_loss: 0.2, conf_loss: 1.6, cls_loss: 0.3, lr: 5.000e-04, size: 320, ETA: 0:45:08
2025-07-30 05:57:36.058 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, 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: 352, ETA: 0:45:05
2025-07-30 05:57:37.914 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:45:03
2025-07-30 05:57:39.674 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 434/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:45:00
2025-07-30 05:57:40.475 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:57:40.510 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch435
2025-07-30 05:57:42.236 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:44:56
2025-07-30 05:57:44.015 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:44:53
2025-07-30 05:57:45.701 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, 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: 320, ETA: 0:44:50
2025-07-30 05:57:47.424 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.0, l1_loss: 1.8, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:44:47
2025-07-30 05:57:49.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:44:44
2025-07-30 05:57:50.957 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 435/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.3, iou_loss: 3.1, l1_loss: 1.3, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:44:41
2025-07-30 05:57:51.754 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:57:58.096 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:57:58.934 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:57:59.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5471
2025-07-30 05:57:59.524 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5009
2025-07-30 05:57:59.613 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2939
2025-07-30 05:57:59.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4473
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.547
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.501
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.294
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.447
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:57:59.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:57:59.616 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:57:59.616 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:57:59.616 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:58:00.255 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:58:00.935 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:58:01.561 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:58:02.192 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:58:02.855 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:58:03.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:58:04.112 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:58:04.768 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:58:05.389 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:58:05.389 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 05:58:05.389 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 05:58:05.389 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:58:05.396 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.94 ms, Average inference time: 2.31 ms

2025-07-30 05:58:05.397 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:58:05.421 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:58:05.450 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch436
2025-07-30 05:58:07.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.080s, 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: 0:44:37
2025-07-30 05:58:08.898 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.7, l1_loss: 1.5, conf_loss: 3.5, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:44:34
2025-07-30 05:58:10.772 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:44:32
2025-07-30 05:58:12.469 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:44:29
2025-07-30 05:58:14.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:44:26
2025-07-30 05:58:15.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 436/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:44:23
2025-07-30 05:58:16.733 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:58:16.766 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch437
2025-07-30 05:58:18.486 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, 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: 352, ETA: 0:44:19
2025-07-30 05:58:20.235 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:44:16
2025-07-30 05:58:22.088 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 1.2, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:44:13
2025-07-30 05:58:23.947 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:44:11
2025-07-30 05:58:25.776 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:44:08
2025-07-30 05:58:27.592 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 437/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:44:05
2025-07-30 05:58:28.441 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:58:28.484 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch438
2025-07-30 05:58:30.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:44:01
2025-07-30 05:58:31.930 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:43:58
2025-07-30 05:58:33.697 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:43:55
2025-07-30 05:58:35.447 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.8, l1_loss: 1.4, conf_loss: 3.0, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:43:52
2025-07-30 05:58:37.237 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.6, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 3.7, cls_loss: 1.1, lr: 5.000e-04, size: 352, ETA: 0:43:50
2025-07-30 05:58:38.974 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 438/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:43:47
2025-07-30 05:58:39.769 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:58:39.805 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch439
2025-07-30 05:58:41.519 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 1.3, lr: 5.000e-04, size: 544, ETA: 0:43:43
2025-07-30 05:58:43.289 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:43:40
2025-07-30 05:58:45.110 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 1.3, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:43:37
2025-07-30 05:58:46.945 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:43:34
2025-07-30 05:58:48.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:43:32
2025-07-30 05:58:50.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 439/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:43:29
2025-07-30 05:58:51.370 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:58:51.411 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch440
2025-07-30 05:58:53.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:43:25
2025-07-30 05:58:54.867 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.9, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 1.0, lr: 5.000e-04, size: 320, ETA: 0:43:22
2025-07-30 05:58:56.607 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, 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: 544, ETA: 0:43:19
2025-07-30 05:58:58.443 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.087s, 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: 512, ETA: 0:43:16
2025-07-30 05:59:00.179 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:43:13
2025-07-30 05:59:02.029 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 440/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.003s, 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: 352, ETA: 0:43:11
2025-07-30 05:59:02.784 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:59:09.203 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 05:59:10.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 05:59:10.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5776
2025-07-30 05:59:10.757 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5166
2025-07-30 05:59:10.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3397
2025-07-30 05:59:10.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4780
2025-07-30 05:59:10.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 05:59:10.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 05:59:10.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.578
2025-07-30 05:59:10.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.517
2025-07-30 05:59:10.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.340
2025-07-30 05:59:10.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.478
2025-07-30 05:59:10.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 05:59:10.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 05:59:10.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 05:59:10.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 05:59:10.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 05:59:10.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 05:59:10.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 05:59:10.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 05:59:10.799 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 05:59:11.592 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 05:59:12.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 05:59:13.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 05:59:13.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 05:59:14.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 05:59:15.158 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 05:59:15.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 05:59:16.733 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 05:59:17.494 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 05:59:17.495 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-30 05:59:17.495 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-30 05:59:17.495 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 05:59:17.502 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.92 ms, Average inference time: 2.30 ms

2025-07-30 05:59:17.503 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:59:17.528 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:59:17.561 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch441
2025-07-30 05:59:19.255 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.3, l1_loss: 1.4, conf_loss: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:43:07
2025-07-30 05:59:21.039 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:43:04
2025-07-30 05:59:22.762 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:43:01
2025-07-30 05:59:24.523 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:42:58
2025-07-30 05:59:26.274 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:42:55
2025-07-30 05:59:28.012 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 441/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:42:53
2025-07-30 05:59:28.767 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:59:28.800 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch442
2025-07-30 05:59:30.550 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:42:48
2025-07-30 05:59:32.325 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:42:46
2025-07-30 05:59:34.172 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.1Gb, 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: 0.7, lr: 5.000e-04, size: 576, ETA: 0:42:43
2025-07-30 05:59:35.995 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.089s, data_time: 0.001s, total_loss: 5.4, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:42:40
2025-07-30 05:59:37.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 3.5, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:42:37
2025-07-30 05:59:39.500 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 442/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:42:35
2025-07-30 05:59:40.325 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:59:40.363 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch443
2025-07-30 05:59:42.191 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:42:30
2025-07-30 05:59:44.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.001s, total_loss: 8.2, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 3.5, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:42:28
2025-07-30 05:59:45.867 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:42:25
2025-07-30 05:59:47.640 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:42:22
2025-07-30 05:59:49.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:42:19
2025-07-30 05:59:51.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 443/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 3.4, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:42:17
2025-07-30 05:59:52.014 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 05:59:52.054 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch444
2025-07-30 05:59:53.868 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:42:13
2025-07-30 05:59:55.618 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:42:10
2025-07-30 05:59:57.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:42:07
2025-07-30 05:59:59.117 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:42:04
2025-07-30 06:00:00.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:42:01
2025-07-30 06:00:02.658 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 444/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:41:59
2025-07-30 06:00:03.489 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:00:03.532 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch445
2025-07-30 06:00:05.307 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 3.6, cls_loss: 1.2, lr: 5.000e-04, size: 512, ETA: 0:41:55
2025-07-30 06:00:07.078 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:41:52
2025-07-30 06:00:08.873 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, 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: 544, ETA: 0:41:49
2025-07-30 06:00:10.694 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.5, iou_loss: 3.2, l1_loss: 1.4, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:41:46
2025-07-30 06:00:12.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:41:44
2025-07-30 06:00:14.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 445/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.006s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:41:41
2025-07-30 06:00:15.156 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:00:21.429 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:00:22.430 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:00:23.020 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5309
2025-07-30 06:00:23.147 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4696
2025-07-30 06:00:23.233 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3120
2025-07-30 06:00:23.233 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4375
2025-07-30 06:00:23.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:00:23.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:00:23.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.531
2025-07-30 06:00:23.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.470
2025-07-30 06:00:23.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.312
2025-07-30 06:00:23.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.437
2025-07-30 06:00:23.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:00:23.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:00:23.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:00:23.235 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:00:23.235 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:00:23.235 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:00:23.235 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:00:23.235 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:00:23.235 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:00:23.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:00:24.791 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:00:25.574 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:00:26.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:00:27.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:00:27.908 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:00:28.663 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:00:29.455 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:00:30.213 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:00:30.213 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 06:00:30.213 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-30 06:00:30.213 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:00:30.221 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.95 ms, Average inference time: 2.35 ms

2025-07-30 06:00:30.221 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:00:30.246 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:00:30.276 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch446
2025-07-30 06:00:31.969 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:41:37
2025-07-30 06:00:33.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:41:34
2025-07-30 06:00:35.474 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:41:31
2025-07-30 06:00:37.201 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:41:28
2025-07-30 06:00:38.942 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:41:26
2025-07-30 06:00:40.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 446/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.005s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:41:23
2025-07-30 06:00:41.680 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:00:41.753 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch447
2025-07-30 06:00:43.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:41:19
2025-07-30 06:00:45.163 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:41:16
2025-07-30 06:00:46.966 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:41:13
2025-07-30 06:00:48.669 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:41:11
2025-07-30 06:00:50.513 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:41:08
2025-07-30 06:00:52.333 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 447/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 8.0, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:41:05
2025-07-30 06:00:53.150 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:00:53.210 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch448
2025-07-30 06:00:54.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:41:01
2025-07-30 06:00:56.697 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:40:58
2025-07-30 06:00:58.545 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:40:55
2025-07-30 06:01:00.317 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:40:53
2025-07-30 06:01:02.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 18.3, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 18.3, cls_loss: 0.0, lr: 5.000e-04, size: 288, ETA: 0:40:50
2025-07-30 06:01:03.985 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 448/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:40:47
2025-07-30 06:01:04.772 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:01:04.825 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch449
2025-07-30 06:01:06.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:40:43
2025-07-30 06:01:08.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 9.3, iou_loss: 3.3, l1_loss: 1.2, conf_loss: 4.0, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:40:40
2025-07-30 06:01:10.042 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:40:38
2025-07-30 06:01:11.827 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:40:35
2025-07-30 06:01:13.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 100/129, gpu mem: 1553Mb, 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: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:40:32
2025-07-30 06:01:15.473 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 449/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 4.8, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:40:29
2025-07-30 06:01:16.279 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:01:16.317 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch450
2025-07-30 06:01:18.138 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:40:25
2025-07-30 06:01:19.863 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:40:23
2025-07-30 06:01:21.690 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 1.3, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:40:20
2025-07-30 06:01:23.484 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:40:17
2025-07-30 06:01:25.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:40:14
2025-07-30 06:01:27.109 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 450/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 8.0, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:40:12
2025-07-30 06:01:27.881 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:01:34.239 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:01:35.098 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:01:35.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5717
2025-07-30 06:01:35.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4957
2025-07-30 06:01:35.720 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3349
2025-07-30 06:01:35.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4674
2025-07-30 06:01:35.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:01:35.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.572
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.496
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.335
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.467
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:01:35.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:01:35.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:01:35.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:01:36.440 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:01:37.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:01:37.715 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:01:38.319 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:01:38.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:01:39.567 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:01:40.203 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:01:40.815 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:01:41.455 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:01:41.456 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-30 06:01:41.456 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-30 06:01:41.456 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:01:41.463 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.34 ms, Average NMS time: 0.94 ms, Average inference time: 2.28 ms

2025-07-30 06:01:41.463 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:01:41.488 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:01:41.517 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch451
2025-07-30 06:01:43.222 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 3.2, cls_loss: 1.2, lr: 5.000e-04, size: 256, ETA: 0:40:08
2025-07-30 06:01:45.060 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:40:05
2025-07-30 06:01:46.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:40:02
2025-07-30 06:01:48.635 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:39:59
2025-07-30 06:01:50.444 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:39:57
2025-07-30 06:01:52.143 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 451/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:39:54
2025-07-30 06:01:52.890 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:01:52.941 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch452
2025-07-30 06:01:54.672 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:39:50
2025-07-30 06:01:56.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:39:47
2025-07-30 06:01:58.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:39:45
2025-07-30 06:02:00.032 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 3.4, cls_loss: 1.1, lr: 5.000e-04, size: 448, ETA: 0:39:42
2025-07-30 06:02:01.799 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:39:39
2025-07-30 06:02:03.568 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 452/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:39:36
2025-07-30 06:02:04.328 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:02:04.364 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch453
2025-07-30 06:02:06.162 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:39:32
2025-07-30 06:02:07.965 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:39:30
2025-07-30 06:02:09.734 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, 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: 0.7, lr: 5.000e-04, size: 320, ETA: 0:39:27
2025-07-30 06:02:11.553 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:39:24
2025-07-30 06:02:13.367 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:39:21
2025-07-30 06:02:15.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 453/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:39:19
2025-07-30 06:02:15.955 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:02:15.999 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch454
2025-07-30 06:02:17.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:39:15
2025-07-30 06:02:19.417 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.8, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:39:12
2025-07-30 06:02:21.170 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:39:09
2025-07-30 06:02:22.929 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, 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: 384, ETA: 0:39:06
2025-07-30 06:02:24.647 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.081s, 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: 384, ETA: 0:39:04
2025-07-30 06:02:26.497 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 454/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:39:01
2025-07-30 06:02:27.249 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:02:27.285 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch455
2025-07-30 06:02:29.047 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:38:57
2025-07-30 06:02:30.850 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:38:54
2025-07-30 06:02:32.642 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:38:52
2025-07-30 06:02:34.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 3.6, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:38:49
2025-07-30 06:02:36.140 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:38:46
2025-07-30 06:02:37.937 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 455/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 2.1, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:38:43
2025-07-30 06:02:38.725 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:02:44.959 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:02:45.895 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:02:46.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5429
2025-07-30 06:02:46.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4921
2025-07-30 06:02:46.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3132
2025-07-30 06:02:46.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4494
2025-07-30 06:02:46.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:02:46.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:02:46.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.543
2025-07-30 06:02:46.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.492
2025-07-30 06:02:46.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.313
2025-07-30 06:02:46.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.449
2025-07-30 06:02:46.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:02:46.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:02:46.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:02:46.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:02:46.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:02:46.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:02:46.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:02:46.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:02:46.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:02:47.527 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:02:48.247 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:02:49.013 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:02:49.733 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:02:50.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:02:51.219 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:02:51.949 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:02:52.714 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:02:53.451 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:02:53.451 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 06:02:53.452 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 06:02:53.452 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:02:53.459 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.33 ms, Average NMS time: 0.91 ms, Average inference time: 2.24 ms

2025-07-30 06:02:53.460 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:02:53.486 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:02:53.515 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch456
2025-07-30 06:02:55.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:38:39
2025-07-30 06:02:56.946 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.3, l1_loss: 1.7, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:38:37
2025-07-30 06:02:58.741 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:38:34
2025-07-30 06:03:00.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:38:31
2025-07-30 06:03:02.178 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:38:28
2025-07-30 06:03:04.074 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 456/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 3.1, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:38:26
2025-07-30 06:03:04.898 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:03:05.000 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch457
2025-07-30 06:03:06.785 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:38:22
2025-07-30 06:03:08.552 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:38:19
2025-07-30 06:03:10.336 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.2, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:38:16
2025-07-30 06:03:12.120 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, 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: 448, ETA: 0:38:14
2025-07-30 06:03:13.919 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:38:11
2025-07-30 06:03:15.657 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 457/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:38:08
2025-07-30 06:03:16.417 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:03:16.456 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch458
2025-07-30 06:03:18.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:38:04
2025-07-30 06:03:20.039 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:38:01
2025-07-30 06:03:21.854 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.6, iou_loss: 2.9, l1_loss: 1.8, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:37:59
2025-07-30 06:03:23.658 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:37:56
2025-07-30 06:03:25.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:37:53
2025-07-30 06:03:27.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 458/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:37:51
2025-07-30 06:03:28.098 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:03:28.162 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch459
2025-07-30 06:03:29.890 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:37:47
2025-07-30 06:03:31.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 3.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:37:44
2025-07-30 06:03:33.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:37:41
2025-07-30 06:03:35.199 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:37:38
2025-07-30 06:03:37.007 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:37:36
2025-07-30 06:03:38.769 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 459/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 7.7, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 3.8, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:37:33
2025-07-30 06:03:39.539 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:03:39.572 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch460
2025-07-30 06:03:41.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.5, l1_loss: 1.8, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:37:29
2025-07-30 06:03:43.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, 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: 576, ETA: 0:37:26
2025-07-30 06:03:44.959 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 8.4, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:37:24
2025-07-30 06:03:46.826 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 9.2, iou_loss: 2.8, l1_loss: 1.6, conf_loss: 4.1, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:37:21
2025-07-30 06:03:48.612 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:37:18
2025-07-30 06:03:50.404 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 460/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:37:16
2025-07-30 06:03:51.150 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:03:57.373 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:03:58.343 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:03:58.906 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5868
2025-07-30 06:03:59.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5357
2025-07-30 06:03:59.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3287
2025-07-30 06:03:59.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4838
2025-07-30 06:03:59.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:03:59.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:03:59.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.587
2025-07-30 06:03:59.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.536
2025-07-30 06:03:59.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.329
2025-07-30 06:03:59.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.484
2025-07-30 06:03:59.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:03:59.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:03:59.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:03:59.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:03:59.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:03:59.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:03:59.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:03:59.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:03:59.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:03:59.916 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:04:00.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:04:01.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:04:02.422 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:04:03.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:04:03.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:04:04.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:04:05.580 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:04:06.336 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:04:06.336 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-30 06:04:06.336 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-30 06:04:06.336 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:04:06.346 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.33 ms, Average NMS time: 0.90 ms, Average inference time: 2.22 ms

2025-07-30 06:04:06.347 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:04:06.373 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:04:06.403 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch461
2025-07-30 06:04:08.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 4.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:37:12
2025-07-30 06:04:09.763 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 3.3, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:37:09
2025-07-30 06:04:11.599 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, 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: 0:37:06
2025-07-30 06:04:13.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 3.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:37:04
2025-07-30 06:04:15.234 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:37:01
2025-07-30 06:04:17.044 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 461/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:36:58
2025-07-30 06:04:17.839 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:04:17.894 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch462
2025-07-30 06:04:19.637 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:36:54
2025-07-30 06:04:21.507 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:36:52
2025-07-30 06:04:23.277 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:36:49
2025-07-30 06:04:25.068 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:36:46
2025-07-30 06:04:26.819 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:36:44
2025-07-30 06:04:28.605 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 462/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:36:41
2025-07-30 06:04:29.419 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:04:29.467 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch463
2025-07-30 06:04:31.208 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:36:37
2025-07-30 06:04:32.942 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 9.4, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 5.1, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:36:34
2025-07-30 06:04:34.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 9.1, iou_loss: 3.5, l1_loss: 1.7, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:36:31
2025-07-30 06:04:36.568 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:36:29
2025-07-30 06:04:38.379 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.4, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 4.0, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:36:26
2025-07-30 06:04:40.290 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 463/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.006s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:36:23
2025-07-30 06:04:41.116 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:04:41.156 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch464
2025-07-30 06:04:42.903 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:36:20
2025-07-30 06:04:44.667 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:36:17
2025-07-30 06:04:46.469 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:36:14
2025-07-30 06:04:48.296 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.7, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 3.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:36:11
2025-07-30 06:04:50.029 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:36:09
2025-07-30 06:04:51.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 464/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:36:06
2025-07-30 06:04:52.692 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:04:52.733 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch465
2025-07-30 06:04:54.476 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:36:02
2025-07-30 06:04:56.285 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, 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: 512, ETA: 0:36:00
2025-07-30 06:04:58.087 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:35:57
2025-07-30 06:04:59.816 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:35:54
2025-07-30 06:05:01.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:35:51
2025-07-30 06:05:03.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 465/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:35:49
2025-07-30 06:05:04.247 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:05:10.708 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:05:11.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:05:12.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5811
2025-07-30 06:05:12.647 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5144
2025-07-30 06:05:12.683 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3414
2025-07-30 06:05:12.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4790
2025-07-30 06:05:12.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.581
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.514
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.341
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.479
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:05:12.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:05:12.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:05:12.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:05:12.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:05:13.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:05:14.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:05:15.263 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:05:16.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:05:16.938 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:05:17.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:05:18.612 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:05:19.516 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:05:20.342 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:05:20.343 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 06:05:20.343 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-30 06:05:20.343 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:05:20.350 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.92 ms, Average inference time: 2.29 ms

2025-07-30 06:05:20.351 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:05:20.376 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:05:20.423 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch466
2025-07-30 06:05:22.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:35:45
2025-07-30 06:05:23.842 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, 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: 384, ETA: 0:35:42
2025-07-30 06:05:25.621 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:35:39
2025-07-30 06:05:27.495 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 10.3, iou_loss: 3.3, l1_loss: 1.8, conf_loss: 4.4, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:35:37
2025-07-30 06:05:29.199 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:35:34
2025-07-30 06:05:30.997 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 466/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:35:31
2025-07-30 06:05:31.789 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:05:31.825 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch467
2025-07-30 06:05:33.554 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.084s, data_time: 0.001s, 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: 256, ETA: 0:35:28
2025-07-30 06:05:35.308 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:35:25
2025-07-30 06:05:37.130 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:35:22
2025-07-30 06:05:38.893 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:35:19
2025-07-30 06:05:40.662 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 3.5, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:35:17
2025-07-30 06:05:42.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 467/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.006s, total_loss: 8.2, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 3.7, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:35:14
2025-07-30 06:05:43.265 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:05:43.324 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch468
2025-07-30 06:05:45.022 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:35:10
2025-07-30 06:05:46.738 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:35:08
2025-07-30 06:05:48.558 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.9, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 3.6, cls_loss: 1.3, lr: 5.000e-04, size: 576, ETA: 0:35:05
2025-07-30 06:05:50.430 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 1.5, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:35:02
2025-07-30 06:05:52.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 9.1, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 4.4, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:35:00
2025-07-30 06:05:54.052 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 468/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 8.9, iou_loss: 2.9, l1_loss: 1.3, conf_loss: 3.8, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:34:57
2025-07-30 06:05:54.841 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:05:54.876 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch469
2025-07-30 06:05:56.666 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 1.0, lr: 5.000e-04, size: 320, ETA: 0:34:53
2025-07-30 06:05:58.495 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 1.0, lr: 5.000e-04, size: 288, ETA: 0:34:50
2025-07-30 06:06:00.220 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 4.9, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:34:48
2025-07-30 06:06:02.034 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:34:45
2025-07-30 06:06:03.833 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 9.3, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 4.8, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:34:42
2025-07-30 06:06:05.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 469/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 9.6, iou_loss: 3.0, l1_loss: 1.2, conf_loss: 4.6, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:34:40
2025-07-30 06:06:06.389 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:06:06.423 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch470
2025-07-30 06:06:08.126 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.0, l1_loss: 0.2, conf_loss: 1.8, cls_loss: 0.4, lr: 5.000e-04, size: 320, ETA: 0:34:36
2025-07-30 06:06:09.898 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:34:33
2025-07-30 06:06:11.672 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:34:30
2025-07-30 06:06:13.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.9, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:34:28
2025-07-30 06:06:15.262 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:34:25
2025-07-30 06:06:17.065 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 470/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:34:22
2025-07-30 06:06:17.866 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:06:24.209 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:06:24.976 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:06:25.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5773
2025-07-30 06:06:25.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5176
2025-07-30 06:06:25.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3367
2025-07-30 06:06:25.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4772
2025-07-30 06:06:25.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:06:25.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:06:25.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.577
2025-07-30 06:06:25.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.518
2025-07-30 06:06:25.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.337
2025-07-30 06:06:25.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.477
2025-07-30 06:06:25.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:06:25.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:06:25.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:06:25.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:06:25.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:06:25.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:06:25.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:06:25.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:06:25.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:06:26.236 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:06:26.841 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:06:27.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:06:28.081 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:06:28.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:06:29.338 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:06:29.943 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:06:30.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:06:31.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:06:31.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-30 06:06:31.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-30 06:06:31.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:06:31.137 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.90 ms, Average inference time: 2.24 ms

2025-07-30 06:06:31.137 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:06:31.159 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:06:31.188 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch471
2025-07-30 06:06:32.825 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 3.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:34:19
2025-07-30 06:06:34.568 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:34:16
2025-07-30 06:06:36.334 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:34:13
2025-07-30 06:06:38.041 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:34:11
2025-07-30 06:06:39.777 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:34:08
2025-07-30 06:06:41.591 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 471/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.005s, total_loss: 4.9, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:34:05
2025-07-30 06:06:42.440 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:06:42.473 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch472
2025-07-30 06:06:44.291 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 1.0, lr: 5.000e-04, size: 256, ETA: 0:34:01
2025-07-30 06:06:46.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:33:59
2025-07-30 06:06:47.836 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:33:56
2025-07-30 06:06:49.635 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 1.5, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:33:53
2025-07-30 06:06:51.490 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:33:51
2025-07-30 06:06:53.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 472/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 9.4, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 4.8, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:33:48
2025-07-30 06:06:54.138 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:06:54.179 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch473
2025-07-30 06:06:55.959 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:33:44
2025-07-30 06:06:57.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:33:42
2025-07-30 06:06:59.557 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:33:39
2025-07-30 06:07:01.310 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 1.4, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:33:36
2025-07-30 06:07:03.112 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:33:34
2025-07-30 06:07:04.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 473/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:33:31
2025-07-30 06:07:05.742 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:07:05.788 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch474
2025-07-30 06:07:07.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 7.9, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 3.9, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:33:27
2025-07-30 06:07:09.266 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 1.0, lr: 5.000e-04, size: 448, ETA: 0:33:25
2025-07-30 06:07:11.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:33:22
2025-07-30 06:07:12.767 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:33:19
2025-07-30 06:07:14.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.3, iou_loss: 1.3, l1_loss: 0.6, conf_loss: 4.8, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:33:17
2025-07-30 06:07:16.373 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 474/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:33:14
2025-07-30 06:07:17.167 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:07:17.203 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch475
2025-07-30 06:07:18.872 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.1, l1_loss: 1.0, conf_loss: 3.7, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:33:10
2025-07-30 06:07:20.691 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:33:07
2025-07-30 06:07:22.398 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.8, l1_loss: 0.4, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:33:05
2025-07-30 06:07:24.124 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:33:02
2025-07-30 06:07:25.931 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:32:59
2025-07-30 06:07:27.694 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 475/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:32:57
2025-07-30 06:07:28.486 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:07:34.977 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:07:35.916 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:07:36.444 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5892
2025-07-30 06:07:36.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5268
2025-07-30 06:07:36.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3403
2025-07-30 06:07:36.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4855
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.589
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.527
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.340
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.485
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:07:36.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:07:36.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:07:36.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:07:36.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:07:36.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:07:36.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:07:37.367 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:07:38.122 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:07:38.843 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:07:39.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:07:40.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:07:41.063 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:07:41.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:07:42.495 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:07:43.244 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:07:43.245 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 06:07:43.245 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-07-30 06:07:43.245 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:07:43.251 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.93 ms, Average inference time: 2.33 ms

2025-07-30 06:07:43.253 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:07:43.273 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:07:43.302 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch476
2025-07-30 06:07:45.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:32:53
2025-07-30 06:07:46.844 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:32:50
2025-07-30 06:07:48.647 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.8, iou_loss: 2.5, l1_loss: 1.5, conf_loss: 3.9, cls_loss: 1.0, lr: 5.000e-04, size: 544, ETA: 0:32:48
2025-07-30 06:07:50.506 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:32:45
2025-07-30 06:07:52.261 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:32:42
2025-07-30 06:07:54.023 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 476/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, 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: 512, ETA: 0:32:40
2025-07-30 06:07:54.867 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:07:54.906 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch477
2025-07-30 06:07:56.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:32:36
2025-07-30 06:07:58.368 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:32:33
2025-07-30 06:08:00.186 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:32:31
2025-07-30 06:08:02.071 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:32:28
2025-07-30 06:08:03.891 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:32:25
2025-07-30 06:08:05.672 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 477/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:32:23
2025-07-30 06:08:06.469 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:08:06.511 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch478
2025-07-30 06:08:08.312 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:32:19
2025-07-30 06:08:10.210 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:32:16
2025-07-30 06:08:11.969 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:32:14
2025-07-30 06:08:13.784 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, 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: 288, ETA: 0:32:11
2025-07-30 06:08:15.427 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.078s, 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: 448, ETA: 0:32:08
2025-07-30 06:08:17.221 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 478/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:32:06
2025-07-30 06:08:17.999 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:08:18.067 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch479
2025-07-30 06:08:19.804 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, 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: 0:32:02
2025-07-30 06:08:21.595 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 3.1, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:31:59
2025-07-30 06:08:23.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:31:57
2025-07-30 06:08:25.189 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 80/129, gpu mem: 1553Mb, 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: 0.6, lr: 5.000e-04, size: 384, ETA: 0:31:54
2025-07-30 06:08:26.957 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:31:51
2025-07-30 06:08:28.696 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 479/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:31:49
2025-07-30 06:08:29.435 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:08:29.469 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch480
2025-07-30 06:08:31.090 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:31:45
2025-07-30 06:08:32.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:31:42
2025-07-30 06:08:34.664 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 9.3, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 3.8, cls_loss: 1.6, lr: 5.000e-04, size: 416, ETA: 0:31:40
2025-07-30 06:08:36.384 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:31:37
2025-07-30 06:08:38.150 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:31:34
2025-07-30 06:08:39.944 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 480/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:31:32
2025-07-30 06:08:40.711 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:08:47.127 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:08:48.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:08:48.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5523
2025-07-30 06:08:48.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4906
2025-07-30 06:08:48.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3152
2025-07-30 06:08:48.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4527
2025-07-30 06:08:48.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:08:48.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:08:48.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.552
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.491
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.315
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.453
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:08:48.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:08:48.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:08:48.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:08:49.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:08:50.350 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:08:50.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:08:51.612 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:08:52.353 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:08:52.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:08:53.586 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:08:54.192 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:08:54.790 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:08:54.790 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 06:08:54.790 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 06:08:54.790 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:08:54.798 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.34 ms, Average NMS time: 0.90 ms, Average inference time: 2.24 ms

2025-07-30 06:08:54.798 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:08:54.824 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:08:54.853 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch481
2025-07-30 06:08:56.551 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:31:28
2025-07-30 06:08:58.291 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.084s, 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: 352, ETA: 0:31:25
2025-07-30 06:08:59.993 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:31:23
2025-07-30 06:09:01.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:31:20
2025-07-30 06:09:03.623 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:31:17
2025-07-30 06:09:05.381 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 481/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:31:15
2025-07-30 06:09:06.171 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:09:06.229 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch482
2025-07-30 06:09:08.030 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:31:11
2025-07-30 06:09:09.836 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:31:08
2025-07-30 06:09:11.656 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:31:06
2025-07-30 06:09:13.380 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:31:03
2025-07-30 06:09:15.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:31:01
2025-07-30 06:09:17.032 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 482/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 12.4, iou_loss: 3.6, l1_loss: 1.6, conf_loss: 6.1, cls_loss: 1.1, lr: 5.000e-04, size: 448, ETA: 0:30:58
2025-07-30 06:09:17.813 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:09:17.849 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch483
2025-07-30 06:09:19.554 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:30:54
2025-07-30 06:09:21.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:30:52
2025-07-30 06:09:23.085 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:30:49
2025-07-30 06:09:24.940 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 12.8, iou_loss: 3.7, l1_loss: 1.4, conf_loss: 6.9, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:30:46
2025-07-30 06:09:26.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.092s, data_time: 0.006s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:30:44
2025-07-30 06:09:28.616 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 483/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 1.1, lr: 5.000e-04, size: 384, ETA: 0:30:41
2025-07-30 06:09:29.402 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:09:29.448 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch484
2025-07-30 06:09:31.250 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:30:37
2025-07-30 06:09:32.985 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:30:35
2025-07-30 06:09:34.693 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:30:32
2025-07-30 06:09:36.419 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:30:29
2025-07-30 06:09:38.258 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:30:27
2025-07-30 06:09:40.024 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 484/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:30:24
2025-07-30 06:09:40.807 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:09:40.864 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch485
2025-07-30 06:09:42.644 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:30:20
2025-07-30 06:09:44.385 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 3.1, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:30:18
2025-07-30 06:09:46.139 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:30:15
2025-07-30 06:09:47.865 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:30:13
2025-07-30 06:09:49.676 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:30:10
2025-07-30 06:09:51.440 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 485/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 3.7, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:30:07
2025-07-30 06:09:52.278 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:09:58.638 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:09:59.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:09:59.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5311
2025-07-30 06:09:59.895 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4595
2025-07-30 06:09:59.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2860
2025-07-30 06:09:59.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4255
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.531
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.459
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.286
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.426
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:09:59.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:09:59.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:09:59.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:09:59.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:09:59.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:09:59.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:10:00.520 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:10:01.065 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:10:01.612 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:10:02.187 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:10:02.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:10:03.252 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:10:03.879 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:10:04.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:10:05.051 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:10:05.052 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 06:10:05.052 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-30 06:10:05.052 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:10:05.061 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.33 ms, Average NMS time: 0.92 ms, Average inference time: 2.25 ms

2025-07-30 06:10:05.062 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:10:05.092 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:10:05.124 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch486
2025-07-30 06:10:06.826 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.7, l1_loss: 1.4, conf_loss: 3.6, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:30:04
2025-07-30 06:10:08.633 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:30:01
2025-07-30 06:10:10.463 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:29:58
2025-07-30 06:10:12.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.8, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:29:56
2025-07-30 06:10:13.987 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:29:53
2025-07-30 06:10:15.739 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 486/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 1.2, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:29:51
2025-07-30 06:10:16.588 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:10:16.622 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch487
2025-07-30 06:10:18.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:29:47
2025-07-30 06:10:20.068 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.081s, 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: 576, ETA: 0:29:44
2025-07-30 06:10:21.930 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:29:42
2025-07-30 06:10:23.713 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:29:39
2025-07-30 06:10:25.439 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.082s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:29:36
2025-07-30 06:10:27.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 487/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:29:34
2025-07-30 06:10:27.974 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:10:28.021 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch488
2025-07-30 06:10:29.812 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:29:30
2025-07-30 06:10:31.576 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:29:27
2025-07-30 06:10:33.386 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:29:25
2025-07-30 06:10:35.185 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:29:22
2025-07-30 06:10:36.948 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.084s, data_time: 0.003s, 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: 288, ETA: 0:29:20
2025-07-30 06:10:38.663 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 488/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:29:17
2025-07-30 06:10:39.491 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:10:39.544 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch489
2025-07-30 06:10:41.350 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:29:13
2025-07-30 06:10:43.123 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:29:11
2025-07-30 06:10:44.853 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 1.0, lr: 5.000e-04, size: 256, ETA: 0:29:08
2025-07-30 06:10:46.636 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 1.1, lr: 5.000e-04, size: 320, ETA: 0:29:05
2025-07-30 06:10:48.442 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:29:03
2025-07-30 06:10:50.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 489/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:29:00
2025-07-30 06:10:51.178 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:10:51.239 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch490
2025-07-30 06:10:52.996 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:28:57
2025-07-30 06:10:54.714 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.7, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 1.2, lr: 5.000e-04, size: 256, ETA: 0:28:54
2025-07-30 06:10:56.499 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:28:51
2025-07-30 06:10:58.233 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 8.6, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 3.9, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:28:49
2025-07-30 06:11:00.008 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:28:46
2025-07-30 06:11:01.799 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 490/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 9.3, iou_loss: 3.2, l1_loss: 0.9, conf_loss: 4.5, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:28:44
2025-07-30 06:11:02.601 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:11:08.907 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:11:09.962 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:11:10.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5091
2025-07-30 06:11:10.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4500
2025-07-30 06:11:10.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2548
2025-07-30 06:11:10.754 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4046
2025-07-30 06:11:10.754 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:11:10.754 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:11:10.754 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.509
2025-07-30 06:11:10.754 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.450
2025-07-30 06:11:10.754 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.255
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.405
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:11:10.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:11:11.585 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:11:12.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:11:13.189 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:11:14.003 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:11:14.776 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:11:15.598 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:11:16.376 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:11:17.186 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:11:18.003 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:11:18.003 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 06:11:18.003 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-07-30 06:11:18.003 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:11:18.011 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.31 ms, Average NMS time: 0.90 ms, Average inference time: 2.21 ms

2025-07-30 06:11:18.019 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:11:18.042 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:11:18.073 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch491
2025-07-30 06:11:19.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 1.7, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:28:40
2025-07-30 06:11:21.586 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:28:37
2025-07-30 06:11:23.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:28:35
2025-07-30 06:11:25.183 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:28:32
2025-07-30 06:11:26.927 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:28:29
2025-07-30 06:11:28.663 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 491/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:28:27
2025-07-30 06:11:29.464 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:11:29.503 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch492
2025-07-30 06:11:31.301 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 1.3, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:28:23
2025-07-30 06:11:33.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, 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: 448, ETA: 0:28:21
2025-07-30 06:11:34.934 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, 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: 576, ETA: 0:28:18
2025-07-30 06:11:36.764 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:28:15
2025-07-30 06:11:38.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 4.2, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:28:13
2025-07-30 06:11:40.356 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 492/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.6, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:28:10
2025-07-30 06:11:41.110 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:11:41.155 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch493
2025-07-30 06:11:42.922 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:28:07
2025-07-30 06:11:44.753 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:28:04
2025-07-30 06:11:46.528 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:28:01
2025-07-30 06:11:48.276 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:27:59
2025-07-30 06:11:50.220 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.094s, data_time: 0.003s, total_loss: 8.0, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 3.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:27:56
2025-07-30 06:11:52.006 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 493/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:27:54
2025-07-30 06:11:52.800 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:11:52.838 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch494
2025-07-30 06:11:54.541 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, 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: 480, ETA: 0:27:50
2025-07-30 06:11:56.276 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:27:47
2025-07-30 06:11:58.067 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 1.0, lr: 5.000e-04, size: 512, ETA: 0:27:45
2025-07-30 06:11:59.864 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:27:42
2025-07-30 06:12:01.712 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 8.4, iou_loss: 2.6, l1_loss: 1.4, conf_loss: 3.5, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:27:40
2025-07-30 06:12:03.480 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 494/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.7, iou_loss: 2.6, l1_loss: 1.8, conf_loss: 3.3, cls_loss: 1.0, lr: 5.000e-04, size: 576, ETA: 0:27:37
2025-07-30 06:12:04.277 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:12:04.319 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch495
2025-07-30 06:12:06.123 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 10.0, iou_loss: 2.1, l1_loss: 1.5, conf_loss: 5.2, cls_loss: 1.1, lr: 5.000e-04, size: 576, ETA: 0:27:33
2025-07-30 06:12:07.955 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:27:31
2025-07-30 06:12:09.693 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 3.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:27:28
2025-07-30 06:12:11.425 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, 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: 352, ETA: 0:27:26
2025-07-30 06:12:13.274 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:27:23
2025-07-30 06:12:14.997 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 495/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, 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: 352, ETA: 0:27:20
2025-07-30 06:12:15.846 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:12:22.072 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:12:22.988 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:12:23.393 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5606
2025-07-30 06:12:23.598 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5062
2025-07-30 06:12:23.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3400
2025-07-30 06:12:23.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4690
2025-07-30 06:12:23.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:12:23.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:12:23.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.561
2025-07-30 06:12:23.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.506
2025-07-30 06:12:23.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.340
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.469
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:12:23.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:12:24.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:12:24.745 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:12:25.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:12:25.818 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:12:26.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:12:26.858 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:12:27.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:12:27.906 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:12:28.464 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:12:28.464 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 06:12:28.464 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-30 06:12:28.464 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:12:28.471 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.34 ms, Average NMS time: 0.90 ms, Average inference time: 2.24 ms

2025-07-30 06:12:28.471 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:12:28.510 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:12:28.563 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch496
2025-07-30 06:12:30.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, 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: 448, ETA: 0:27:17
2025-07-30 06:12:32.166 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 1.5, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:27:14
2025-07-30 06:12:33.897 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.0, l1_loss: 1.1, conf_loss: 3.8, cls_loss: 1.0, lr: 5.000e-04, size: 256, ETA: 0:27:12
2025-07-30 06:12:35.653 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:27:09
2025-07-30 06:12:37.493 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, 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: 384, ETA: 0:27:06
2025-07-30 06:12:39.335 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 496/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 1.1, lr: 5.000e-04, size: 544, ETA: 0:27:04
2025-07-30 06:12:40.139 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:12:40.187 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch497
2025-07-30 06:12:41.984 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:27:00
2025-07-30 06:12:43.767 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 1.4, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:26:58
2025-07-30 06:12:45.572 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:26:55
2025-07-30 06:12:47.284 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, 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: 288, ETA: 0:26:52
2025-07-30 06:12:49.064 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.3, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 3.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:26:50
2025-07-30 06:12:50.861 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 497/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.1, l1_loss: 1.3, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:26:47
2025-07-30 06:12:51.681 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:12:51.716 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch498
2025-07-30 06:12:53.513 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:26:44
2025-07-30 06:12:55.244 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:26:41
2025-07-30 06:12:57.036 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:26:38
2025-07-30 06:12:58.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:26:36
2025-07-30 06:13:00.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:26:33
2025-07-30 06:13:02.488 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 498/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 3.4, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:26:31
2025-07-30 06:13:03.293 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:13:03.342 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch499
2025-07-30 06:13:05.123 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:26:27
2025-07-30 06:13:06.826 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:26:25
2025-07-30 06:13:08.627 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:26:22
2025-07-30 06:13:10.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 3.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:26:19
2025-07-30 06:13:12.285 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, 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: 0:26:17
2025-07-30 06:13:14.058 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 499/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 25.1, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 25.1, cls_loss: 0.0, lr: 5.000e-04, size: 480, ETA: 0:26:14
2025-07-30 06:13:14.925 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:13:14.965 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch500
2025-07-30 06:13:16.710 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, 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: 320, ETA: 0:26:11
2025-07-30 06:13:18.517 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:26:08
2025-07-30 06:13:20.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:26:06
2025-07-30 06:13:22.054 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:26:03
2025-07-30 06:13:23.847 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.8, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 4.4, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:26:00
2025-07-30 06:13:25.639 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 500/600, iter: 120/129, gpu mem: 1553Mb, 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: 0.6, lr: 5.000e-04, size: 544, ETA: 0:25:58
2025-07-30 06:13:26.467 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:13:32.845 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:13:33.638 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:13:34.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5795
2025-07-30 06:13:34.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5324
2025-07-30 06:13:34.256 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3598
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4906
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.580
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.532
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.360
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.491
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:13:34.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:13:34.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:13:34.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:13:34.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:13:34.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:13:34.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:13:34.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:13:34.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:13:35.588 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:13:36.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:13:36.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:13:37.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:13:38.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:13:38.729 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:13:39.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:13:39.986 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:13:39.986 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-30 06:13:39.986 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-07-30 06:13:39.986 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:13:39.993 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.92 ms, Average inference time: 2.26 ms

2025-07-30 06:13:39.994 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:13:40.019 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:13:40.048 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch501
2025-07-30 06:13:41.689 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, 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: 320, ETA: 0:25:54
2025-07-30 06:13:43.415 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:25:52
2025-07-30 06:13:45.218 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 1.4, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:25:49
2025-07-30 06:13:46.926 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 8.1, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:25:46
2025-07-30 06:13:48.719 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.4, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:25:44
2025-07-30 06:13:50.517 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 501/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:25:41
2025-07-30 06:13:51.289 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:13:51.324 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch502
2025-07-30 06:13:53.051 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:25:38
2025-07-30 06:13:54.782 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.3, l1_loss: 1.4, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:25:35
2025-07-30 06:13:56.560 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:25:33
2025-07-30 06:13:58.277 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:25:30
2025-07-30 06:14:00.057 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, 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: 0:25:27
2025-07-30 06:14:01.886 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 502/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:25:25
2025-07-30 06:14:02.615 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:14:02.651 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch503
2025-07-30 06:14:04.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, 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: 384, ETA: 0:25:21
2025-07-30 06:14:06.065 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 16.0, iou_loss: 3.7, l1_loss: 0.9, conf_loss: 10.6, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:25:19
2025-07-30 06:14:07.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 9.1, iou_loss: 3.1, l1_loss: 1.4, conf_loss: 3.7, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:25:16
2025-07-30 06:14:09.680 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:25:14
2025-07-30 06:14:11.454 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 7.6, iou_loss: 2.7, l1_loss: 1.3, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:25:11
2025-07-30 06:14:13.365 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 503/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.094s, 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: 448, ETA: 0:25:08
2025-07-30 06:14:14.135 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:14:14.176 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch504
2025-07-30 06:14:16.001 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:25:05
2025-07-30 06:14:17.758 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:25:02
2025-07-30 06:14:19.502 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:25:00
2025-07-30 06:14:21.335 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:24:57
2025-07-30 06:14:23.092 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.003s, 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: 544, ETA: 0:24:55
2025-07-30 06:14:24.873 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 504/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:24:52
2025-07-30 06:14:25.651 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:14:25.686 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch505
2025-07-30 06:14:27.352 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:24:48
2025-07-30 06:14:29.134 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:24:46
2025-07-30 06:14:30.871 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 1.0, lr: 5.000e-04, size: 512, ETA: 0:24:43
2025-07-30 06:14:32.662 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 1.3, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:24:41
2025-07-30 06:14:34.463 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:24:38
2025-07-30 06:14:36.160 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 505/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.1, iou_loss: 1.4, l1_loss: 0.6, conf_loss: 3.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:24:36
2025-07-30 06:14:36.903 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:14:43.076 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:14:44.036 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:14:44.608 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5482
2025-07-30 06:14:44.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4917
2025-07-30 06:14:44.835 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3011
2025-07-30 06:14:44.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4470
2025-07-30 06:14:44.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:14:44.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:14:44.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.548
2025-07-30 06:14:44.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.492
2025-07-30 06:14:44.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.301
2025-07-30 06:14:44.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.447
2025-07-30 06:14:44.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:14:44.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:14:44.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:14:44.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:14:44.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:14:44.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:14:44.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:14:44.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:14:44.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:14:45.600 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:14:46.316 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:14:47.065 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:14:47.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:14:48.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:14:49.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:14:49.988 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:14:50.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:14:51.409 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:14:51.409 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 06:14:51.409 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 06:14:51.410 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:14:51.418 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.90 ms, Average inference time: 2.29 ms

2025-07-30 06:14:51.418 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:14:51.496 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:14:51.528 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch506
2025-07-30 06:14:53.302 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:24:32
2025-07-30 06:14:55.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 3.4, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:24:29
2025-07-30 06:14:56.747 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:24:27
2025-07-30 06:14:58.444 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:24:24
2025-07-30 06:15:00.214 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:24:22
2025-07-30 06:15:01.982 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 506/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:24:19
2025-07-30 06:15:02.752 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:15:02.786 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch507
2025-07-30 06:15:04.483 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:24:16
2025-07-30 06:15:06.279 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:24:13
2025-07-30 06:15:08.061 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:24:10
2025-07-30 06:15:09.804 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 8.0, iou_loss: 2.8, l1_loss: 1.5, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:24:08
2025-07-30 06:15:11.611 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:24:05
2025-07-30 06:15:13.425 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 507/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, 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: 576, ETA: 0:24:03
2025-07-30 06:15:14.243 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:15:14.302 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch508
2025-07-30 06:15:16.033 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:23:59
2025-07-30 06:15:17.793 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:23:57
2025-07-30 06:15:19.527 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 10.0, iou_loss: 3.0, l1_loss: 1.3, conf_loss: 4.9, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:23:54
2025-07-30 06:15:21.375 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:23:52
2025-07-30 06:15:23.095 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 1.3, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:23:49
2025-07-30 06:15:24.917 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 508/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:23:47
2025-07-30 06:15:25.779 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:15:25.825 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch509
2025-07-30 06:15:27.521 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:23:43
2025-07-30 06:15:29.331 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 4.1, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:23:40
2025-07-30 06:15:31.107 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:23:38
2025-07-30 06:15:32.832 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:23:35
2025-07-30 06:15:34.630 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:23:33
2025-07-30 06:15:36.402 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 509/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:23:30
2025-07-30 06:15:37.232 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:15:37.284 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch510
2025-07-30 06:15:38.952 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 9.1, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 4.6, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:23:27
2025-07-30 06:15:40.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 3.5, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:23:24
2025-07-30 06:15:42.727 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 3.2, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:23:22
2025-07-30 06:15:44.552 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, 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: 480, ETA: 0:23:19
2025-07-30 06:15:46.359 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 100/129, gpu mem: 1553Mb, 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: 480, ETA: 0:23:17
2025-07-30 06:15:48.121 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 510/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.001s, 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: 448, ETA: 0:23:14
2025-07-30 06:15:48.912 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:15:55.237 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:15:56.123 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:15:56.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5836
2025-07-30 06:15:56.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5003
2025-07-30 06:15:56.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3173
2025-07-30 06:15:56.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4671
2025-07-30 06:15:56.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.584
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.500
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.317
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.467
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:15:56.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:15:56.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:15:56.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:15:57.607 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:15:58.342 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:15:59.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:15:59.774 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:16:00.464 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:16:01.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:16:01.888 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:16:02.586 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:16:03.314 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:16:03.314 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 06:16:03.315 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-30 06:16:03.315 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:16:03.321 | 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: 2.32 ms

2025-07-30 06:16:03.322 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:16:03.347 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:16:03.377 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch511
2025-07-30 06:16:05.053 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:23:10
2025-07-30 06:16:06.781 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 3.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:23:08
2025-07-30 06:16:08.521 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:23:05
2025-07-30 06:16:10.393 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 10.1, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 5.3, cls_loss: 1.1, lr: 5.000e-04, size: 384, ETA: 0:23:03
2025-07-30 06:16:12.159 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:23:00
2025-07-30 06:16:13.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 511/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:22:58
2025-07-30 06:16:14.763 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:16:14.801 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch512
2025-07-30 06:16:16.552 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:22:54
2025-07-30 06:16:18.276 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 9.5, iou_loss: 3.0, l1_loss: 1.2, conf_loss: 4.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:22:52
2025-07-30 06:16:19.979 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:22:49
2025-07-30 06:16:21.762 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:22:47
2025-07-30 06:16:23.564 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:22:44
2025-07-30 06:16:25.275 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 512/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:22:42
2025-07-30 06:16:26.050 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:16:26.102 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch513
2025-07-30 06:16:27.814 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:22:38
2025-07-30 06:16:29.627 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:22:35
2025-07-30 06:16:31.266 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 35.4, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 35.4, cls_loss: 0.0, lr: 5.000e-04, size: 512, ETA: 0:22:33
2025-07-30 06:16:33.055 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:22:30
2025-07-30 06:16:34.759 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:22:28
2025-07-30 06:16:36.449 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 513/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:22:25
2025-07-30 06:16:37.256 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:16:37.294 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch514
2025-07-30 06:16:39.124 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 20/129, gpu mem: 1553Mb, 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: 0.7, lr: 5.000e-04, size: 544, ETA: 0:22:22
2025-07-30 06:16:40.894 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 3.3, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:22:19
2025-07-30 06:16:42.634 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:22:17
2025-07-30 06:16:44.424 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 1.5, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:22:14
2025-07-30 06:16:46.264 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 1.5, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:22:12
2025-07-30 06:16:48.024 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 514/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, 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: 0:22:09
2025-07-30 06:16:48.818 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:16:48.864 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch515
2025-07-30 06:16:50.535 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:22:05
2025-07-30 06:16:52.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:22:03
2025-07-30 06:16:54.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.3, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:22:00
2025-07-30 06:16:55.789 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:21:58
2025-07-30 06:16:57.534 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:21:55
2025-07-30 06:16:59.294 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 515/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:21:53
2025-07-30 06:17:00.095 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:17:06.431 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:17:07.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:17:07.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5698
2025-07-30 06:17:07.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5195
2025-07-30 06:17:07.735 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3298
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4730
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.570
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.519
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.330
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.473
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:17:07.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:17:07.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:17:07.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:17:07.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:17:07.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:17:07.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:17:07.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:17:08.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:17:08.895 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:17:09.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:17:10.012 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:17:10.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:17:11.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:17:11.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:17:12.219 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:17:12.759 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:17:12.759 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 06:17:12.760 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-30 06:17:12.760 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:17:12.767 | 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: 2.37 ms

2025-07-30 06:17:12.767 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:17:12.793 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:17:12.821 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch516
2025-07-30 06:17:14.486 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:21:49
2025-07-30 06:17:16.278 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:21:47
2025-07-30 06:17:18.110 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:21:44
2025-07-30 06:17:19.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:21:42
2025-07-30 06:17:21.774 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:21:39
2025-07-30 06:17:23.549 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 516/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, 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: 320, ETA: 0:21:37
2025-07-30 06:17:24.295 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:17:24.342 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch517
2025-07-30 06:17:26.014 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:21:33
2025-07-30 06:17:27.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:21:31
2025-07-30 06:17:29.655 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.5, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:21:28
2025-07-30 06:17:31.530 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.093s, data_time: 0.006s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:21:26
2025-07-30 06:17:33.313 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.7, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:21:23
2025-07-30 06:17:35.013 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 517/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:21:21
2025-07-30 06:17:35.815 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:17:35.851 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch518
2025-07-30 06:17:37.537 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 4.7, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:21:17
2025-07-30 06:17:39.366 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.7, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:21:14
2025-07-30 06:17:41.147 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:21:12
2025-07-30 06:17:42.914 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:21:09
2025-07-30 06:17:44.683 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:21:07
2025-07-30 06:17:46.431 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 518/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:21:04
2025-07-30 06:17:47.261 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:17:47.301 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch519
2025-07-30 06:17:49.068 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.9, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:21:01
2025-07-30 06:17:50.870 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:20:58
2025-07-30 06:17:52.647 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:20:56
2025-07-30 06:17:54.423 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:20:53
2025-07-30 06:17:56.153 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, 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: 0:20:51
2025-07-30 06:17:57.991 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 519/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:20:48
2025-07-30 06:17:58.773 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:17:58.818 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch520
2025-07-30 06:18:00.522 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.4, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:20:45
2025-07-30 06:18:02.371 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.9, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:20:42
2025-07-30 06:18:04.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:20:40
2025-07-30 06:18:05.810 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 1.4, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:20:37
2025-07-30 06:18:07.556 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, 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: 320, ETA: 0:20:35
2025-07-30 06:18:09.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 520/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:20:32
2025-07-30 06:18:10.055 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:18:16.310 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:18:17.204 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:18:17.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5454
2025-07-30 06:18:17.885 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4988
2025-07-30 06:18:17.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2931
2025-07-30 06:18:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4458
2025-07-30 06:18:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:18:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:18:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.545
2025-07-30 06:18:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.499
2025-07-30 06:18:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.293
2025-07-30 06:18:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.446
2025-07-30 06:18:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:18:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:18:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:18:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:18:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:18:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:18:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:18:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:18:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:18:18.616 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:18:19.333 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:18:20.019 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:18:20.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:18:21.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:18:22.069 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:18:22.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:18:23.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:18:24.115 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:18:24.115 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-07-30 06:18:24.116 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-07-30 06:18:24.116 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:18:24.123 | 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: 2.32 ms

2025-07-30 06:18:24.124 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:18:24.144 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:18:24.174 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch521
2025-07-30 06:18:25.820 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:20:29
2025-07-30 06:18:27.532 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 1.1, lr: 5.000e-04, size: 288, ETA: 0:20:26
2025-07-30 06:18:29.266 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:20:24
2025-07-30 06:18:31.025 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.003s, 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: 256, ETA: 0:20:21
2025-07-30 06:18:32.792 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, 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: 448, ETA: 0:20:19
2025-07-30 06:18:34.551 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 521/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:20:16
2025-07-30 06:18:35.308 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:18:35.372 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch522
2025-07-30 06:18:37.060 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:20:13
2025-07-30 06:18:38.883 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 40/129, gpu mem: 1553Mb, 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: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:20:10
2025-07-30 06:18:40.730 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:20:08
2025-07-30 06:18:42.553 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:20:05
2025-07-30 06:18:44.326 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:20:03
2025-07-30 06:18:46.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 522/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:20:00
2025-07-30 06:18:46.963 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:18:47.071 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch523
2025-07-30 06:18:48.805 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:19:57
2025-07-30 06:18:50.587 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:19:54
2025-07-30 06:18:52.409 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:19:52
2025-07-30 06:18:54.291 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:19:49
2025-07-30 06:18:56.059 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 1.1, lr: 5.000e-04, size: 320, ETA: 0:19:47
2025-07-30 06:18:58.041 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 523/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.097s, 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: 256, ETA: 0:19:44
2025-07-30 06:18:58.844 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:18:58.896 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch524
2025-07-30 06:19:00.788 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 9.2, iou_loss: 2.8, l1_loss: 1.5, conf_loss: 4.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:19:41
2025-07-30 06:19:02.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.094s, data_time: 0.003s, total_loss: 5.3, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:19:38
2025-07-30 06:19:04.620 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:19:36
2025-07-30 06:19:06.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.005s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:19:33
2025-07-30 06:19:08.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:19:31
2025-07-30 06:19:10.206 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 524/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:19:28
2025-07-30 06:19:11.024 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:19:11.064 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch525
2025-07-30 06:19:12.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 1.0, lr: 5.000e-04, size: 416, ETA: 0:19:25
2025-07-30 06:19:14.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, 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: 0.6, lr: 5.000e-04, size: 448, ETA: 0:19:22
2025-07-30 06:19:16.573 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:19:20
2025-07-30 06:19:18.563 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.098s, data_time: 0.003s, total_loss: 6.8, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:19:17
2025-07-30 06:19:20.370 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:19:15
2025-07-30 06:19:22.131 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 525/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:19:12
2025-07-30 06:19:22.943 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:19:29.286 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:19:30.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:19:30.776 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5433
2025-07-30 06:19:30.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4816
2025-07-30 06:19:30.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3000
2025-07-30 06:19:30.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4417
2025-07-30 06:19:30.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:19:30.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:19:30.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.543
2025-07-30 06:19:30.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.482
2025-07-30 06:19:30.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.300
2025-07-30 06:19:30.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.442
2025-07-30 06:19:30.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:19:30.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:19:30.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:19:30.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:19:30.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:19:30.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:19:30.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:19:30.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:19:30.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:19:31.701 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:19:32.454 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:19:33.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:19:33.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:19:34.606 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:19:35.325 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:19:36.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:19:36.840 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:19:37.569 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:19:37.570 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 06:19:37.570 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-07-30 06:19:37.570 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:19:37.577 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.33 ms, Average NMS time: 0.91 ms, Average inference time: 2.24 ms

2025-07-30 06:19:37.577 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:19:37.599 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:19:37.631 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch526
2025-07-30 06:19:39.346 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:19:09
2025-07-30 06:19:41.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:19:06
2025-07-30 06:19:42.922 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 60/129, gpu mem: 1553Mb, 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: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:19:04
2025-07-30 06:19:44.665 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 80/129, gpu mem: 1553Mb, 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: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:19:01
2025-07-30 06:19:46.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:18:59
2025-07-30 06:19:48.238 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 526/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:18:56
2025-07-30 06:19:49.034 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:19:49.082 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch527
2025-07-30 06:19:50.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:18:53
2025-07-30 06:19:52.638 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 1.6, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:18:50
2025-07-30 06:19:54.449 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 6.2, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:18:48
2025-07-30 06:19:56.190 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 1.5, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:18:45
2025-07-30 06:19:57.943 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:18:43
2025-07-30 06:19:59.743 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 527/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:18:40
2025-07-30 06:20:00.554 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:20:00.588 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch528
2025-07-30 06:20:02.278 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 9.7, iou_loss: 2.8, l1_loss: 0.7, conf_loss: 5.1, cls_loss: 1.1, lr: 5.000e-04, size: 512, ETA: 0:18:37
2025-07-30 06:20:04.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:18:34
2025-07-30 06:20:05.800 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, 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: 448, ETA: 0:18:32
2025-07-30 06:20:07.571 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:18:29
2025-07-30 06:20:09.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:18:27
2025-07-30 06:20:11.163 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 528/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 1.9, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:18:25
2025-07-30 06:20:11.918 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:20:11.974 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch529
2025-07-30 06:20:13.671 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:18:21
2025-07-30 06:20:15.491 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.6, l1_loss: 1.5, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:18:18
2025-07-30 06:20:17.386 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 8.7, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 4.0, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:18:16
2025-07-30 06:20:19.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:18:14
2025-07-30 06:20:20.954 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:18:11
2025-07-30 06:20:22.664 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 529/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, 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: 352, ETA: 0:18:09
2025-07-30 06:20:23.429 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:20:23.464 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch530
2025-07-30 06:20:25.212 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:18:05
2025-07-30 06:20:26.980 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:18:03
2025-07-30 06:20:28.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 9.3, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 4.6, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:18:00
2025-07-30 06:20:30.636 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:17:58
2025-07-30 06:20:32.372 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.001s, 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: 256, ETA: 0:17:55
2025-07-30 06:20:34.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 530/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:17:53
2025-07-30 06:20:34.939 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:20:41.177 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:20:42.069 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:20:42.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5918
2025-07-30 06:20:42.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5338
2025-07-30 06:20:42.759 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3609
2025-07-30 06:20:42.759 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4955
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.592
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.534
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.361
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.496
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:20:42.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:20:42.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:20:42.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:20:42.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:20:42.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:20:43.587 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:20:44.263 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:20:44.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:20:45.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:20:46.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:20:47.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:20:47.766 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:20:48.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:20:49.131 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:20:49.131 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-30 06:20:49.131 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-30 06:20:49.131 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:20:49.138 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.90 ms, Average inference time: 2.27 ms

2025-07-30 06:20:49.139 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:20:49.163 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:20:49.192 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch531
2025-07-30 06:20:50.878 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:17:49
2025-07-30 06:20:52.622 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:17:47
2025-07-30 06:20:54.338 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 60/129, gpu mem: 1553Mb, 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: 512, ETA: 0:17:44
2025-07-30 06:20:56.148 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:17:42
2025-07-30 06:20:57.866 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:17:39
2025-07-30 06:20:59.739 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 531/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 1.5, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:17:37
2025-07-30 06:21:00.464 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:21:00.511 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch532
2025-07-30 06:21:02.227 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:17:33
2025-07-30 06:21:04.013 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:17:31
2025-07-30 06:21:05.764 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 1.1, lr: 5.000e-04, size: 352, ETA: 0:17:28
2025-07-30 06:21:07.565 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:17:26
2025-07-30 06:21:09.315 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:17:23
2025-07-30 06:21:11.040 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 532/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:17:21
2025-07-30 06:21:11.833 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:21:11.882 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch533
2025-07-30 06:21:13.596 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, 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: 480, ETA: 0:17:17
2025-07-30 06:21:15.405 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.001s, 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: 288, ETA: 0:17:15
2025-07-30 06:21:17.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:17:12
2025-07-30 06:21:18.963 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:17:10
2025-07-30 06:21:20.753 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:17:08
2025-07-30 06:21:22.494 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 533/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, 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: 352, ETA: 0:17:05
2025-07-30 06:21:23.306 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:21:23.349 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch534
2025-07-30 06:21:25.157 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:17:02
2025-07-30 06:21:26.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.1, l1_loss: 1.2, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:16:59
2025-07-30 06:21:28.684 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:16:57
2025-07-30 06:21:30.442 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, 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: 384, ETA: 0:16:54
2025-07-30 06:21:32.241 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:16:52
2025-07-30 06:21:34.011 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 534/600, iter: 120/129, gpu mem: 1553Mb, 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: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:16:49
2025-07-30 06:21:34.831 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:21:34.872 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch535
2025-07-30 06:21:36.610 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:16:46
2025-07-30 06:21:38.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:16:43
2025-07-30 06:21:40.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:16:41
2025-07-30 06:21:42.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, 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: 416, ETA: 0:16:38
2025-07-30 06:21:43.795 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 3.6, cls_loss: 1.0, lr: 5.000e-04, size: 256, ETA: 0:16:36
2025-07-30 06:21:45.589 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 535/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:16:34
2025-07-30 06:21:46.347 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:21:52.530 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:21:53.472 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:21:53.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5799
2025-07-30 06:21:54.129 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5258
2025-07-30 06:21:54.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3414
2025-07-30 06:21:54.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4824
2025-07-30 06:21:54.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:21:54.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:21:54.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.580
2025-07-30 06:21:54.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.526
2025-07-30 06:21:54.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.341
2025-07-30 06:21:54.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.482
2025-07-30 06:21:54.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:21:54.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:21:54.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:21:54.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:21:54.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:21:54.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:21:54.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:21:54.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:21:54.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:21:54.892 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:21:55.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:21:56.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:21:56.943 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:21:57.612 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:21:58.318 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:21:58.993 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:21:59.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:22:00.365 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:22:00.365 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-30 06:22:00.365 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-30 06:22:00.365 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:22:00.372 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.91 ms, Average inference time: 2.28 ms

2025-07-30 06:22:00.373 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:22:00.397 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:22:00.427 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch536
2025-07-30 06:22:02.143 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:16:30
2025-07-30 06:22:03.882 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:16:28
2025-07-30 06:22:05.673 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:16:25
2025-07-30 06:22:07.554 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.091s, 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: 256, ETA: 0:16:23
2025-07-30 06:22:09.296 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:16:20
2025-07-30 06:22:11.161 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 536/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 1.0, lr: 5.000e-04, size: 320, ETA: 0:16:18
2025-07-30 06:22:11.950 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:22:11.994 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch537
2025-07-30 06:22:13.776 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 9.1, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 4.8, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:16:14
2025-07-30 06:22:15.585 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, 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: 384, ETA: 0:16:12
2025-07-30 06:22:17.394 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:16:09
2025-07-30 06:22:19.131 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:16:07
2025-07-30 06:22:20.920 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:16:04
2025-07-30 06:22:22.640 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 537/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:16:02
2025-07-30 06:22:23.442 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:22:23.480 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch538
2025-07-30 06:22:25.232 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:15:58
2025-07-30 06:22:27.005 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:15:56
2025-07-30 06:22:28.844 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:15:54
2025-07-30 06:22:30.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.006s, 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: 320, ETA: 0:15:51
2025-07-30 06:22:32.425 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:15:49
2025-07-30 06:22:34.213 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 538/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, 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: 480, ETA: 0:15:46
2025-07-30 06:22:35.044 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:22:35.076 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch539
2025-07-30 06:22:36.834 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 1.2, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:15:43
2025-07-30 06:22:38.569 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:15:40
2025-07-30 06:22:40.324 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:15:38
2025-07-30 06:22:42.109 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:15:35
2025-07-30 06:22:43.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:15:33
2025-07-30 06:22:45.703 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 539/600, iter: 120/129, gpu mem: 1553Mb, 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: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:15:31
2025-07-30 06:22:46.519 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:22:46.556 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch540
2025-07-30 06:22:48.274 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:15:27
2025-07-30 06:22:50.032 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, 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: 256, ETA: 0:15:25
2025-07-30 06:22:51.767 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:15:22
2025-07-30 06:22:53.550 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 3.3, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:15:20
2025-07-30 06:22:55.322 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:15:17
2025-07-30 06:22:57.016 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 540/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:15:15
2025-07-30 06:22:57.841 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:23:04.146 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:23:04.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:23:05.310 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5607
2025-07-30 06:23:05.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4885
2025-07-30 06:23:05.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3238
2025-07-30 06:23:05.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4577
2025-07-30 06:23:05.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:23:05.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:23:05.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.561
2025-07-30 06:23:05.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.488
2025-07-30 06:23:05.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.324
2025-07-30 06:23:05.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.458
2025-07-30 06:23:05.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:23:05.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:23:05.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:23:05.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:23:05.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:23:05.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:23:05.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:23:05.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:23:05.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:23:06.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:23:06.565 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:23:07.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:23:07.661 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:23:08.242 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:23:08.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:23:09.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:23:09.866 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:23:10.398 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:23:10.398 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-07-30 06:23:10.398 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-07-30 06:23:10.398 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:23:10.405 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.40 ms, Average NMS time: 0.94 ms, Average inference time: 2.34 ms

2025-07-30 06:23:10.406 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:23:10.474 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:23:10.506 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch541
2025-07-30 06:23:12.191 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:15:11
2025-07-30 06:23:13.966 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:15:09
2025-07-30 06:23:15.837 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:15:06
2025-07-30 06:23:17.561 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.0, l1_loss: 1.2, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:15:04
2025-07-30 06:23:19.354 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:15:02
2025-07-30 06:23:21.171 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 541/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:14:59
2025-07-30 06:23:21.965 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:23:22.004 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch542
2025-07-30 06:23:23.781 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 2.4, cls_loss: 1.0, lr: 5.000e-04, size: 288, ETA: 0:14:56
2025-07-30 06:23:25.565 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 40/129, gpu mem: 1553Mb, 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: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:14:53
2025-07-30 06:23:27.397 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 3.6, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:14:51
2025-07-30 06:23:29.122 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:14:48
2025-07-30 06:23:30.914 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 8.0, iou_loss: 2.6, l1_loss: 1.5, conf_loss: 3.0, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:14:46
2025-07-30 06:23:32.669 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 542/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:14:43
2025-07-30 06:23:33.457 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:23:33.497 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch543
2025-07-30 06:23:35.203 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 1.0, lr: 5.000e-04, size: 320, ETA: 0:14:40
2025-07-30 06:23:36.958 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:14:37
2025-07-30 06:23:38.779 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:14:35
2025-07-30 06:23:40.459 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:14:33
2025-07-30 06:23:42.320 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.3, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:14:30
2025-07-30 06:23:44.110 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 543/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:14:28
2025-07-30 06:23:44.948 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:23:44.982 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch544
2025-07-30 06:23:46.717 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:14:24
2025-07-30 06:23:48.530 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, 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: 256, ETA: 0:14:22
2025-07-30 06:23:50.242 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:14:19
2025-07-30 06:23:52.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 80/129, gpu mem: 1553Mb, 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: 0.6, lr: 5.000e-04, size: 352, ETA: 0:14:17
2025-07-30 06:23:53.817 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 1.3, lr: 5.000e-04, size: 480, ETA: 0:14:15
2025-07-30 06:23:55.601 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 544/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:14:12
2025-07-30 06:23:56.393 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:23:56.432 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch545
2025-07-30 06:23:58.259 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 1.0, conf_loss: 1.5, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:14:09
2025-07-30 06:24:00.091 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, 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: 384, ETA: 0:14:06
2025-07-30 06:24:01.908 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:14:04
2025-07-30 06:24:03.603 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:14:01
2025-07-30 06:24:05.323 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:13:59
2025-07-30 06:24:07.096 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 545/600, iter: 120/129, gpu mem: 1553Mb, 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: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:13:56
2025-07-30 06:24:07.829 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:24:14.145 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:24:15.142 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:24:15.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5718
2025-07-30 06:24:15.815 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4976
2025-07-30 06:24:15.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3393
2025-07-30 06:24:15.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4696
2025-07-30 06:24:15.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:24:15.860 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.572
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.498
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.339
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.470
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:24:15.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:24:15.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:24:16.707 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:24:17.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:24:18.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:24:18.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:24:19.682 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:24:20.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:24:21.186 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:24:21.935 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:24:22.644 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:24:22.644 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 06:24:22.644 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-07-30 06:24:22.644 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:24:22.651 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.91 ms, Average inference time: 2.28 ms

2025-07-30 06:24:22.652 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:24:22.695 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:24:22.739 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch546
2025-07-30 06:24:24.474 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:13:53
2025-07-30 06:24:26.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 9.9, iou_loss: 2.9, l1_loss: 1.7, conf_loss: 4.5, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:13:51
2025-07-30 06:24:27.983 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:13:48
2025-07-30 06:24:29.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:13:46
2025-07-30 06:24:31.505 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:13:43
2025-07-30 06:24:33.200 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 546/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 1.4, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:13:41
2025-07-30 06:24:33.973 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:24:34.034 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch547
2025-07-30 06:24:35.861 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 9.1, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 4.1, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:13:37
2025-07-30 06:24:37.625 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:13:35
2025-07-30 06:24:39.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:13:33
2025-07-30 06:24:41.244 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 4.6, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:13:30
2025-07-30 06:24:42.953 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 3.5, cls_loss: 1.0, lr: 5.000e-04, size: 416, ETA: 0:13:28
2025-07-30 06:24:44.699 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 547/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:13:25
2025-07-30 06:24:45.473 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:24:45.509 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch548
2025-07-30 06:24:47.348 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:13:22
2025-07-30 06:24:49.179 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.6, l1_loss: 1.4, conf_loss: 3.4, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:13:19
2025-07-30 06:24:51.063 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 3.7, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:13:17
2025-07-30 06:24:52.773 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:13:15
2025-07-30 06:24:54.572 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:13:12
2025-07-30 06:24:56.314 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 548/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:13:10
2025-07-30 06:24:57.099 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:24:57.134 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch549
2025-07-30 06:24:58.877 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:13:06
2025-07-30 06:25:00.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, 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: 480, ETA: 0:13:04
2025-07-30 06:25:02.516 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.003s, 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: 448, ETA: 0:13:01
2025-07-30 06:25:04.289 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:12:59
2025-07-30 06:25:06.023 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:12:57
2025-07-30 06:25:07.879 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 549/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:12:54
2025-07-30 06:25:08.658 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:25:08.693 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch550
2025-07-30 06:25:10.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 20/129, gpu mem: 1553Mb, 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: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:12:51
2025-07-30 06:25:12.089 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 1.0, lr: 5.000e-04, size: 256, ETA: 0:12:48
2025-07-30 06:25:13.905 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.006s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:12:46
2025-07-30 06:25:15.699 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:12:43
2025-07-30 06:25:17.436 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:12:41
2025-07-30 06:25:19.158 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 550/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 3.1, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:12:39
2025-07-30 06:25:19.923 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:25:26.184 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:25:27.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:25:27.773 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5902
2025-07-30 06:25:27.886 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5117
2025-07-30 06:25:27.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3866
2025-07-30 06:25:27.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4962
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.590
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.512
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.387
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.496
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:25:27.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:25:27.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:25:27.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:25:27.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:25:27.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:25:27.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:25:28.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:25:29.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:25:30.351 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:25:31.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:25:32.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:25:32.946 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:25:33.781 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:25:34.657 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:25:35.497 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:25:35.498 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-30 06:25:35.498 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-30 06:25:35.498 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:25:35.505 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.91 ms, Average inference time: 2.28 ms

2025-07-30 06:25:35.506 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:25:35.531 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:25:35.563 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch551
2025-07-30 06:25:37.189 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.078s, data_time: 0.001s, total_loss: 4.9, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:12:35
2025-07-30 06:25:38.988 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:12:33
2025-07-30 06:25:40.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 5.2, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:12:30
2025-07-30 06:25:42.526 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 80/129, gpu mem: 1553Mb, 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: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:12:28
2025-07-30 06:25:44.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 8.4, iou_loss: 2.3, l1_loss: 1.3, conf_loss: 3.8, cls_loss: 1.0, lr: 5.000e-04, size: 448, ETA: 0:12:25
2025-07-30 06:25:46.009 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 551/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:12:23
2025-07-30 06:25:46.788 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:25:46.829 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch552
2025-07-30 06:25:48.586 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:12:20
2025-07-30 06:25:50.304 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 8.0, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 1.1, lr: 5.000e-04, size: 288, ETA: 0:12:17
2025-07-30 06:25:52.112 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:12:15
2025-07-30 06:25:53.856 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:12:12
2025-07-30 06:25:55.629 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 9.2, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 4.3, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:12:10
2025-07-30 06:25:57.345 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 552/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:12:08
2025-07-30 06:25:58.144 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:25:58.189 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch553
2025-07-30 06:25:59.948 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:12:04
2025-07-30 06:26:01.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:12:02
2025-07-30 06:26:03.584 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:11:59
2025-07-30 06:26:05.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.1, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:11:57
2025-07-30 06:26:07.196 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:11:54
2025-07-30 06:26:08.911 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 553/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:11:52
2025-07-30 06:26:09.660 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:26:09.694 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch554
2025-07-30 06:26:11.492 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, 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: 0:11:49
2025-07-30 06:26:13.216 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.4, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:11:46
2025-07-30 06:26:15.113 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.091s, data_time: 0.006s, total_loss: 5.4, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:11:44
2025-07-30 06:26:16.911 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, 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: 544, ETA: 0:11:41
2025-07-30 06:26:18.643 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, 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: 512, ETA: 0:11:39
2025-07-30 06:26:20.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 554/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:11:37
2025-07-30 06:26:21.206 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:26:21.256 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch555
2025-07-30 06:26:23.043 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:11:33
2025-07-30 06:26:24.886 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:11:31
2025-07-30 06:26:26.757 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 4.5, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:11:28
2025-07-30 06:26:28.569 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.2, l1_loss: 0.7, conf_loss: 2.7, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:11:26
2025-07-30 06:26:30.335 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, 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: 448, ETA: 0:11:24
2025-07-30 06:26:32.091 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 555/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:11:21
2025-07-30 06:26:32.899 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:26:39.201 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:26:40.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:26:40.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5462
2025-07-30 06:26:40.818 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4420
2025-07-30 06:26:40.897 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3101
2025-07-30 06:26:40.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4328
2025-07-30 06:26:40.898 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:26:40.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:26:40.899 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.546
2025-07-30 06:26:40.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.442
2025-07-30 06:26:40.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.310
2025-07-30 06:26:40.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.433
2025-07-30 06:26:40.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:26:40.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:26:40.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:26:40.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:26:40.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:26:40.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:26:40.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:26:40.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:26:40.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:26:41.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:26:42.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:26:43.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:26:43.905 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:26:44.659 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:26:45.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:26:46.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:26:46.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:26:47.580 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:26:47.580 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-07-30 06:26:47.580 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-07-30 06:26:47.580 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:26:47.587 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.35 ms, Average NMS time: 0.91 ms, Average inference time: 2.26 ms

2025-07-30 06:26:47.588 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:26:47.613 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:26:47.650 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch556
2025-07-30 06:26:49.387 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:11:18
2025-07-30 06:26:51.192 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, 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: 384, ETA: 0:11:15
2025-07-30 06:26:53.051 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:11:13
2025-07-30 06:26:54.839 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 1.0, lr: 5.000e-04, size: 288, ETA: 0:11:10
2025-07-30 06:26:56.582 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 1.3, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:11:08
2025-07-30 06:26:58.367 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 556/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:11:06
2025-07-30 06:26:59.181 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:26:59.230 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch557
2025-07-30 06:27:01.074 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:11:02
2025-07-30 06:27:02.877 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.9, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 4.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:11:00
2025-07-30 06:27:04.719 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:10:57
2025-07-30 06:27:06.615 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:10:55
2025-07-30 06:27:08.319 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, 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: 288, ETA: 0:10:53
2025-07-30 06:27:09.975 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 557/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:10:50
2025-07-30 06:27:10.768 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:27:10.811 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch558
2025-07-30 06:27:12.562 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 10.0, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 5.1, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:10:47
2025-07-30 06:27:14.343 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:10:44
2025-07-30 06:27:16.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:10:42
2025-07-30 06:27:17.883 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 3.1, cls_loss: 1.2, lr: 5.000e-04, size: 448, ETA: 0:10:40
2025-07-30 06:27:19.646 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:10:37
2025-07-30 06:27:21.407 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 558/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, 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: 352, ETA: 0:10:35
2025-07-30 06:27:22.170 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:27:22.209 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch559
2025-07-30 06:27:23.969 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:10:31
2025-07-30 06:27:25.695 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.0, l1_loss: 1.1, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:10:29
2025-07-30 06:27:27.450 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.003s, 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: 352, ETA: 0:10:27
2025-07-30 06:27:29.135 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 1.1, lr: 5.000e-04, size: 576, ETA: 0:10:24
2025-07-30 06:27:30.939 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, 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: 288, ETA: 0:10:22
2025-07-30 06:27:32.710 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 559/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 9.1, iou_loss: 2.6, l1_loss: 0.7, conf_loss: 4.9, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:10:19
2025-07-30 06:27:33.517 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:27:33.559 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch560
2025-07-30 06:27:35.308 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:10:16
2025-07-30 06:27:37.118 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, 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: 480, ETA: 0:10:14
2025-07-30 06:27:38.966 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:10:11
2025-07-30 06:27:40.748 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:10:09
2025-07-30 06:27:42.507 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.2, l1_loss: 0.4, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:10:06
2025-07-30 06:27:44.303 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 560/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:10:04
2025-07-30 06:27:45.060 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:27:51.429 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:27:52.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:27:52.729 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6031
2025-07-30 06:27:52.883 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5285
2025-07-30 06:27:52.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3563
2025-07-30 06:27:52.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4959
2025-07-30 06:27:52.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:27:52.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:27:52.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.603
2025-07-30 06:27:52.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.528
2025-07-30 06:27:52.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.356
2025-07-30 06:27:52.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.496
2025-07-30 06:27:52.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:27:52.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:27:52.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:27:52.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:27:52.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:27:52.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:27:52.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:27:52.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:27:52.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:27:53.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:27:54.263 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:27:54.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:27:55.576 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:27:56.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:27:56.845 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:27:57.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:27:58.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:27:58.776 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:27:58.776 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-30 06:27:58.776 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-30 06:27:58.776 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:27:58.784 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.32 ms, Average NMS time: 0.89 ms, Average inference time: 2.21 ms

2025-07-30 06:27:58.784 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:27:58.808 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:27:58.837 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch561
2025-07-30 06:28:00.468 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:10:01
2025-07-30 06:28:02.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:09:58
2025-07-30 06:28:03.975 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:09:56
2025-07-30 06:28:05.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, 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: 256, ETA: 0:09:53
2025-07-30 06:28:07.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:09:51
2025-07-30 06:28:09.125 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 561/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 1.1, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:09:49
2025-07-30 06:28:09.906 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:28:09.947 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch562
2025-07-30 06:28:11.708 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 1.3, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:09:45
2025-07-30 06:28:13.472 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 9.1, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 4.5, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:09:43
2025-07-30 06:28:15.360 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.092s, 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: 544, ETA: 0:09:40
2025-07-30 06:28:17.128 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:09:38
2025-07-30 06:28:18.888 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 3.7, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:09:36
2025-07-30 06:28:20.681 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 562/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:09:33
2025-07-30 06:28:21.480 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:28:21.585 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch563
2025-07-30 06:28:23.281 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 3.3, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:09:30
2025-07-30 06:28:25.071 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.3, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 2.9, cls_loss: 1.1, lr: 5.000e-04, size: 256, ETA: 0:09:27
2025-07-30 06:28:26.935 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 7.7, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 3.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:09:25
2025-07-30 06:28:28.724 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:09:23
2025-07-30 06:28:30.485 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 9.8, iou_loss: 3.2, l1_loss: 1.1, conf_loss: 4.7, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:09:20
2025-07-30 06:28:32.235 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 563/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:09:18
2025-07-30 06:28:33.020 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:28:33.055 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch564
2025-07-30 06:28:34.884 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:09:15
2025-07-30 06:28:36.646 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 40/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:09:12
2025-07-30 06:28:38.437 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:09:10
2025-07-30 06:28:40.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:09:07
2025-07-30 06:28:42.064 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:09:05
2025-07-30 06:28:43.891 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 564/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:09:03
2025-07-30 06:28:44.682 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:28:44.729 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch565
2025-07-30 06:28:46.411 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.081s, 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: 288, ETA: 0:08:59
2025-07-30 06:28:48.173 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.001s, 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: 256, ETA: 0:08:57
2025-07-30 06:28:49.936 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:08:54
2025-07-30 06:28:51.711 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:08:52
2025-07-30 06:28:53.481 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:08:50
2025-07-30 06:28:55.222 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 565/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:08:47
2025-07-30 06:28:56.028 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:29:02.273 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:29:03.542 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:29:04.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5880
2025-07-30 06:29:04.367 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5309
2025-07-30 06:29:04.422 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3658
2025-07-30 06:29:04.423 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4949
2025-07-30 06:29:04.423 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:29:04.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:29:04.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.588
2025-07-30 06:29:04.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.531
2025-07-30 06:29:04.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.366
2025-07-30 06:29:04.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.495
2025-07-30 06:29:04.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:29:04.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:29:04.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:29:04.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:29:04.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:29:04.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:29:04.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:29:04.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:29:04.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:29:05.263 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:29:06.118 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:29:06.942 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:29:07.808 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:29:08.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:29:09.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:29:10.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:29:11.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:29:11.953 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:29:11.953 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 06:29:11.954 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-07-30 06:29:11.954 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:29:11.961 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.88 ms, Average inference time: 2.24 ms

2025-07-30 06:29:11.961 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:29:11.992 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:29:12.027 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch566
2025-07-30 06:29:13.761 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:08:44
2025-07-30 06:29:15.514 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, 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: 480, ETA: 0:08:42
2025-07-30 06:29:17.392 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.7, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 4.1, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:08:39
2025-07-30 06:29:19.151 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:08:37
2025-07-30 06:29:20.897 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, 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: 480, ETA: 0:08:34
2025-07-30 06:29:22.618 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 566/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:08:32
2025-07-30 06:29:23.404 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:29:23.447 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch567
2025-07-30 06:29:25.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, 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: 416, ETA: 0:08:29
2025-07-30 06:29:27.021 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:08:26
2025-07-30 06:29:28.827 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:08:24
2025-07-30 06:29:30.556 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.5, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:08:21
2025-07-30 06:29:32.350 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:08:19
2025-07-30 06:29:34.134 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 567/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:08:17
2025-07-30 06:29:34.919 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:29:34.963 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch568
2025-07-30 06:29:36.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 20/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.3, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:08:13
2025-07-30 06:29:38.452 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.8, l1_loss: 1.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:08:11
2025-07-30 06:29:40.290 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:08:09
2025-07-30 06:29:42.084 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:08:06
2025-07-30 06:29:43.846 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 1.0, lr: 5.000e-04, size: 256, ETA: 0:08:04
2025-07-30 06:29:45.593 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 568/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.1, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:08:01
2025-07-30 06:29:46.404 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:29:46.446 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch569
2025-07-30 06:29:48.116 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.081s, 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: 288, ETA: 0:07:58
2025-07-30 06:29:49.862 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:07:56
2025-07-30 06:29:51.635 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.086s, data_time: 0.003s, 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: 352, ETA: 0:07:53
2025-07-30 06:29:53.347 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.001s, 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: 0:07:51
2025-07-30 06:29:55.208 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:07:49
2025-07-30 06:29:57.032 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 569/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:07:46
2025-07-30 06:29:57.801 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:29:57.940 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch570
2025-07-30 06:29:59.581 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:07:43
2025-07-30 06:30:01.302 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 7.8, iou_loss: 2.3, l1_loss: 1.3, conf_loss: 3.4, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:07:40
2025-07-30 06:30:03.164 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.091s, data_time: 0.003s, 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: 256, ETA: 0:07:38
2025-07-30 06:30:04.935 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:07:36
2025-07-30 06:30:06.756 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 4.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:07:33
2025-07-30 06:30:08.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 570/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:07:31
2025-07-30 06:30:09.433 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:30:15.686 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:30:16.306 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:30:16.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4466
2025-07-30 06:30:16.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.2623
2025-07-30 06:30:16.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1895
2025-07-30 06:30:16.821 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2995
2025-07-30 06:30:16.821 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:30:16.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:30:16.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.447
2025-07-30 06:30:16.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.262
2025-07-30 06:30:16.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.189
2025-07-30 06:30:16.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.299
2025-07-30 06:30:16.823 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:30:16.823 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:30:16.823 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:30:16.823 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:30:16.823 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:30:16.823 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:30:16.824 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:30:16.824 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:30:16.824 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:30:17.290 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:30:17.716 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:30:18.178 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:30:18.611 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:30:19.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:30:19.472 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:30:19.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:30:20.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:30:20.759 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:30:20.760 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.14
2025-07-30 06:30:20.760 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.30
2025-07-30 06:30:20.761 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:30:20.772 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.90 ms, Average inference time: 2.27 ms

2025-07-30 06:30:20.773 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:30:20.804 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:30:20.841 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch571
2025-07-30 06:30:22.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.079s, 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: 288, ETA: 0:07:28
2025-07-30 06:30:24.285 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.001s, total_loss: 5.9, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 3.1, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:07:25
2025-07-30 06:30:26.104 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:07:23
2025-07-30 06:30:27.884 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:07:21
2025-07-30 06:30:29.730 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:07:18
2025-07-30 06:30:31.455 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 571/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:07:16
2025-07-30 06:30:32.201 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:30:32.246 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch572
2025-07-30 06:30:33.995 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:07:12
2025-07-30 06:30:35.791 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:07:10
2025-07-30 06:30:37.648 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:07:08
2025-07-30 06:30:39.447 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 11.6, iou_loss: 3.0, l1_loss: 2.2, conf_loss: 5.5, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:07:05
2025-07-30 06:30:41.204 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.2, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:07:03
2025-07-30 06:30:43.001 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 572/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:07:01
2025-07-30 06:30:43.786 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:30:43.821 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch573
2025-07-30 06:30:45.533 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:06:57
2025-07-30 06:30:47.285 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:06:55
2025-07-30 06:30:49.066 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 3.2, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:06:52
2025-07-30 06:30:50.801 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:06:50
2025-07-30 06:30:52.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 100/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, 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: 0:06:48
2025-07-30 06:30:54.369 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 573/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:06:45
2025-07-30 06:30:55.151 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:30:55.191 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch574
2025-07-30 06:30:56.933 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:06:42
2025-07-30 06:30:58.799 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:06:40
2025-07-30 06:31:00.574 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:06:37
2025-07-30 06:31:02.302 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 4.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:06:35
2025-07-30 06:31:04.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:06:33
2025-07-30 06:31:05.814 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 574/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 3.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:06:30
2025-07-30 06:31:06.630 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:31:06.677 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch575
2025-07-30 06:31:08.361 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.2, l1_loss: 1.3, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:06:27
2025-07-30 06:31:10.129 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 8.8, iou_loss: 2.8, l1_loss: 1.6, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:06:24
2025-07-30 06:31:11.967 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 16.7, iou_loss: 3.6, l1_loss: 3.1, conf_loss: 8.5, cls_loss: 1.4, lr: 5.000e-04, size: 480, ETA: 0:06:22
2025-07-30 06:31:13.700 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 9.4, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 3.8, cls_loss: 1.9, lr: 5.000e-04, size: 416, ETA: 0:06:20
2025-07-30 06:31:15.475 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.1Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:06:17
2025-07-30 06:31:17.291 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 575/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, 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: 256, ETA: 0:06:15
2025-07-30 06:31:18.082 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:31:24.544 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:31:25.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:31:25.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5952
2025-07-30 06:31:26.067 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5152
2025-07-30 06:31:26.148 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3812
2025-07-30 06:31:26.148 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4972
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.595
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.515
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.381
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.497
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:31:26.149 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:31:26.150 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:31:26.150 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:31:26.150 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:31:26.150 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:31:26.150 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:31:26.833 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:31:27.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:31:28.223 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:31:28.892 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:31:29.599 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:31:30.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:31:30.949 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:31:31.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:31:32.322 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:31:32.322 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-30 06:31:32.322 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-30 06:31:32.322 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:31:32.329 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.92 ms, Average inference time: 2.29 ms

2025-07-30 06:31:32.330 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:31:32.354 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:31:32.385 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch576
2025-07-30 06:31:34.176 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, 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: 480, ETA: 0:06:12
2025-07-30 06:31:35.971 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 9.0, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 3.9, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:06:09
2025-07-30 06:31:37.729 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:06:07
2025-07-30 06:31:39.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:06:05
2025-07-30 06:31:41.287 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:06:02
2025-07-30 06:31:43.035 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 576/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:06:00
2025-07-30 06:31:43.797 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:31:43.871 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch577
2025-07-30 06:31:45.641 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:05:57
2025-07-30 06:31:47.467 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.4, l1_loss: 1.4, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:05:54
2025-07-30 06:31:49.252 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:05:52
2025-07-30 06:31:51.034 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 5.0, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:05:49
2025-07-30 06:31:52.828 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:05:47
2025-07-30 06:31:54.628 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 577/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:05:45
2025-07-30 06:31:55.398 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:31:55.431 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch578
2025-07-30 06:31:57.186 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:05:41
2025-07-30 06:31:59.032 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.006s, total_loss: 4.5, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:05:39
2025-07-30 06:32:00.770 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:05:37
2025-07-30 06:32:02.471 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:05:34
2025-07-30 06:32:04.270 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:05:32
2025-07-30 06:32:06.017 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 578/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:05:30
2025-07-30 06:32:06.858 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:32:06.907 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch579
2025-07-30 06:32:08.736 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.3, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:05:26
2025-07-30 06:32:10.588 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 40/129, gpu mem: 1553Mb, mem: 79.6Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.7, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.7, cls_loss: 1.5, lr: 5.000e-04, size: 448, ETA: 0:05:24
2025-07-30 06:32:12.405 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 60/129, gpu mem: 1553Mb, mem: 80.6Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 8.0, iou_loss: 2.6, l1_loss: 1.2, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:05:22
2025-07-30 06:32:14.270 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 80/129, gpu mem: 1553Mb, mem: 81.4Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.0, l1_loss: 1.3, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:05:19
2025-07-30 06:32:16.196 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.093s, data_time: 0.004s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:05:17
2025-07-30 06:32:18.056 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 579/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.001s, 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: 352, ETA: 0:05:15
2025-07-30 06:32:18.862 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:32:18.920 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch580
2025-07-30 06:32:20.632 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:05:11
2025-07-30 06:32:22.403 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 9.4, iou_loss: 1.0, l1_loss: 0.4, conf_loss: 5.7, cls_loss: 2.2, lr: 5.000e-04, size: 480, ETA: 0:05:09
2025-07-30 06:32:24.214 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:05:07
2025-07-30 06:32:25.994 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 3.7, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:05:04
2025-07-30 06:32:27.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:05:02
2025-07-30 06:32:29.548 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 580/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:04:59
2025-07-30 06:32:30.268 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:32:36.546 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:32:37.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:32:38.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5656
2025-07-30 06:32:38.349 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5182
2025-07-30 06:32:38.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3437
2025-07-30 06:32:38.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4758
2025-07-30 06:32:38.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:32:38.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:32:38.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.566
2025-07-30 06:32:38.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.518
2025-07-30 06:32:38.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.344
2025-07-30 06:32:38.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.476
2025-07-30 06:32:38.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:32:38.405 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:32:38.405 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:32:38.405 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:32:38.405 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:32:38.405 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:32:38.405 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:32:38.405 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:32:38.405 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:32:39.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:32:40.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:32:40.888 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:32:41.701 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:32:42.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:32:43.432 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:32:44.317 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:32:45.107 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:32:46.020 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:32:46.021 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-07-30 06:32:46.021 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-30 06:32:46.022 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:32:46.034 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.38 ms, Average NMS time: 0.94 ms, Average inference time: 2.32 ms

2025-07-30 06:32:46.035 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:32:46.066 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:32:46.107 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch581
2025-07-30 06:32:47.786 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:04:56
2025-07-30 06:32:49.577 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 1.7, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:04:54
2025-07-30 06:32:51.328 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:04:51
2025-07-30 06:32:53.155 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:04:49
2025-07-30 06:32:54.913 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 11.7, iou_loss: 2.9, l1_loss: 2.1, conf_loss: 5.0, cls_loss: 1.7, lr: 5.000e-04, size: 544, ETA: 0:04:47
2025-07-30 06:32:56.771 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 581/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, 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: 576, ETA: 0:04:44
2025-07-30 06:32:57.549 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:32:57.587 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch582
2025-07-30 06:32:59.288 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:04:41
2025-07-30 06:33:01.091 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:04:39
2025-07-30 06:33:02.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:04:36
2025-07-30 06:33:04.565 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.9, iou_loss: 2.9, l1_loss: 1.3, conf_loss: 3.8, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:04:34
2025-07-30 06:33:06.321 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, 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: 256, ETA: 0:04:32
2025-07-30 06:33:08.245 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 582/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:04:29
2025-07-30 06:33:09.053 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:33:09.100 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch583
2025-07-30 06:33:10.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 3.0, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:04:26
2025-07-30 06:33:12.654 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:04:24
2025-07-30 06:33:14.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:04:21
2025-07-30 06:33:16.225 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.4, l1_loss: 1.3, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:04:19
2025-07-30 06:33:18.081 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 1.0, lr: 5.000e-04, size: 576, ETA: 0:04:17
2025-07-30 06:33:19.879 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 583/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:04:14
2025-07-30 06:33:20.604 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:33:20.645 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch584
2025-07-30 06:33:22.342 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:04:11
2025-07-30 06:33:24.082 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:04:09
2025-07-30 06:33:25.843 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 8.0, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:04:06
2025-07-30 06:33:27.611 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.1, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.7, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:04:04
2025-07-30 06:33:29.344 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:04:02
2025-07-30 06:33:31.063 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 584/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:03:59
2025-07-30 06:33:31.840 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:33:31.890 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch585
2025-07-30 06:33:33.623 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 9.1, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 4.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:03:56
2025-07-30 06:33:35.339 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:03:54
2025-07-30 06:33:37.054 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:03:51
2025-07-30 06:33:38.823 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.9, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:03:49
2025-07-30 06:33:40.586 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:03:47
2025-07-30 06:33:42.333 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 585/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:03:44
2025-07-30 06:33:43.097 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:33:49.487 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:33:50.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:33:50.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5908
2025-07-30 06:33:50.841 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5256
2025-07-30 06:33:50.879 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3319
2025-07-30 06:33:50.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4828
2025-07-30 06:33:50.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:33:50.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:33:50.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.591
2025-07-30 06:33:50.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.526
2025-07-30 06:33:50.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.332
2025-07-30 06:33:50.880 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.483
2025-07-30 06:33:50.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:33:50.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:33:50.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:33:50.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:33:50.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:33:50.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:33:50.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:33:50.882 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:33:50.882 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:33:51.517 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:33:52.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:33:52.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:33:53.393 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:33:53.976 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:33:54.592 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:33:55.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:33:55.755 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:33:56.373 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:33:56.373 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-30 06:33:56.373 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-07-30 06:33:56.374 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:33:56.380 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.37 ms, Average NMS time: 0.96 ms, Average inference time: 2.32 ms

2025-07-30 06:33:56.381 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:33:56.405 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:33:56.436 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch586
2025-07-30 06:33:58.238 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:03:41
2025-07-30 06:33:59.975 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:03:39
2025-07-30 06:34:01.709 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:03:36
2025-07-30 06:34:03.433 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:03:34
2025-07-30 06:34:05.177 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:03:32
2025-07-30 06:34:06.850 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 586/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:03:29
2025-07-30 06:34:07.613 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:34:07.645 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch587
2025-07-30 06:34:09.433 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:03:26
2025-07-30 06:34:11.239 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.003s, 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: 0:03:24
2025-07-30 06:34:12.984 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 3.4, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:03:21
2025-07-30 06:34:14.738 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 7.6, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:03:19
2025-07-30 06:34:16.508 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:03:17
2025-07-30 06:34:18.243 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 587/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:03:14
2025-07-30 06:34:19.001 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:34:19.034 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch588
2025-07-30 06:34:20.803 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:03:11
2025-07-30 06:34:22.564 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 3.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:03:09
2025-07-30 06:34:24.400 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.2, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:03:06
2025-07-30 06:34:26.201 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:03:04
2025-07-30 06:34:27.973 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:03:02
2025-07-30 06:34:29.743 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 588/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:02:59
2025-07-30 06:34:30.571 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:34:30.615 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch589
2025-07-30 06:34:32.391 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:02:56
2025-07-30 06:34:34.293 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 8.2, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 4.0, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:02:54
2025-07-30 06:34:36.094 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.2, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:02:51
2025-07-30 06:34:37.849 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:02:49
2025-07-30 06:34:39.544 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:02:47
2025-07-30 06:34:41.285 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 589/600, iter: 120/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.7, l1_loss: 1.6, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:02:44
2025-07-30 06:34:42.142 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:34:42.181 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch590
2025-07-30 06:34:43.937 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:02:41
2025-07-30 06:34:45.704 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:02:39
2025-07-30 06:34:47.515 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:02:36
2025-07-30 06:34:49.271 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 80/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:02:34
2025-07-30 06:34:51.058 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, 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: 320, ETA: 0:02:32
2025-07-30 06:34:52.768 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 590/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:02:29
2025-07-30 06:34:53.569 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:34:59.949 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:35:00.771 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:35:01.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5981
2025-07-30 06:35:01.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5495
2025-07-30 06:35:01.408 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3625
2025-07-30 06:35:01.408 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5034
2025-07-30 06:35:01.408 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:35:01.408 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.598
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.549
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.362
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.503
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:35:01.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:35:01.410 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:35:01.410 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:35:01.410 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:35:02.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:35:02.784 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:35:03.410 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:35:04.039 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:35:04.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:35:05.319 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:35:05.943 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:35:06.612 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:35:07.242 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:35:07.242 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-30 06:35:07.242 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-07-30 06:35:07.242 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:35:07.249 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.39 ms, Average NMS time: 0.90 ms, Average inference time: 2.29 ms

2025-07-30 06:35:07.253 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:35:07.274 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:35:07.301 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch591
2025-07-30 06:35:08.974 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:02:26
2025-07-30 06:35:10.742 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:02:24
2025-07-30 06:35:12.558 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:02:21
2025-07-30 06:35:14.360 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:02:19
2025-07-30 06:35:16.194 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:02:17
2025-07-30 06:35:17.913 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 591/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:02:14
2025-07-30 06:35:18.670 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:35:18.708 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch592
2025-07-30 06:35:20.465 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:02:11
2025-07-30 06:35:22.257 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:02:09
2025-07-30 06:35:24.046 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:02:06
2025-07-30 06:35:25.775 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:02:04
2025-07-30 06:35:27.529 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:02:02
2025-07-30 06:35:29.382 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 592/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:01:59
2025-07-30 06:35:30.142 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:35:30.176 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch593
2025-07-30 06:35:31.918 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:01:56
2025-07-30 06:35:33.706 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:01:54
2025-07-30 06:35:35.516 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 1.6, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:01:52
2025-07-30 06:35:37.327 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:01:49
2025-07-30 06:35:39.168 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, 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: 384, ETA: 0:01:47
2025-07-30 06:35:40.937 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 593/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:01:45
2025-07-30 06:35:41.691 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:35:41.746 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch594
2025-07-30 06:35:43.446 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:01:41
2025-07-30 06:35:45.340 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.091s, data_time: 0.006s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:01:39
2025-07-30 06:35:46.992 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:01:37
2025-07-30 06:35:48.848 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.8Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.0, l1_loss: 1.2, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:01:34
2025-07-30 06:35:50.765 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 100/129, gpu mem: 1553Mb, mem: 80.0Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:01:32
2025-07-30 06:35:52.547 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 594/600, iter: 120/129, gpu mem: 1553Mb, mem: 81.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:01:30
2025-07-30 06:35:53.302 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:35:53.364 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch595
2025-07-30 06:35:55.074 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 20/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:01:26
2025-07-30 06:35:56.841 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 40/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:01:24
2025-07-30 06:35:58.589 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 60/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:01:22
2025-07-30 06:36:00.396 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 80/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:01:19
2025-07-30 06:36:02.119 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 100/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 3.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:01:17
2025-07-30 06:36:03.891 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 595/600, iter: 120/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:01:15
2025-07-30 06:36:04.717 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:36:10.912 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:36:11.991 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:36:12.714 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5957
2025-07-30 06:36:12.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5443
2025-07-30 06:36:12.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3920
2025-07-30 06:36:12.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5107
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.596
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.544
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.392
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.511
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:36:12.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:36:12.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:36:12.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:36:12.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:36:12.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:36:12.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:36:13.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:36:14.710 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:36:15.635 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:36:16.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:36:17.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:36:18.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:36:19.188 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:36:20.066 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:36:20.894 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:36:20.894 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-07-30 06:36:20.894 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-07-30 06:36:20.894 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:36:20.901 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.32 ms, Average NMS time: 0.89 ms, Average inference time: 2.21 ms

2025-07-30 06:36:20.902 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:36:20.923 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:36:20.955 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch596
2025-07-30 06:36:22.668 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.083s, 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: 512, ETA: 0:01:11
2025-07-30 06:36:24.466 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:01:09
2025-07-30 06:36:26.337 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 60/129, gpu mem: 1553Mb, mem: 77.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:01:07
2025-07-30 06:36:28.194 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:01:05
2025-07-30 06:36:30.082 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:01:02
2025-07-30 06:36:31.745 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 596/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:01:00
2025-07-30 06:36:32.515 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:36:32.550 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch597
2025-07-30 06:36:34.266 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:00:57
2025-07-30 06:36:36.168 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.092s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:00:54
2025-07-30 06:36:37.949 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:00:52
2025-07-30 06:36:39.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:00:50
2025-07-30 06:36:41.565 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 3.7, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:00:47
2025-07-30 06:36:43.313 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 597/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, 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: 416, ETA: 0:00:45
2025-07-30 06:36:44.099 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:36:44.139 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch598
2025-07-30 06:36:45.921 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 1.1, lr: 5.000e-04, size: 512, ETA: 0:00:42
2025-07-30 06:36:47.786 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 3.3, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:00:39
2025-07-30 06:36:49.631 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:00:37
2025-07-30 06:36:51.426 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.088s, 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: 352, ETA: 0:00:35
2025-07-30 06:36:53.256 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:00:32
2025-07-30 06:36:55.021 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 598/600, iter: 120/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.3, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:00:30
2025-07-30 06:36:55.873 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:36:55.906 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch599
2025-07-30 06:36:57.672 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 20/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:00:27
2025-07-30 06:36:59.485 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 40/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:00:25
2025-07-30 06:37:01.240 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 60/129, gpu mem: 1553Mb, mem: 78.0Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:00:22
2025-07-30 06:37:03.023 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 80/129, gpu mem: 1553Mb, mem: 78.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:00:20
2025-07-30 06:37:04.778 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 100/129, gpu mem: 1553Mb, mem: 78.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:00:18
2025-07-30 06:37:06.584 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 599/600, iter: 120/129, gpu mem: 1553Mb, mem: 79.6Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 3.5, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:00:15
2025-07-30 06:37:07.465 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:37:07.496 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch600
2025-07-30 06:37:09.205 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 20/129, gpu mem: 1553Mb, mem: 81.1Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:00:12
2025-07-30 06:37:11.069 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 40/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.090s, 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: 320, ETA: 0:00:10
2025-07-30 06:37:12.874 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 60/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 8.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 4.4, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:00:07
2025-07-30 06:37:14.672 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 80/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:00:05
2025-07-30 06:37:16.435 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 100/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:00:03
2025-07-30 06:37:18.197 | INFO     | yolox_microbt.core.trainer:after_iter:257 - epoch: 600/600, iter: 120/129, gpu mem: 1553Mb, mem: 81.9Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:00:01
2025-07-30 06:37:18.983 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:37:25.241 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-07-30 06:37:26.202 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-07-30 06:37:26.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5942
2025-07-30 06:37:26.936 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5305
2025-07-30 06:37:27.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3382
2025-07-30 06:37:27.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4876
2025-07-30 06:37:27.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-07-30 06:37:27.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-07-30 06:37:27.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.594
2025-07-30 06:37:27.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.530
2025-07-30 06:37:27.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.338
2025-07-30 06:37:27.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.488
2025-07-30 06:37:27.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-07-30 06:37:27.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-07-30 06:37:27.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-07-30 06:37:27.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-07-30 06:37:27.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-07-30 06:37:27.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-07-30 06:37:27.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-07-30 06:37:27.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-07-30 06:37:27.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-07-30 06:37:27.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-07-30 06:37:28.633 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-07-30 06:37:29.470 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-07-30 06:37:30.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-07-30 06:37:31.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-07-30 06:37:31.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-07-30 06:37:32.682 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-07-30 06:37:33.451 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-07-30 06:37:34.263 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-07-30 06:37:34.263 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-07-30 06:37:34.264 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-07-30 06:37:34.264 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-07-30 06:37:34.271 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:367 - 
Average forward time: 1.36 ms, Average NMS time: 0.99 ms, Average inference time: 2.35 ms

2025-07-30 06:37:34.272 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:37:34.299 | INFO     | yolox_microbt.core.trainer:save_ckpt:388 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_trainset
2025-07-30 06:37:34.326 | INFO     | yolox_microbt.core.trainer:after_train:172 - Training of experiment is done and the best AP is 27.42
