2025-09-01 06:58:11.968 | INFO     | yolox_microbt.core.trainer:before_train:88 - args: Namespace(config='configs.sa6921_vnne_3classes_voc_float_600e_185k_trainset', experiment_name='sa6921_vnne_3classes_voc_float_600e_185k_trainset', name=None, dist_backend='nccl', dist_url=None, batch_size=64, devices=8, exp_file=None, resume=False, ckpt='checkpoint/SA6921/coco_pretrain_185k.pth', start_epoch=None, num_machines=1, machine_rank=0, fp16=False, cache=None, occupy=False, logger='tensorboard', opts=[])
2025-09-01 06:58:11.973 | 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_185k_trainset' │
├───────────────────┼─────────────────────────────────────────────────────┤
│ test_size         │ (416, 416)                                          │
├───────────────────┼─────────────────────────────────────────────────────┤
│ test_conf         │ 0.01                                                │
├───────────────────┼─────────────────────────────────────────────────────┤
│ nmsthre           │ 0.65                                                │
├───────────────────┼─────────────────────────────────────────────────────┤
│ qat_warmup_epoch  │ -1                                                  │
├───────────────────┼─────────────────────────────────────────────────────┤
│ qat_clib_epoch    │ 1                                                   │
├───────────────────┼─────────────────────────────────────────────────────┤
│ all_reduce_norm   │ True                                                │
╘═══════════════════╧═════════════════════════════════════════════════════╛
2025-09-01 06:58:12.024 | INFO     | yolox_microbt.core.trainer:resume_train:326 - loading checkpoint for fine tuning
2025-09-01 06:58:12.765 | INFO     | yolox_microbt.core.trainer:before_train:129 - init prefetcher, this might take one minute or less...
2025-09-01 06:58:16.115 | INFO     | yolox_microbt.core.trainer:before_train:168 - Training start...
2025-09-01 06:58:16.118 | 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, 10, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(10, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
            (1): InvertedResidual(
              (conv_pw): Conv2d(10, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(40, 40, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=40, bias=False)
              (bn2): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(40, 10, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(10, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (4): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(10, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(40, 40, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=40, bias=False)
              (bn2): BatchNorm2d(40, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(40, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
            (1): InvertedResidual(
              (conv_pw): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128, bias=False)
              (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(128, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
            (2): InvertedResidual(
              (conv_pw): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128, bias=False)
              (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(128, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (5): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128, bias=False)
              (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(128, 38, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(38, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (6): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(38, 152, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(152, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(152, 152, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=152, bias=False)
              (bn2): BatchNorm2d(152, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(152, 42, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn3): BatchNorm2d(42, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
          (7): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(42, 168, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(168, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(168, 168, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=168, bias=False)
              (bn2): BatchNorm2d(168, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(168, 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)
            )
            (1): InvertedResidual(
              (conv_pw): Conv2d(80, 320, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(320, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(320, 320, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=320, bias=False)
              (bn2): BatchNorm2d(320, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(320, 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)
            )
          )
          (8): Sequential(
            (0): InvertedResidual(
              (conv_pw): Conv2d(80, 320, kernel_size=(1, 1), stride=(1, 1), bias=False)
              (bn1): BatchNorm2d(320, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act1): ReLU()
              (conv_dw): Conv2d(320, 320, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=320, bias=False)
              (bn2): BatchNorm2d(320, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
              (act2): ReLU()
              (conv_pwl): Conv2d(320, 128, kernel_size=(1, 1), stride=(1, 1), groups=2, bias=False)
              (bn3): BatchNorm2d(128, eps=1e-05, momentum=0.03, affine=True, track_running_stats=True)
            )
          )
        )
      )
      (head0): YOLOXHead(
        (shared_layer_8): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(10, 64, kernel_size=(1, 1), stride=(1, 1))
            (act0): ReLU()
          )
          (conv1): ConvBlock(
            (conv0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64)
            (act0): ReLU()
          )
          (conv2): ConvBlock(
            (conv0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))
            (act0): ReLU()
          )
        )
        (layer_8_obj): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 1, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (layer_8_cls): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 3, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (layer_8_box): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(64, 4, kernel_size=(1, 1), stride=(1, 1))
          )
        )
        (shared_layer_16): Compose(
          (conv0): ConvBlock(
            (conv0): Conv2d(42, 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(128, 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()
    )
  )
)
2025-09-01 06:58:16.121 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch1
2025-09-01 06:58:16.122 | INFO     | yolox_microbt.core.trainer:before_epoch:204 - --->enable mosaic aug for quantization training!
2025-09-01 06:58:19.733 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 1/600, iter: 20/129, gpu mem: 720Mb, mem: 45.3Gb, iter_time: 0.175s, data_time: 0.013s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.615e-06, size: 288, ETA: 3:45:10
2025-09-01 06:58:22.569 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 1/600, iter: 40/129, gpu mem: 1005Mb, mem: 45.4Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.846e-05, size: 384, ETA: 3:19:13
2025-09-01 06:58:25.429 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 1/600, iter: 60/129, gpu mem: 1005Mb, mem: 45.3Gb, iter_time: 0.139s, data_time: 0.015s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.653e-05, size: 320, ETA: 3:12:39
2025-09-01 06:58:28.251 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 1/600, iter: 80/129, gpu mem: 1005Mb, mem: 45.3Gb, iter_time: 0.140s, data_time: 0.027s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 1.538e-04, size: 288, ETA: 3:09:33
2025-09-01 06:58:31.015 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 1/600, iter: 100/129, gpu mem: 1552Mb, mem: 45.3Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 2.404e-04, size: 544, ETA: 3:05:34
2025-09-01 06:58:33.824 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 1/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.136s, data_time: 0.005s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.461e-04, size: 576, ETA: 3:03:54
2025-09-01 06:58:35.138 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 06:58:35.244 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch2
2025-09-01 06:58:37.882 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 2/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.129s, data_time: 0.038s, total_loss: 7.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 5.336e-04, size: 384, ETA: 3:01:32
2025-09-01 06:58:40.718 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 2/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 6.865e-04, size: 544, ETA: 3:01:23
2025-09-01 06:58:43.641 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 2/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.145s, data_time: 0.047s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 8.586e-04, size: 384, ETA: 3:01:53
2025-09-01 06:58:46.472 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 2/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.135s, data_time: 0.024s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 1.050e-03, size: 448, ETA: 3:01:02
2025-09-01 06:58:49.207 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 2/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.126s, data_time: 0.010s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.261e-03, size: 416, ETA: 2:59:21
2025-09-01 06:58:51.865 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 2/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.127s, data_time: 0.049s, total_loss: 7.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 1.490e-03, size: 288, ETA: 2:58:01
2025-09-01 06:58:53.144 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 06:58:53.238 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch3
2025-09-01 06:58:55.957 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 3/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.121s, data_time: 0.021s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.858e-03, size: 416, ETA: 2:56:26
2025-09-01 06:58:58.787 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 3/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 2.135e-03, size: 288, ETA: 2:55:44
2025-09-01 06:59:01.638 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 3/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.122s, data_time: 0.008s, total_loss: 8.1, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 2.431e-03, size: 352, ETA: 2:54:32
2025-09-01 06:59:04.399 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 3/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.133s, data_time: 0.052s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.746e-03, size: 544, ETA: 2:54:15
2025-09-01 06:59:07.277 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 3/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.142s, data_time: 0.065s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 3.081e-03, size: 320, ETA: 2:54:42
2025-09-01 06:59:10.026 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 3/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.135s, data_time: 0.031s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.435e-03, size: 416, ETA: 2:54:36
2025-09-01 06:59:11.269 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 06:59:11.459 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch4
2025-09-01 06:59:14.059 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 4/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.125s, data_time: 0.018s, total_loss: 8.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 3.982e-03, size: 384, ETA: 2:53:49
2025-09-01 06:59:16.905 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 4/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 4.383e-03, size: 416, ETA: 2:54:07
2025-09-01 06:59:19.695 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 4/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.139s, data_time: 0.060s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 4.803e-03, size: 448, ETA: 2:54:14
2025-09-01 06:59:22.484 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 4/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.242e-03, size: 384, ETA: 2:54:18
2025-09-01 06:59:25.347 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 4/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.138s, data_time: 0.051s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.701e-03, size: 576, ETA: 2:54:21
2025-09-01 06:59:28.146 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 4/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.128s, data_time: 0.027s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 6.179e-03, size: 320, ETA: 2:53:53
2025-09-01 06:59:29.374 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 06:59:29.408 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch5
2025-09-01 06:59:32.282 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 5/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 6.906e-03, size: 576, ETA: 2:54:10
2025-09-01 06:59:35.128 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 5/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.431e-03, size: 480, ETA: 2:54:22
2025-09-01 06:59:37.958 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 5/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 7.975e-03, size: 576, ETA: 2:54:32
2025-09-01 06:59:40.604 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 5/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.131s, data_time: 0.051s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.538e-03, size: 480, ETA: 2:54:16
2025-09-01 06:59:43.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 5/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.136s, data_time: 0.045s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.121e-03, size: 576, ETA: 2:54:13
2025-09-01 06:59:46.259 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 5/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.3Gb, iter_time: 0.141s, data_time: 0.060s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.723e-03, size: 480, ETA: 2:54:21
2025-09-01 06:59:47.520 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 06:59:53.512 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 06:59:56.762 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 06:59:59.247 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4794
2025-09-01 06:59:59.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3806
2025-09-01 06:59:59.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2405
2025-09-01 06:59:59.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3668
2025-09-01 06:59:59.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 06:59:59.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 06:59:59.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.479
2025-09-01 06:59:59.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.381
2025-09-01 06:59:59.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.240
2025-09-01 06:59:59.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.367
2025-09-01 06:59:59.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 06:59:59.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 06:59:59.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 06:59:59.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 06:59:59.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 06:59:59.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 06:59:59.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 06:59:59.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 06:59:59.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:00:02.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:00:05.308 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:00:08.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:00:11.026 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:00:13.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:00:16.700 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:00:19.568 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:00:22.458 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:00:25.435 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:00:25.435 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.13
2025-09-01 07:00:25.435 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-09-01 07:00:25.435 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:00:25.461 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.97 ms, Average inference time: 2.33 ms

2025-09-01 07:00:25.461 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:00:25.487 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:00:25.521 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch6
2025-09-01 07:00:28.003 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 6/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.121s, data_time: 0.039s, total_loss: 7.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 1.000e-02, size: 480, ETA: 2:53:45
2025-09-01 07:00:30.765 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 6/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.129s, data_time: 0.049s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.000e-02, size: 480, ETA: 2:53:28
2025-09-01 07:00:33.536 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 6/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.125s, data_time: 0.023s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 1.000e-02, size: 416, ETA: 2:53:02
2025-09-01 07:00:36.411 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 6/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 1.000e-02, size: 352, ETA: 2:52:51
2025-09-01 07:00:39.178 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 6/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.126s, 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: 1.000e-02, size: 480, ETA: 2:52:30
2025-09-01 07:00:41.921 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 6/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.129s, data_time: 0.029s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.000e-02, size: 416, ETA: 2:52:16
2025-09-01 07:00:43.274 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:00:43.310 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch7
2025-09-01 07:00:46.121 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 7/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.000e-02, size: 544, ETA: 2:52:34
2025-09-01 07:00:48.988 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 7/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 1.000e-02, size: 384, ETA: 2:52:45
2025-09-01 07:00:51.690 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 7/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.134s, data_time: 0.052s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 1.000e-02, size: 320, ETA: 2:52:41
2025-09-01 07:00:54.500 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 7/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.139s, data_time: 0.060s, total_loss: 5.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 1.000e-02, size: 288, ETA: 2:52:45
2025-09-01 07:00:57.502 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 7/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.149s, data_time: 0.065s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.000e-02, size: 256, ETA: 2:53:06
2025-09-01 07:01:00.198 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 7/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.134s, data_time: 0.053s, total_loss: 7.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.999e-03, size: 480, ETA: 2:53:01
2025-09-01 07:01:01.390 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:01:01.515 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch8
2025-09-01 07:01:04.198 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 8/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.132s, data_time: 0.052s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.999e-03, size: 256, ETA: 2:52:47
2025-09-01 07:01:07.156 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 8/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.140s, data_time: 0.036s, total_loss: 7.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.999e-03, size: 352, ETA: 2:52:52
2025-09-01 07:01:09.907 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 8/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.132s, data_time: 0.012s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.999e-03, size: 288, ETA: 2:52:43
2025-09-01 07:01:12.658 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 8/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.130s, data_time: 0.020s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.999e-03, size: 512, ETA: 2:52:33
2025-09-01 07:01:15.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 8/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.132s, data_time: 0.040s, total_loss: 7.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.999e-03, size: 384, ETA: 2:52:25
2025-09-01 07:01:18.250 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 8/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.133s, data_time: 0.039s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.999e-03, size: 576, ETA: 2:52:19
2025-09-01 07:01:19.437 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:01:19.537 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch9
2025-09-01 07:01:22.252 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 9/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.125s, data_time: 0.040s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.999e-03, size: 256, ETA: 2:51:54
2025-09-01 07:01:24.998 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 9/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.136s, data_time: 0.055s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.998e-03, size: 288, ETA: 2:51:53
2025-09-01 07:01:27.810 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 9/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.998e-03, size: 352, ETA: 2:51:56
2025-09-01 07:01:30.712 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 9/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.142s, data_time: 0.054s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.998e-03, size: 256, ETA: 2:52:02
2025-09-01 07:01:33.470 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 9/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.136s, data_time: 0.034s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.998e-03, size: 544, ETA: 2:52:00
2025-09-01 07:01:36.340 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 9/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.998e-03, size: 416, ETA: 2:52:04
2025-09-01 07:01:37.551 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:01:37.685 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch10
2025-09-01 07:01:40.522 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 10/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.132s, data_time: 0.030s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.997e-03, size: 576, ETA: 2:51:54
2025-09-01 07:01:43.262 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 10/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 9.997e-03, size: 288, ETA: 2:51:47
2025-09-01 07:01:46.144 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 10/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.997e-03, size: 576, ETA: 2:51:47
2025-09-01 07:01:48.800 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 10/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.125s, data_time: 0.008s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.997e-03, size: 320, ETA: 2:51:31
2025-09-01 07:01:51.639 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 10/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.128s, data_time: 0.024s, total_loss: 8.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.0, lr: 9.997e-03, size: 416, ETA: 2:51:20
2025-09-01 07:01:54.425 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 10/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.132s, data_time: 0.023s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 9.996e-03, size: 384, ETA: 2:51:13
2025-09-01 07:01:55.715 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:02:01.519 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:02:02.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:02:03.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4738
2025-09-01 07:02:04.072 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3512
2025-09-01 07:02:04.113 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2161
2025-09-01 07:02:04.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3470
2025-09-01 07:02:04.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:02:04.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:02:04.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.474
2025-09-01 07:02:04.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.351
2025-09-01 07:02:04.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.216
2025-09-01 07:02:04.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.347
2025-09-01 07:02:04.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:02:04.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:02:04.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:02:04.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:02:04.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:02:04.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:02:04.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:02:04.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:02:04.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:02:05.261 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:02:06.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:02:07.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:02:08.856 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:02:09.992 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:02:11.131 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:02:12.252 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:02:13.371 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:02:14.503 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:02:14.504 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-09-01 07:02:14.504 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.35
2025-09-01 07:02:14.504 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:02:14.512 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.94 ms, Average inference time: 2.30 ms

2025-09-01 07:02:14.518 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:02:14.545 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:02:14.576 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch11
2025-09-01 07:02:17.034 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 11/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.121s, data_time: 0.044s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.996e-03, size: 576, ETA: 2:50:56
2025-09-01 07:02:19.842 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 11/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.134s, data_time: 0.050s, total_loss: 8.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.996e-03, size: 384, ETA: 2:50:53
2025-09-01 07:02:22.623 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 11/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.128s, data_time: 0.016s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.996e-03, size: 480, ETA: 2:50:43
2025-09-01 07:02:25.460 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 11/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.134s, data_time: 0.021s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.995e-03, size: 448, ETA: 2:50:40
2025-09-01 07:02:28.249 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 11/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.135s, data_time: 0.022s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.995e-03, size: 576, ETA: 2:50:37
2025-09-01 07:02:31.121 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 11/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.141s, data_time: 0.046s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.995e-03, size: 512, ETA: 2:50:41
2025-09-01 07:02:32.332 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:02:32.426 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch12
2025-09-01 07:02:35.244 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 12/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.136s, data_time: 0.048s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.994e-03, size: 416, ETA: 2:50:38
2025-09-01 07:02:38.048 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 12/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.133s, data_time: 0.036s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 9.994e-03, size: 576, ETA: 2:50:34
2025-09-01 07:02:40.866 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 12/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.133s, data_time: 0.025s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.994e-03, size: 512, ETA: 2:50:29
2025-09-01 07:02:43.653 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 12/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.136s, data_time: 0.022s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.993e-03, size: 544, ETA: 2:50:27
2025-09-01 07:02:46.550 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 12/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.132s, data_time: 0.037s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.993e-03, size: 384, ETA: 2:50:22
2025-09-01 07:02:49.468 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 12/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.139s, 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: 9.993e-03, size: 448, ETA: 2:50:24
2025-09-01 07:02:50.594 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:02:50.635 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch13
2025-09-01 07:02:53.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 13/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.132s, data_time: 0.039s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.992e-03, size: 544, ETA: 2:50:13
2025-09-01 07:02:56.278 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 13/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.143s, data_time: 0.065s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 9.992e-03, size: 288, ETA: 2:50:18
2025-09-01 07:02:59.057 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 13/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.137s, data_time: 0.045s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.992e-03, size: 416, ETA: 2:50:18
2025-09-01 07:03:01.881 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 13/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.138s, 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: 9.991e-03, size: 352, ETA: 2:50:18
2025-09-01 07:03:04.765 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 13/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.143s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.991e-03, size: 384, ETA: 2:50:23
2025-09-01 07:03:07.601 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 13/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.139s, data_time: 0.004s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 9.991e-03, size: 256, ETA: 2:50:24
2025-09-01 07:03:08.793 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:03:08.950 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch14
2025-09-01 07:03:11.722 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 14/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.128s, data_time: 0.024s, total_loss: 6.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.990e-03, size: 320, ETA: 2:50:11
2025-09-01 07:03:14.579 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 14/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.024s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.990e-03, size: 256, ETA: 2:50:07
2025-09-01 07:03:17.402 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 14/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 9.989e-03, size: 256, ETA: 2:50:02
2025-09-01 07:03:20.088 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 14/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.131s, data_time: 0.024s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.989e-03, size: 256, ETA: 2:49:56
2025-09-01 07:03:23.045 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 14/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.140s, data_time: 0.022s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 9.988e-03, size: 256, ETA: 2:49:58
2025-09-01 07:03:25.893 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 14/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.4Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.988e-03, size: 320, ETA: 2:49:53
2025-09-01 07:03:27.145 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:03:27.190 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch15
2025-09-01 07:03:29.920 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 15/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.987e-03, size: 288, ETA: 2:49:50
2025-09-01 07:03:32.772 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 15/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.139s, data_time: 0.014s, total_loss: 6.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.987e-03, size: 288, ETA: 2:49:50
2025-09-01 07:03:35.584 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 15/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.137s, data_time: 0.014s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.987e-03, size: 544, ETA: 2:49:49
2025-09-01 07:03:38.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 15/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.986e-03, size: 448, ETA: 2:49:47
2025-09-01 07:03:41.155 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 15/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.135s, data_time: 0.008s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.986e-03, size: 544, ETA: 2:49:44
2025-09-01 07:03:43.962 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 15/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.135s, data_time: 0.035s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 9.985e-03, size: 480, ETA: 2:49:42
2025-09-01 07:03:45.332 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:03:51.249 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:03:56.023 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:03:59.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4451
2025-09-01 07:04:00.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3567
2025-09-01 07:04:00.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1788
2025-09-01 07:04:00.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3269
2025-09-01 07:04:00.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:04:00.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:04:00.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.445
2025-09-01 07:04:00.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.357
2025-09-01 07:04:00.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.179
2025-09-01 07:04:00.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.327
2025-09-01 07:04:00.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:04:00.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:04:00.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:04:00.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:04:00.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:04:00.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:04:00.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:04:00.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:04:00.294 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:04:04.456 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:04:08.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:04:12.897 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:04:17.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:04:21.367 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:04:25.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:04:29.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:04:33.952 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:04:38.317 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:04:38.318 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.15
2025-09-01 07:04:38.318 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.33
2025-09-01 07:04:38.318 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:04:38.343 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.97 ms, Average inference time: 2.35 ms

2025-09-01 07:04:38.344 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:04:38.380 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:04:38.429 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch16
2025-09-01 07:04:40.816 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 16/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.117s, data_time: 0.036s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.985e-03, size: 256, ETA: 2:49:29
2025-09-01 07:04:43.642 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 16/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.135s, data_time: 0.050s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.984e-03, size: 448, ETA: 2:49:27
2025-09-01 07:04:46.407 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 16/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.132s, data_time: 0.013s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.984e-03, size: 416, ETA: 2:49:22
2025-09-01 07:04:49.211 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 16/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.130s, data_time: 0.017s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.983e-03, size: 288, ETA: 2:49:16
2025-09-01 07:04:52.053 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 16/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.130s, data_time: 0.029s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.983e-03, size: 416, ETA: 2:49:10
2025-09-01 07:04:54.858 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 16/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.127s, data_time: 0.005s, total_loss: 7.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.982e-03, size: 384, ETA: 2:49:02
2025-09-01 07:04:56.000 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:04:56.170 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch17
2025-09-01 07:04:59.071 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 17/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.123s, data_time: 0.027s, total_loss: 8.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 1.3, lr: 9.981e-03, size: 544, ETA: 2:48:42
2025-09-01 07:05:01.783 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 17/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.127s, data_time: 0.043s, total_loss: 7.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.981e-03, size: 320, ETA: 2:48:35
2025-09-01 07:05:04.629 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 17/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.142s, data_time: 0.064s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.980e-03, size: 544, ETA: 2:48:37
2025-09-01 07:05:07.552 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 17/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.145s, data_time: 0.065s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 9.980e-03, size: 512, ETA: 2:48:42
2025-09-01 07:05:10.322 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 17/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.132s, data_time: 0.048s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.979e-03, size: 352, ETA: 2:48:37
2025-09-01 07:05:13.126 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 17/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.133s, data_time: 0.044s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.979e-03, size: 384, ETA: 2:48:34
2025-09-01 07:05:14.371 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:05:14.412 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch18
2025-09-01 07:05:17.197 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 18/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.978e-03, size: 576, ETA: 2:48:32
2025-09-01 07:05:20.042 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 18/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.136s, data_time: 0.033s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.977e-03, size: 256, ETA: 2:48:30
2025-09-01 07:05:22.932 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 18/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.136s, 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: 9.977e-03, size: 512, ETA: 2:48:28
2025-09-01 07:05:25.662 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 18/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.034s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.976e-03, size: 576, ETA: 2:48:25
2025-09-01 07:05:28.503 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 18/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.027s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.976e-03, size: 384, ETA: 2:48:22
2025-09-01 07:05:31.280 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 18/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.131s, data_time: 0.007s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.975e-03, size: 352, ETA: 2:48:17
2025-09-01 07:05:32.467 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:05:32.508 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch19
2025-09-01 07:05:35.309 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 19/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.137s, 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: 9.974e-03, size: 384, ETA: 2:48:14
2025-09-01 07:05:38.107 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 19/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.137s, data_time: 0.049s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.973e-03, size: 512, ETA: 2:48:13
2025-09-01 07:05:40.988 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 19/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.140s, data_time: 0.026s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.973e-03, size: 416, ETA: 2:48:14
2025-09-01 07:05:43.867 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 19/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.141s, data_time: 0.015s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.972e-03, size: 384, ETA: 2:48:15
2025-09-01 07:05:46.783 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 19/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.972e-03, size: 480, ETA: 2:48:18
2025-09-01 07:05:49.629 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 19/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.138s, data_time: 0.004s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.971e-03, size: 576, ETA: 2:48:18
2025-09-01 07:05:50.869 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:05:50.916 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch20
2025-09-01 07:05:53.709 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 20/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 9.970e-03, size: 576, ETA: 2:48:13
2025-09-01 07:05:56.575 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 20/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.139s, 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: 9.969e-03, size: 384, ETA: 2:48:13
2025-09-01 07:05:59.358 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 20/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.969e-03, size: 544, ETA: 2:48:08
2025-09-01 07:06:02.205 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 20/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.968e-03, size: 352, ETA: 2:48:07
2025-09-01 07:06:05.026 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 20/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.138s, data_time: 0.030s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.967e-03, size: 320, ETA: 2:48:06
2025-09-01 07:06:07.801 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 20/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.130s, data_time: 0.024s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.967e-03, size: 416, ETA: 2:48:00
2025-09-01 07:06:09.080 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:06:15.030 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:06:16.315 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:06:17.067 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4329
2025-09-01 07:06:17.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3498
2025-09-01 07:06:17.271 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2103
2025-09-01 07:06:17.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3310
2025-09-01 07:06:17.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:06:17.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:06:17.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.433
2025-09-01 07:06:17.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.350
2025-09-01 07:06:17.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.210
2025-09-01 07:06:17.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.331
2025-09-01 07:06:17.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:06:17.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:06:17.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:06:17.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:06:17.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:06:17.273 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:06:17.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:06:17.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:06:17.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:06:18.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:06:19.180 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:06:20.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:06:21.142 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:06:22.075 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:06:23.019 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:06:23.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:06:24.851 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:06:25.808 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:06:25.809 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-09-01 07:06:25.809 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.33
2025-09-01 07:06:25.809 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:06:25.817 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.95 ms, Average inference time: 2.34 ms

2025-09-01 07:06:25.822 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:06:25.848 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:06:25.879 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch21
2025-09-01 07:06:28.264 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 21/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.118s, data_time: 0.041s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.966e-03, size: 352, ETA: 2:47:44
2025-09-01 07:06:31.147 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 21/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.965e-03, size: 352, ETA: 2:47:46
2025-09-01 07:06:33.968 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 21/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.964e-03, size: 384, ETA: 2:47:47
2025-09-01 07:06:36.814 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 21/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.141s, data_time: 0.007s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.963e-03, size: 576, ETA: 2:47:47
2025-09-01 07:06:39.646 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 21/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.128s, data_time: 0.014s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.963e-03, size: 416, ETA: 2:47:41
2025-09-01 07:06:42.494 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 21/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.962e-03, size: 416, ETA: 2:47:38
2025-09-01 07:06:43.717 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:06:43.762 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch22
2025-09-01 07:06:46.584 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 22/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.034s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.961e-03, size: 320, ETA: 2:47:34
2025-09-01 07:06:49.456 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 22/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.133s, 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: 9.960e-03, size: 480, ETA: 2:47:30
2025-09-01 07:06:52.278 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 22/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.136s, data_time: 0.021s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.959e-03, size: 576, ETA: 2:47:28
2025-09-01 07:06:55.181 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 22/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.143s, data_time: 0.056s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.959e-03, size: 384, ETA: 2:47:29
2025-09-01 07:06:57.903 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 22/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.958e-03, size: 512, ETA: 2:47:27
2025-09-01 07:07:00.806 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 22/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.142s, data_time: 0.054s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.957e-03, size: 544, ETA: 2:47:28
2025-09-01 07:07:02.095 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:07:02.133 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch23
2025-09-01 07:07:04.979 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 23/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.141s, data_time: 0.034s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.956e-03, size: 352, ETA: 2:47:28
2025-09-01 07:07:07.899 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 23/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.955e-03, size: 256, ETA: 2:47:30
2025-09-01 07:07:10.883 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 23/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.148s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.954e-03, size: 480, ETA: 2:47:34
2025-09-01 07:07:13.785 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 23/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.142s, data_time: 0.003s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 9.953e-03, size: 576, ETA: 2:47:35
2025-09-01 07:07:16.711 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 23/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.143s, data_time: 0.004s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.953e-03, size: 416, ETA: 2:47:36
2025-09-01 07:07:19.674 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 23/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.147s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 9.952e-03, size: 512, ETA: 2:47:40
2025-09-01 07:07:20.940 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:07:21.067 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch24
2025-09-01 07:07:23.864 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 24/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.951e-03, size: 512, ETA: 2:47:36
2025-09-01 07:07:26.653 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 24/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.137s, data_time: 0.045s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.950e-03, size: 288, ETA: 2:47:34
2025-09-01 07:07:29.542 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 24/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.139s, data_time: 0.055s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.949e-03, size: 352, ETA: 2:47:33
2025-09-01 07:07:32.485 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 24/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.138s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.948e-03, size: 416, ETA: 2:47:32
2025-09-01 07:07:35.274 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 24/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 9.947e-03, size: 320, ETA: 2:47:27
2025-09-01 07:07:38.040 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 24/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.039s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.9, lr: 9.946e-03, size: 576, ETA: 2:47:25
2025-09-01 07:07:39.279 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:07:39.315 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch25
2025-09-01 07:07:42.052 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 25/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 8.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.4, lr: 9.945e-03, size: 320, ETA: 2:47:22
2025-09-01 07:07:44.833 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 25/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.944e-03, size: 320, ETA: 2:47:20
2025-09-01 07:07:47.652 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 25/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.943e-03, size: 448, ETA: 2:47:19
2025-09-01 07:07:50.387 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 25/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.055s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.942e-03, size: 416, ETA: 2:47:16
2025-09-01 07:07:53.349 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 25/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.144s, data_time: 0.031s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.941e-03, size: 576, ETA: 2:47:17
2025-09-01 07:07:56.152 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 25/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.138s, 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: 9.940e-03, size: 512, ETA: 2:47:16
2025-09-01 07:07:57.401 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:08:03.536 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:08:08.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:08:12.037 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4084
2025-09-01 07:08:12.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3536
2025-09-01 07:08:12.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2075
2025-09-01 07:08:12.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3232
2025-09-01 07:08:12.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:08:12.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:08:12.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.408
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.354
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.208
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.323
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:08:12.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:08:12.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:08:12.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:08:16.711 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:08:21.189 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:08:25.382 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:08:29.580 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:08:33.683 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:08:37.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:08:42.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:08:46.158 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:08:50.341 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:08:50.341 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.15
2025-09-01 07:08:50.341 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.32
2025-09-01 07:08:50.342 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:08:50.368 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.41 ms, Average NMS time: 1.00 ms, Average inference time: 2.41 ms

2025-09-01 07:08:50.370 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:08:50.402 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:08:50.439 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch26
2025-09-01 07:08:53.011 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 26/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.126s, data_time: 0.052s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.939e-03, size: 480, ETA: 2:47:08
2025-09-01 07:08:55.874 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 26/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.142s, data_time: 0.058s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.938e-03, size: 288, ETA: 2:47:08
2025-09-01 07:08:58.593 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 26/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.129s, data_time: 0.047s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.937e-03, size: 288, ETA: 2:47:02
2025-09-01 07:09:01.363 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 26/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.936e-03, size: 448, ETA: 2:47:01
2025-09-01 07:09:04.206 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 26/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.141s, data_time: 0.060s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.935e-03, size: 544, ETA: 2:47:01
2025-09-01 07:09:06.934 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 26/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.133s, data_time: 0.054s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.934e-03, size: 320, ETA: 2:46:57
2025-09-01 07:09:08.153 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:09:08.263 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch27
2025-09-01 07:09:11.141 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 27/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.5Gb, iter_time: 0.122s, data_time: 0.037s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 9.933e-03, size: 288, ETA: 2:46:45
2025-09-01 07:09:13.957 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 27/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.123s, data_time: 0.029s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 9.932e-03, size: 576, ETA: 2:46:37
2025-09-01 07:09:16.877 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 27/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.931e-03, size: 448, ETA: 2:46:38
2025-09-01 07:09:19.678 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 27/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.930e-03, size: 480, ETA: 2:46:37
2025-09-01 07:09:22.525 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 27/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.929e-03, size: 384, ETA: 2:46:37
2025-09-01 07:09:25.400 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 27/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 8.2, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 9.928e-03, size: 288, ETA: 2:46:37
2025-09-01 07:09:26.588 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:09:26.649 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch28
2025-09-01 07:09:29.378 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 28/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.126s, data_time: 0.028s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.926e-03, size: 416, ETA: 2:46:29
2025-09-01 07:09:32.279 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 28/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.131s, 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: 9.925e-03, size: 512, ETA: 2:46:24
2025-09-01 07:09:35.130 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 28/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.924e-03, size: 320, ETA: 2:46:20
2025-09-01 07:09:38.021 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 28/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.923e-03, size: 448, ETA: 2:46:14
2025-09-01 07:09:40.858 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 28/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.126s, 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: 9.922e-03, size: 480, ETA: 2:46:08
2025-09-01 07:09:43.527 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 28/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.119s, data_time: 0.006s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.921e-03, size: 416, ETA: 2:45:59
2025-09-01 07:09:44.838 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:09:44.887 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch29
2025-09-01 07:09:47.746 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 29/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.140s, data_time: 0.052s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.920e-03, size: 576, ETA: 2:45:58
2025-09-01 07:09:50.541 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 29/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.138s, data_time: 0.034s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.919e-03, size: 352, ETA: 2:45:57
2025-09-01 07:09:53.367 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 29/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.133s, data_time: 0.007s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.918e-03, size: 320, ETA: 2:45:53
2025-09-01 07:09:56.147 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 29/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.131s, data_time: 0.049s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.916e-03, size: 352, ETA: 2:45:49
2025-09-01 07:09:58.966 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 29/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.017s, total_loss: 5.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 9.915e-03, size: 288, ETA: 2:45:46
2025-09-01 07:10:01.862 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 29/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.914e-03, size: 256, ETA: 2:45:46
2025-09-01 07:10:03.097 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:10:03.229 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch30
2025-09-01 07:10:06.065 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 30/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.050s, total_loss: 8.4, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.913e-03, size: 256, ETA: 2:45:41
2025-09-01 07:10:08.826 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 30/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.130s, data_time: 0.003s, total_loss: 7.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.911e-03, size: 288, ETA: 2:45:36
2025-09-01 07:10:11.635 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 30/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.131s, 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: 9.910e-03, size: 576, ETA: 2:45:32
2025-09-01 07:10:14.567 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 30/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.909e-03, size: 448, ETA: 2:45:31
2025-09-01 07:10:17.416 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 30/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.9, lr: 9.908e-03, size: 288, ETA: 2:45:29
2025-09-01 07:10:20.124 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 30/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.132s, data_time: 0.017s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 9.907e-03, size: 256, ETA: 2:45:25
2025-09-01 07:10:21.388 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:10:27.338 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:10:33.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:10:39.202 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4436
2025-09-01 07:10:39.509 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3472
2025-09-01 07:10:39.613 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2279
2025-09-01 07:10:39.613 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3395
2025-09-01 07:10:39.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:10:39.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:10:39.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.444
2025-09-01 07:10:39.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.347
2025-09-01 07:10:39.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.228
2025-09-01 07:10:39.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.340
2025-09-01 07:10:39.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:10:39.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:10:39.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:10:39.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:10:39.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:10:39.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:10:39.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:10:39.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:10:39.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:10:45.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:10:51.182 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:10:56.984 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:11:02.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:11:08.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:11:15.060 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:11:21.006 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:11:26.748 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:11:32.571 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:11:32.571 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.16
2025-09-01 07:11:32.571 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.34
2025-09-01 07:11:32.571 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:11:32.597 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.40 ms, Average NMS time: 0.98 ms, Average inference time: 2.38 ms

2025-09-01 07:11:32.599 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:11:32.626 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:11:32.658 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch31
2025-09-01 07:11:35.101 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 31/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.121s, data_time: 0.042s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.905e-03, size: 288, ETA: 2:45:16
2025-09-01 07:11:37.886 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 31/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.138s, data_time: 0.054s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.904e-03, size: 480, ETA: 2:45:14
2025-09-01 07:11:40.737 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 31/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.140s, data_time: 0.056s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.903e-03, size: 448, ETA: 2:45:13
2025-09-01 07:11:43.437 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 31/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.133s, data_time: 0.045s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.902e-03, size: 544, ETA: 2:45:10
2025-09-01 07:11:46.308 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 31/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.901e-03, size: 416, ETA: 2:45:09
2025-09-01 07:11:49.182 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 31/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.140s, data_time: 0.026s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.3, lr: 9.899e-03, size: 256, ETA: 2:45:09
2025-09-01 07:11:50.338 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:11:50.498 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch32
2025-09-01 07:11:53.256 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 32/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.132s, data_time: 0.033s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.898e-03, size: 544, ETA: 2:45:02
2025-09-01 07:11:56.167 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 32/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.138s, data_time: 0.051s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 9.896e-03, size: 544, ETA: 2:45:01
2025-09-01 07:11:59.032 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 32/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.136s, data_time: 0.048s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.895e-03, size: 320, ETA: 2:44:58
2025-09-01 07:12:01.791 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 32/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.894e-03, size: 384, ETA: 2:44:56
2025-09-01 07:12:04.721 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 32/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.146s, data_time: 0.063s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 9.893e-03, size: 512, ETA: 2:44:57
2025-09-01 07:12:07.630 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 32/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.145s, data_time: 0.062s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 9.891e-03, size: 256, ETA: 2:44:58
2025-09-01 07:12:08.991 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:12:09.041 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch33
2025-09-01 07:12:11.799 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 33/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.053s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.890e-03, size: 576, ETA: 2:44:57
2025-09-01 07:12:14.544 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 33/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.054s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.888e-03, size: 384, ETA: 2:44:55
2025-09-01 07:12:17.409 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 33/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.887e-03, size: 352, ETA: 2:44:54
2025-09-01 07:12:20.249 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 33/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.036s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 9.886e-03, size: 576, ETA: 2:44:51
2025-09-01 07:12:23.069 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 33/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.122s, data_time: 0.017s, total_loss: 7.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.885e-03, size: 256, ETA: 2:44:43
2025-09-01 07:12:25.939 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 33/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.125s, data_time: 0.013s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 9.883e-03, size: 320, ETA: 2:44:37
2025-09-01 07:12:27.275 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:12:27.317 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch34
2025-09-01 07:12:30.093 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 34/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.125s, data_time: 0.011s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.881e-03, size: 448, ETA: 2:44:29
2025-09-01 07:12:32.883 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 34/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.130s, data_time: 0.021s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.880e-03, size: 448, ETA: 2:44:25
2025-09-01 07:12:35.649 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 34/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.050s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 9.879e-03, size: 320, ETA: 2:44:22
2025-09-01 07:12:38.505 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 34/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.877e-03, size: 320, ETA: 2:44:21
2025-09-01 07:12:41.326 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 34/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.047s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.876e-03, size: 480, ETA: 2:44:18
2025-09-01 07:12:44.100 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 34/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.134s, data_time: 0.052s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.875e-03, size: 480, ETA: 2:44:15
2025-09-01 07:12:45.351 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:12:45.391 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch35
2025-09-01 07:12:48.197 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 35/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.139s, data_time: 0.051s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.873e-03, size: 576, ETA: 2:44:13
2025-09-01 07:12:51.012 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 35/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.128s, data_time: 0.029s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.2, lr: 9.872e-03, size: 384, ETA: 2:44:07
2025-09-01 07:12:53.789 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 35/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.131s, data_time: 0.049s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 9.870e-03, size: 256, ETA: 2:44:03
2025-09-01 07:12:56.661 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 35/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.137s, data_time: 0.059s, total_loss: 5.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.6, lr: 9.869e-03, size: 576, ETA: 2:44:01
2025-09-01 07:12:59.530 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 35/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 9.867e-03, size: 288, ETA: 2:44:01
2025-09-01 07:13:02.455 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 35/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 6.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.866e-03, size: 320, ETA: 2:44:01
2025-09-01 07:13:03.700 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:13:09.759 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:13:14.894 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:13:18.818 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4719
2025-09-01 07:13:19.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3610
2025-09-01 07:13:19.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2518
2025-09-01 07:13:19.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3616
2025-09-01 07:13:19.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:13:19.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:13:19.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.472
2025-09-01 07:13:19.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.361
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.252
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.362
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:13:19.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:13:19.469 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:13:23.887 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:13:28.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:13:32.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:13:37.128 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:13:41.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:13:46.034 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:13:50.419 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:13:54.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:13:59.147 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:13:59.148 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.15
2025-09-01 07:13:59.148 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-09-01 07:13:59.148 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:13:59.174 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.93 ms, Average inference time: 2.29 ms

2025-09-01 07:13:59.179 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:13:59.206 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:13:59.244 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch36
2025-09-01 07:14:01.693 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 36/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.114s, data_time: 0.032s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.864e-03, size: 384, ETA: 2:43:49
2025-09-01 07:14:04.629 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 36/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.015s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.3, lr: 9.863e-03, size: 352, ETA: 2:43:47
2025-09-01 07:14:07.490 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 36/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.134s, data_time: 0.014s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.861e-03, size: 544, ETA: 2:43:44
2025-09-01 07:14:10.292 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 36/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.132s, data_time: 0.046s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 9.860e-03, size: 384, ETA: 2:43:41
2025-09-01 07:14:13.232 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 36/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.041s, total_loss: 7.7, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.858e-03, size: 256, ETA: 2:43:38
2025-09-01 07:14:16.028 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 36/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.132s, data_time: 0.015s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.857e-03, size: 576, ETA: 2:43:34
2025-09-01 07:14:17.328 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:14:17.363 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch37
2025-09-01 07:14:20.120 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 37/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.022s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.855e-03, size: 416, ETA: 2:43:32
2025-09-01 07:14:22.872 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 37/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 8.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.2, lr: 9.853e-03, size: 320, ETA: 2:43:29
2025-09-01 07:14:25.827 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 37/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.146s, data_time: 0.071s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.852e-03, size: 416, ETA: 2:43:30
2025-09-01 07:14:28.597 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 37/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.851e-03, size: 352, ETA: 2:43:28
2025-09-01 07:14:31.442 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 37/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.849e-03, size: 480, ETA: 2:43:27
2025-09-01 07:14:34.257 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 37/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.848e-03, size: 576, ETA: 2:43:26
2025-09-01 07:14:35.535 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:14:35.571 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch38
2025-09-01 07:14:38.492 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 38/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.145s, data_time: 0.060s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.846e-03, size: 576, ETA: 2:43:26
2025-09-01 07:14:41.254 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 38/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.055s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 9.844e-03, size: 416, ETA: 2:43:23
2025-09-01 07:14:44.087 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 38/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.134s, data_time: 0.037s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.843e-03, size: 576, ETA: 2:43:20
2025-09-01 07:14:46.894 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 38/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.017s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 9.841e-03, size: 256, ETA: 2:43:18
2025-09-01 07:14:49.706 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 38/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.131s, data_time: 0.049s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.840e-03, size: 320, ETA: 2:43:14
2025-09-01 07:14:52.610 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 38/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.129s, data_time: 0.048s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.838e-03, size: 576, ETA: 2:43:10
2025-09-01 07:14:53.779 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:14:53.957 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch39
2025-09-01 07:14:56.779 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 39/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 9.836e-03, size: 384, ETA: 2:43:05
2025-09-01 07:14:59.508 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 39/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.133s, data_time: 0.051s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.834e-03, size: 384, ETA: 2:43:02
2025-09-01 07:15:02.273 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 39/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.833e-03, size: 320, ETA: 2:42:59
2025-09-01 07:15:05.105 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 39/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.130s, data_time: 0.042s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.831e-03, size: 256, ETA: 2:42:55
2025-09-01 07:15:07.942 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 39/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.042s, total_loss: 7.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.830e-03, size: 576, ETA: 2:42:53
2025-09-01 07:15:10.747 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 39/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.041s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.828e-03, size: 320, ETA: 2:42:50
2025-09-01 07:15:12.015 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:15:12.071 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch40
2025-09-01 07:15:14.900 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 40/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.6Gb, iter_time: 0.135s, data_time: 0.049s, total_loss: 7.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.826e-03, size: 256, ETA: 2:42:47
2025-09-01 07:15:17.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 40/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.130s, data_time: 0.015s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 9.824e-03, size: 384, ETA: 2:42:43
2025-09-01 07:15:20.418 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 40/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.034s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 9.823e-03, size: 352, ETA: 2:42:40
2025-09-01 07:15:23.236 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 40/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.821e-03, size: 352, ETA: 2:42:39
2025-09-01 07:15:26.109 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 40/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.030s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.819e-03, size: 512, ETA: 2:42:37
2025-09-01 07:15:28.852 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 40/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.027s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.818e-03, size: 288, ETA: 2:42:34
2025-09-01 07:15:30.111 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:15:36.063 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:15:38.645 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:15:40.400 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4559
2025-09-01 07:15:40.809 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3802
2025-09-01 07:15:40.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2300
2025-09-01 07:15:40.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3554
2025-09-01 07:15:40.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:15:40.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:15:40.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.456
2025-09-01 07:15:40.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.380
2025-09-01 07:15:40.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.230
2025-09-01 07:15:40.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.355
2025-09-01 07:15:40.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:15:40.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:15:40.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:15:40.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:15:40.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:15:40.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:15:40.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:15:40.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:15:40.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:15:43.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:15:45.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:15:47.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:15:49.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:15:51.726 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:15:53.809 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:15:55.907 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:15:58.039 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:16:00.143 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:16:00.143 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-09-01 07:16:00.143 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-09-01 07:16:00.143 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:16:00.163 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.98 ms, Average inference time: 2.37 ms

2025-09-01 07:16:00.172 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:16:00.194 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:16:00.224 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch41
2025-09-01 07:16:02.753 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 41/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.126s, data_time: 0.051s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.816e-03, size: 320, ETA: 2:42:28
2025-09-01 07:16:05.631 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 41/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.142s, data_time: 0.066s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.814e-03, size: 320, ETA: 2:42:27
2025-09-01 07:16:08.432 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 41/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.061s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.812e-03, size: 320, ETA: 2:42:25
2025-09-01 07:16:11.282 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 41/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.811e-03, size: 320, ETA: 2:42:25
2025-09-01 07:16:14.200 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 41/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.145s, data_time: 0.061s, total_loss: 7.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.809e-03, size: 480, ETA: 2:42:25
2025-09-01 07:16:17.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 41/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.144s, data_time: 0.060s, total_loss: 7.3, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.807e-03, size: 512, ETA: 2:42:24
2025-09-01 07:16:18.233 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:16:18.288 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch42
2025-09-01 07:16:21.152 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 42/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.143s, data_time: 0.058s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.805e-03, size: 416, ETA: 2:42:21
2025-09-01 07:16:23.927 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 42/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.138s, data_time: 0.058s, total_loss: 8.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 9.803e-03, size: 544, ETA: 2:42:19
2025-09-01 07:16:26.838 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 42/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.802e-03, size: 544, ETA: 2:42:19
2025-09-01 07:16:29.669 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 42/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.800e-03, size: 352, ETA: 2:42:18
2025-09-01 07:16:32.569 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 42/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.041s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.798e-03, size: 480, ETA: 2:42:15
2025-09-01 07:16:35.323 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 42/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.133s, data_time: 0.051s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.797e-03, size: 352, ETA: 2:42:12
2025-09-01 07:16:36.567 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:16:36.621 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch43
2025-09-01 07:16:39.349 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 43/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.794e-03, size: 320, ETA: 2:42:08
2025-09-01 07:16:42.070 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 43/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.054s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.792e-03, size: 544, ETA: 2:42:06
2025-09-01 07:16:44.969 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 43/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.142s, data_time: 0.044s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.791e-03, size: 480, ETA: 2:42:05
2025-09-01 07:16:47.830 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 43/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.142s, data_time: 0.059s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.789e-03, size: 512, ETA: 2:42:04
2025-09-01 07:16:50.666 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 43/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.141s, data_time: 0.057s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.787e-03, size: 256, ETA: 2:42:03
2025-09-01 07:16:53.426 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 43/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.133s, data_time: 0.047s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.785e-03, size: 448, ETA: 2:41:59
2025-09-01 07:16:54.629 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:16:54.668 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch44
2025-09-01 07:16:57.564 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 44/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.144s, data_time: 0.061s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.783e-03, size: 512, ETA: 2:41:57
2025-09-01 07:17:00.501 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 44/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.021s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.781e-03, size: 448, ETA: 2:41:55
2025-09-01 07:17:03.150 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 44/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.127s, data_time: 0.029s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.779e-03, size: 544, ETA: 2:41:51
2025-09-01 07:17:06.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 44/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.144s, data_time: 0.059s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.778e-03, size: 576, ETA: 2:41:50
2025-09-01 07:17:08.948 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 44/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.132s, data_time: 0.016s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.776e-03, size: 256, ETA: 2:41:47
2025-09-01 07:17:11.829 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 44/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.140s, data_time: 0.045s, total_loss: 7.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.774e-03, size: 256, ETA: 2:41:45
2025-09-01 07:17:13.180 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:17:13.227 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch45
2025-09-01 07:17:15.931 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 45/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.055s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.772e-03, size: 448, ETA: 2:41:43
2025-09-01 07:17:18.728 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 45/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.770e-03, size: 320, ETA: 2:41:41
2025-09-01 07:17:21.726 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 45/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.149s, data_time: 0.068s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 9.768e-03, size: 352, ETA: 2:41:42
2025-09-01 07:17:24.492 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 45/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.138s, data_time: 0.054s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.766e-03, size: 480, ETA: 2:41:39
2025-09-01 07:17:27.288 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 45/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.764e-03, size: 256, ETA: 2:41:37
2025-09-01 07:17:30.047 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 45/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.129s, data_time: 0.042s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.762e-03, size: 416, ETA: 2:41:32
2025-09-01 07:17:31.300 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:17:37.210 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:17:39.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:17:40.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4555
2025-09-01 07:17:40.648 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4022
2025-09-01 07:17:40.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2356
2025-09-01 07:17:40.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3644
2025-09-01 07:17:40.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:17:40.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:17:40.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.456
2025-09-01 07:17:40.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.402
2025-09-01 07:17:40.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.236
2025-09-01 07:17:40.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.364
2025-09-01 07:17:40.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:17:40.789 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:17:40.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:17:40.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:17:40.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:17:40.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:17:40.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:17:40.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:17:40.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:17:42.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:17:43.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:17:45.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:17:47.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:17:48.751 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:17:50.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:17:51.911 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:17:53.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:17:55.097 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:17:55.097 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-09-01 07:17:55.097 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.36
2025-09-01 07:17:55.097 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:17:55.124 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.94 ms, Average inference time: 2.31 ms

2025-09-01 07:17:55.126 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:17:55.156 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:17:55.189 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch46
2025-09-01 07:17:57.703 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 46/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.124s, data_time: 0.043s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.760e-03, size: 352, ETA: 2:41:24
2025-09-01 07:18:00.494 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 46/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 9.758e-03, size: 288, ETA: 2:41:23
2025-09-01 07:18:03.386 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 46/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.056s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 9.756e-03, size: 288, ETA: 2:41:21
2025-09-01 07:18:06.154 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 46/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 9.754e-03, size: 256, ETA: 2:41:18
2025-09-01 07:18:08.873 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 46/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.133s, data_time: 0.054s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.752e-03, size: 416, ETA: 2:41:15
2025-09-01 07:18:11.669 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 46/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.041s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.751e-03, size: 288, ETA: 2:41:12
2025-09-01 07:18:12.951 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:18:12.993 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch47
2025-09-01 07:18:15.891 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 47/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.144s, data_time: 0.065s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 9.748e-03, size: 416, ETA: 2:41:11
2025-09-01 07:18:18.673 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 47/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.138s, data_time: 0.055s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.746e-03, size: 512, ETA: 2:41:09
2025-09-01 07:18:21.469 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 47/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.130s, data_time: 0.049s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.744e-03, size: 576, ETA: 2:41:05
2025-09-01 07:18:24.221 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 47/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.127s, data_time: 0.042s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 9.742e-03, size: 256, ETA: 2:41:00
2025-09-01 07:18:27.124 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 47/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.144s, data_time: 0.059s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.740e-03, size: 448, ETA: 2:40:59
2025-09-01 07:18:30.001 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 47/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.142s, data_time: 0.059s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.738e-03, size: 416, ETA: 2:40:58
2025-09-01 07:18:31.267 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:18:31.319 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch48
2025-09-01 07:18:34.163 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 48/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.134s, data_time: 0.039s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.736e-03, size: 288, ETA: 2:40:54
2025-09-01 07:18:36.907 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 48/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.129s, data_time: 0.037s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.734e-03, size: 544, ETA: 2:40:50
2025-09-01 07:18:39.748 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 48/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.732e-03, size: 480, ETA: 2:40:47
2025-09-01 07:18:42.466 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 48/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.132s, data_time: 0.037s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 9.730e-03, size: 288, ETA: 2:40:44
2025-09-01 07:18:45.255 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 48/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.133s, data_time: 0.048s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.728e-03, size: 288, ETA: 2:40:40
2025-09-01 07:18:48.078 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 48/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.130s, data_time: 0.045s, total_loss: 8.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 0.8, lr: 9.726e-03, size: 448, ETA: 2:40:36
2025-09-01 07:18:49.354 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:18:49.468 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch49
2025-09-01 07:18:52.126 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 49/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.129s, data_time: 0.034s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 9.723e-03, size: 384, ETA: 2:40:30
2025-09-01 07:18:54.968 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 49/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.057s, total_loss: 8.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.721e-03, size: 512, ETA: 2:40:27
2025-09-01 07:18:57.878 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 49/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.719e-03, size: 480, ETA: 2:40:26
2025-09-01 07:19:00.889 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 49/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.148s, data_time: 0.063s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.717e-03, size: 288, ETA: 2:40:27
2025-09-01 07:19:03.712 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 49/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.055s, total_loss: 7.3, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.715e-03, size: 288, ETA: 2:40:25
2025-09-01 07:19:06.438 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 49/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.056s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.713e-03, size: 544, ETA: 2:40:22
2025-09-01 07:19:07.699 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:19:07.761 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch50
2025-09-01 07:19:10.628 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 50/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.136s, data_time: 0.034s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.710e-03, size: 576, ETA: 2:40:18
2025-09-01 07:19:13.407 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 50/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.135s, data_time: 0.035s, total_loss: 8.2, iou_loss: 3.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.708e-03, size: 288, ETA: 2:40:15
2025-09-01 07:19:16.447 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 50/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.150s, data_time: 0.066s, total_loss: 8.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 9.706e-03, size: 288, ETA: 2:40:16
2025-09-01 07:19:19.152 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 50/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.131s, data_time: 0.050s, total_loss: 8.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.704e-03, size: 544, ETA: 2:40:12
2025-09-01 07:19:21.892 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 50/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.128s, data_time: 0.039s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 9.702e-03, size: 384, ETA: 2:40:08
2025-09-01 07:19:24.708 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 50/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.132s, data_time: 0.011s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 9.700e-03, size: 384, ETA: 2:40:05
2025-09-01 07:19:25.923 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:19:31.858 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:19:34.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:19:36.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5021
2025-09-01 07:19:36.336 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3654
2025-09-01 07:19:36.382 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2546
2025-09-01 07:19:36.383 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3740
2025-09-01 07:19:36.383 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:19:36.383 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.502
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.365
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.255
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.374
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:19:36.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:19:36.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:19:38.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:19:40.472 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:19:42.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:19:44.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:19:46.728 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:19:48.776 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:19:50.808 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:19:52.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:19:54.997 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:19:54.998 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-09-01 07:19:54.998 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-09-01 07:19:54.998 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:19:55.024 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.95 ms, Average inference time: 2.31 ms

2025-09-01 07:19:55.025 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:19:55.056 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:19:55.089 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch51
2025-09-01 07:19:57.470 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 51/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.118s, data_time: 0.041s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 9.697e-03, size: 288, ETA: 2:39:57
2025-09-01 07:20:00.366 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 51/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 9.695e-03, size: 576, ETA: 2:39:55
2025-09-01 07:20:03.159 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 51/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.028s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 9.693e-03, size: 416, ETA: 2:39:53
2025-09-01 07:20:06.099 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 51/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.146s, data_time: 0.066s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.691e-03, size: 320, ETA: 2:39:53
2025-09-01 07:20:08.858 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 51/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.6, lr: 9.689e-03, size: 416, ETA: 2:39:50
2025-09-01 07:20:11.683 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 51/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.054s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.687e-03, size: 320, ETA: 2:39:48
2025-09-01 07:20:12.893 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:20:12.931 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch52
2025-09-01 07:20:15.753 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 52/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.137s, data_time: 0.050s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.684e-03, size: 512, ETA: 2:39:45
2025-09-01 07:20:18.544 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 52/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.055s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.681e-03, size: 416, ETA: 2:39:43
2025-09-01 07:20:21.354 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 52/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.138s, data_time: 0.048s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.679e-03, size: 480, ETA: 2:39:40
2025-09-01 07:20:24.114 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 52/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.130s, data_time: 0.050s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.677e-03, size: 416, ETA: 2:39:37
2025-09-01 07:20:27.009 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 52/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.144s, data_time: 0.064s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.675e-03, size: 448, ETA: 2:39:36
2025-09-01 07:20:29.859 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 52/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 9.673e-03, size: 544, ETA: 2:39:34
2025-09-01 07:20:31.017 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:20:31.055 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch53
2025-09-01 07:20:33.909 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 53/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.140s, data_time: 0.021s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.670e-03, size: 320, ETA: 2:39:30
2025-09-01 07:20:36.716 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 53/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.005s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.668e-03, size: 288, ETA: 2:39:28
2025-09-01 07:20:39.466 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 53/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.666e-03, size: 352, ETA: 2:39:25
2025-09-01 07:20:42.296 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 53/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.2, lr: 9.663e-03, size: 512, ETA: 2:39:23
2025-09-01 07:20:45.194 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 53/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.144s, data_time: 0.064s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.661e-03, size: 352, ETA: 2:39:22
2025-09-01 07:20:48.063 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 53/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 9.659e-03, size: 544, ETA: 2:39:21
2025-09-01 07:20:49.269 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:20:49.295 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch54
2025-09-01 07:20:52.058 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 54/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.656e-03, size: 352, ETA: 2:39:17
2025-09-01 07:20:55.084 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 54/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.138s, data_time: 0.037s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 9.654e-03, size: 320, ETA: 2:39:15
2025-09-01 07:20:57.931 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 54/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.128s, data_time: 0.035s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.651e-03, size: 544, ETA: 2:39:10
2025-09-01 07:21:00.718 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 54/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.126s, data_time: 0.009s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.649e-03, size: 256, ETA: 2:39:06
2025-09-01 07:21:03.565 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 54/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.137s, data_time: 0.041s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.647e-03, size: 320, ETA: 2:39:03
2025-09-01 07:21:06.536 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 54/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.645e-03, size: 512, ETA: 2:39:00
2025-09-01 07:21:07.677 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:21:07.763 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch55
2025-09-01 07:21:10.539 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 55/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.127s, data_time: 0.010s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.3, lr: 9.642e-03, size: 352, ETA: 2:38:53
2025-09-01 07:21:13.461 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 55/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.639e-03, size: 544, ETA: 2:38:51
2025-09-01 07:21:16.238 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 55/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.637e-03, size: 352, ETA: 2:38:48
2025-09-01 07:21:19.113 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 55/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.139s, data_time: 0.008s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 9.635e-03, size: 288, ETA: 2:38:46
2025-09-01 07:21:21.960 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 55/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.141s, data_time: 0.003s, total_loss: 8.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 9.633e-03, size: 480, ETA: 2:38:45
2025-09-01 07:21:24.841 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 55/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.143s, data_time: 0.004s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.630e-03, size: 512, ETA: 2:38:44
2025-09-01 07:21:26.169 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:21:32.319 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:21:34.766 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:21:36.734 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4722
2025-09-01 07:21:36.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4102
2025-09-01 07:21:36.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2386
2025-09-01 07:21:36.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3737
2025-09-01 07:21:36.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:21:36.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:21:36.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.472
2025-09-01 07:21:36.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.410
2025-09-01 07:21:36.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.239
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.374
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:21:36.960 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:21:39.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:21:41.305 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:21:43.501 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:21:45.685 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:21:47.935 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:21:50.082 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:21:52.205 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:21:54.322 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:21:56.493 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:21:56.493 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.15
2025-09-01 07:21:56.493 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-09-01 07:21:56.493 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:21:56.522 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.98 ms, Average inference time: 2.37 ms

2025-09-01 07:21:56.523 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:21:56.548 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:21:56.580 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch56
2025-09-01 07:21:59.038 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 56/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.116s, data_time: 0.012s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.627e-03, size: 416, ETA: 2:38:37
2025-09-01 07:22:01.796 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 56/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.127s, data_time: 0.022s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.625e-03, size: 576, ETA: 2:38:32
2025-09-01 07:22:04.567 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 56/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.623e-03, size: 448, ETA: 2:38:30
2025-09-01 07:22:07.404 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 56/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.134s, data_time: 0.022s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.620e-03, size: 416, ETA: 2:38:27
2025-09-01 07:22:10.200 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 56/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.127s, 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: 9.618e-03, size: 256, ETA: 2:38:23
2025-09-01 07:22:12.938 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 56/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.124s, data_time: 0.015s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.616e-03, size: 544, ETA: 2:38:18
2025-09-01 07:22:14.164 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:22:14.277 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch57
2025-09-01 07:22:17.077 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 57/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.134s, data_time: 0.039s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.612e-03, size: 448, ETA: 2:38:13
2025-09-01 07:22:19.941 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 57/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.610e-03, size: 576, ETA: 2:38:12
2025-09-01 07:22:22.727 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 57/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.139s, data_time: 0.060s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 9.608e-03, size: 448, ETA: 2:38:10
2025-09-01 07:22:25.599 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 57/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.127s, data_time: 0.018s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.605e-03, size: 352, ETA: 2:38:05
2025-09-01 07:22:28.441 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 57/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.603e-03, size: 256, ETA: 2:38:00
2025-09-01 07:22:31.129 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 57/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.124s, data_time: 0.028s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 9.601e-03, size: 352, ETA: 2:37:56
2025-09-01 07:22:32.304 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:22:32.441 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch58
2025-09-01 07:22:35.252 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 58/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.132s, data_time: 0.042s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.597e-03, size: 544, ETA: 2:37:51
2025-09-01 07:22:38.022 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 58/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.138s, data_time: 0.056s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.595e-03, size: 544, ETA: 2:37:48
2025-09-01 07:22:40.870 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 58/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.142s, data_time: 0.063s, total_loss: 9.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 5.0, cls_loss: 1.1, lr: 9.592e-03, size: 480, ETA: 2:37:47
2025-09-01 07:22:43.694 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 58/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.140s, data_time: 0.062s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.590e-03, size: 288, ETA: 2:37:45
2025-09-01 07:22:46.519 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 58/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.588e-03, size: 352, ETA: 2:37:43
2025-09-01 07:22:49.465 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 58/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.147s, data_time: 0.069s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.585e-03, size: 512, ETA: 2:37:43
2025-09-01 07:22:50.696 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:22:50.835 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch59
2025-09-01 07:22:53.507 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 59/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.127s, data_time: 0.012s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.582e-03, size: 288, ETA: 2:37:37
2025-09-01 07:22:56.276 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 59/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.135s, data_time: 0.029s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.579e-03, size: 448, ETA: 2:37:34
2025-09-01 07:22:59.133 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 59/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.577e-03, size: 416, ETA: 2:37:32
2025-09-01 07:23:02.037 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 59/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.142s, data_time: 0.015s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.575e-03, size: 320, ETA: 2:37:31
2025-09-01 07:23:04.735 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 59/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.131s, data_time: 0.028s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.572e-03, size: 352, ETA: 2:37:27
2025-09-01 07:23:07.588 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 59/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.135s, data_time: 0.021s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.570e-03, size: 352, ETA: 2:37:25
2025-09-01 07:23:08.835 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:23:08.950 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch60
2025-09-01 07:23:11.802 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 60/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.137s, data_time: 0.052s, total_loss: 8.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 1.0, lr: 9.566e-03, size: 576, ETA: 2:37:21
2025-09-01 07:23:14.552 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 60/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.135s, data_time: 0.050s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.564e-03, size: 576, ETA: 2:37:18
2025-09-01 07:23:17.316 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 60/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.137s, data_time: 0.060s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 9.561e-03, size: 352, ETA: 2:37:15
2025-09-01 07:23:20.179 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 60/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.559e-03, size: 384, ETA: 2:37:14
2025-09-01 07:23:23.087 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 60/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.144s, data_time: 0.063s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.556e-03, size: 352, ETA: 2:37:13
2025-09-01 07:23:25.880 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 60/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.139s, data_time: 0.061s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.554e-03, size: 320, ETA: 2:37:11
2025-09-01 07:23:27.205 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:23:33.150 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:23:36.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:23:38.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5213
2025-09-01 07:23:38.724 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3871
2025-09-01 07:23:38.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2343
2025-09-01 07:23:38.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3809
2025-09-01 07:23:38.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:23:38.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:23:38.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.521
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.387
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.234
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.381
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:23:38.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:23:38.815 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:23:41.457 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:23:44.012 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:23:46.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:23:49.156 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:23:51.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:23:54.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:23:56.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:23:59.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:24:02.380 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:24:02.380 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-09-01 07:24:02.380 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.38
2025-09-01 07:24:02.380 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:24:02.407 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.96 ms, Average inference time: 2.33 ms

2025-09-01 07:24:02.410 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:24:02.437 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:24:02.470 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch61
2025-09-01 07:24:04.965 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 61/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.123s, data_time: 0.040s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 9.550e-03, size: 448, ETA: 2:37:05
2025-09-01 07:24:07.810 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 61/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.138s, data_time: 0.010s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 9.548e-03, size: 352, ETA: 2:37:03
2025-09-01 07:24:10.610 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 61/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.138s, data_time: 0.012s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 9.545e-03, size: 448, ETA: 2:37:01
2025-09-01 07:24:13.461 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 61/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.140s, data_time: 0.044s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 9.543e-03, size: 384, ETA: 2:36:59
2025-09-01 07:24:16.239 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 61/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.135s, 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: 9.540e-03, size: 384, ETA: 2:36:56
2025-09-01 07:24:19.029 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 61/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.137s, data_time: 0.028s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 9.538e-03, size: 320, ETA: 2:36:54
2025-09-01 07:24:20.223 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:24:20.386 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch62
2025-09-01 07:24:23.091 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 62/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.133s, data_time: 0.045s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.534e-03, size: 576, ETA: 2:36:49
2025-09-01 07:24:25.911 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 62/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.140s, data_time: 0.056s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.532e-03, size: 480, ETA: 2:36:47
2025-09-01 07:24:28.730 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 62/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 7.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.529e-03, size: 480, ETA: 2:36:44
2025-09-01 07:24:31.580 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 62/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.142s, data_time: 0.063s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.526e-03, size: 512, ETA: 2:36:43
2025-09-01 07:24:34.442 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 62/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.524e-03, size: 256, ETA: 2:36:41
2025-09-01 07:24:37.281 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 62/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.137s, data_time: 0.043s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 9.521e-03, size: 480, ETA: 2:36:38
2025-09-01 07:24:38.557 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:24:38.602 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch63
2025-09-01 07:24:41.443 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 63/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.518e-03, size: 448, ETA: 2:36:36
2025-09-01 07:24:44.214 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 63/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.138s, data_time: 0.052s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.515e-03, size: 256, ETA: 2:36:34
2025-09-01 07:24:46.989 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 63/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.512e-03, size: 320, ETA: 2:36:31
2025-09-01 07:24:49.684 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 63/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.133s, data_time: 0.050s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 9.510e-03, size: 576, ETA: 2:36:28
2025-09-01 07:24:52.499 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 63/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.138s, data_time: 0.055s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.507e-03, size: 256, ETA: 2:36:26
2025-09-01 07:24:55.406 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 63/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.145s, data_time: 0.062s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.505e-03, size: 512, ETA: 2:36:25
2025-09-01 07:24:56.651 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:24:56.687 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch64
2025-09-01 07:24:59.433 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 64/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.134s, data_time: 0.056s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.501e-03, size: 416, ETA: 2:36:21
2025-09-01 07:25:02.285 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 64/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.133s, data_time: 0.056s, total_loss: 8.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.8, lr: 9.498e-03, size: 544, ETA: 2:36:18
2025-09-01 07:25:05.175 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 64/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.496e-03, size: 320, ETA: 2:36:15
2025-09-01 07:25:08.035 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 64/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.493e-03, size: 544, ETA: 2:36:14
2025-09-01 07:25:10.793 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 64/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.133s, data_time: 0.046s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 9.490e-03, size: 512, ETA: 2:36:10
2025-09-01 07:25:13.586 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 64/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.7Gb, iter_time: 0.128s, data_time: 0.009s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.488e-03, size: 320, ETA: 2:36:06
2025-09-01 07:25:14.771 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:25:14.941 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch65
2025-09-01 07:25:17.765 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 65/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.122s, data_time: 0.005s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.4, lr: 9.484e-03, size: 288, ETA: 2:35:59
2025-09-01 07:25:20.673 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 65/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.481e-03, size: 448, ETA: 2:35:55
2025-09-01 07:25:23.499 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 65/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.479e-03, size: 576, ETA: 2:35:53
2025-09-01 07:25:26.281 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 65/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 8.8, iou_loss: 4.0, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.6, lr: 9.476e-03, size: 352, ETA: 2:35:48
2025-09-01 07:25:29.045 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 65/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.121s, data_time: 0.011s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 9.473e-03, size: 352, ETA: 2:35:43
2025-09-01 07:25:31.883 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 65/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.125s, data_time: 0.039s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.471e-03, size: 544, ETA: 2:35:38
2025-09-01 07:25:33.123 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:25:39.117 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:25:50.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:25:59.474 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.3083
2025-09-01 07:26:00.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3519
2025-09-01 07:26:00.570 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.1748
2025-09-01 07:26:00.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.2783
2025-09-01 07:26:00.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:26:00.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:26:00.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.308
2025-09-01 07:26:00.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.352
2025-09-01 07:26:00.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.175
2025-09-01 07:26:00.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.278
2025-09-01 07:26:00.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:26:00.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:26:00.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:26:00.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:26:00.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:26:00.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:26:00.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:26:00.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:26:00.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:26:10.543 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:26:20.648 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:26:30.587 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:26:40.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:26:50.622 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:27:00.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:27:10.501 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:27:20.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:27:30.520 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:27:30.521 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.12
2025-09-01 07:27:30.521 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.28
2025-09-01 07:27:30.521 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:27:30.547 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 1.02 ms, Average inference time: 2.41 ms

2025-09-01 07:27:30.550 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:27:30.571 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:27:30.602 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch66
2025-09-01 07:27:33.088 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 66/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.116s, data_time: 0.010s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.467e-03, size: 352, ETA: 2:35:31
2025-09-01 07:27:35.972 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 66/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, 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: 9.464e-03, size: 352, ETA: 2:35:28
2025-09-01 07:27:38.842 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 66/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.461e-03, size: 416, ETA: 2:35:25
2025-09-01 07:27:41.719 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 66/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 9.459e-03, size: 576, ETA: 2:35:22
2025-09-01 07:27:44.511 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 66/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.456e-03, size: 288, ETA: 2:35:18
2025-09-01 07:27:47.291 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 66/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.042s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.453e-03, size: 256, ETA: 2:35:16
2025-09-01 07:27:48.625 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:27:48.667 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch67
2025-09-01 07:27:51.398 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 67/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.134s, data_time: 0.007s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.449e-03, size: 352, ETA: 2:35:12
2025-09-01 07:27:54.172 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 67/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.013s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 9.446e-03, size: 512, ETA: 2:35:09
2025-09-01 07:27:57.091 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 67/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.145s, data_time: 0.038s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 9.444e-03, size: 256, ETA: 2:35:08
2025-09-01 07:27:59.983 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 67/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.141s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.441e-03, size: 448, ETA: 2:35:06
2025-09-01 07:28:02.783 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 67/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.028s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.438e-03, size: 576, ETA: 2:35:04
2025-09-01 07:28:05.475 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 67/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.129s, data_time: 0.027s, total_loss: 7.4, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.435e-03, size: 288, ETA: 2:35:00
2025-09-01 07:28:06.714 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:28:06.816 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch68
2025-09-01 07:28:09.581 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 68/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.126s, data_time: 0.032s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.431e-03, size: 256, ETA: 2:34:55
2025-09-01 07:28:12.546 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 68/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.027s, total_loss: 6.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.429e-03, size: 320, ETA: 2:34:52
2025-09-01 07:28:15.367 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 68/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.426e-03, size: 288, ETA: 2:34:49
2025-09-01 07:28:18.178 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 68/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.132s, data_time: 0.020s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.423e-03, size: 256, ETA: 2:34:46
2025-09-01 07:28:21.038 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 68/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.420e-03, size: 544, ETA: 2:34:43
2025-09-01 07:28:23.762 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 68/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.417e-03, size: 544, ETA: 2:34:40
2025-09-01 07:28:24.981 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:28:25.059 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch69
2025-09-01 07:28:27.929 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 69/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.140s, data_time: 0.033s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.413e-03, size: 512, ETA: 2:34:36
2025-09-01 07:28:30.790 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 69/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.141s, 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: 9.410e-03, size: 576, ETA: 2:34:34
2025-09-01 07:28:33.501 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 69/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.132s, data_time: 0.016s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.408e-03, size: 480, ETA: 2:34:31
2025-09-01 07:28:36.331 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 69/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.045s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.405e-03, size: 416, ETA: 2:34:29
2025-09-01 07:28:39.184 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 69/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.402e-03, size: 576, ETA: 2:34:28
2025-09-01 07:28:42.189 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 69/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.150s, data_time: 0.063s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.399e-03, size: 384, ETA: 2:34:27
2025-09-01 07:28:43.411 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:28:43.475 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch70
2025-09-01 07:28:46.394 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 70/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.144s, data_time: 0.060s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.395e-03, size: 288, ETA: 2:34:25
2025-09-01 07:28:49.081 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 70/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.133s, data_time: 0.056s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.2, lr: 9.392e-03, size: 384, ETA: 2:34:21
2025-09-01 07:28:51.958 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 70/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.143s, data_time: 0.067s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.389e-03, size: 416, ETA: 2:34:20
2025-09-01 07:28:54.656 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 70/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.054s, total_loss: 7.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.386e-03, size: 480, ETA: 2:34:17
2025-09-01 07:28:57.375 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 70/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.383e-03, size: 352, ETA: 2:34:14
2025-09-01 07:29:00.257 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 70/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.381e-03, size: 416, ETA: 2:34:12
2025-09-01 07:29:01.457 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:29:07.650 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:29:10.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:29:11.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5243
2025-09-01 07:29:12.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4279
2025-09-01 07:29:12.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2424
2025-09-01 07:29:12.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3982
2025-09-01 07:29:12.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:29:12.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:29:12.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.524
2025-09-01 07:29:12.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.428
2025-09-01 07:29:12.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.242
2025-09-01 07:29:12.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.398
2025-09-01 07:29:12.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:29:12.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:29:12.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:29:12.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:29:12.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:29:12.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:29:12.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:29:12.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:29:12.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:29:14.251 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:29:16.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:29:18.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:29:20.267 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:29:22.282 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:29:24.311 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:29:26.327 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:29:28.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:29:30.492 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:29:30.492 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-09-01 07:29:30.492 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-09-01 07:29:30.492 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:29:30.516 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.94 ms, Average inference time: 2.33 ms

2025-09-01 07:29:30.518 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:29:30.547 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:29:30.579 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch71
2025-09-01 07:29:33.010 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 71/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.120s, data_time: 0.033s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.376e-03, size: 256, ETA: 2:34:06
2025-09-01 07:29:35.853 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 71/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 9.373e-03, size: 416, ETA: 2:34:04
2025-09-01 07:29:38.684 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 71/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.371e-03, size: 512, ETA: 2:34:02
2025-09-01 07:29:41.391 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 71/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.368e-03, size: 352, ETA: 2:33:59
2025-09-01 07:29:44.188 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 71/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.040s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.365e-03, size: 384, ETA: 2:33:56
2025-09-01 07:29:46.939 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 71/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.133s, data_time: 0.027s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 9.362e-03, size: 320, ETA: 2:33:53
2025-09-01 07:29:48.203 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:29:48.282 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch72
2025-09-01 07:29:51.157 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 72/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 9.358e-03, size: 544, ETA: 2:33:50
2025-09-01 07:29:53.919 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 72/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.137s, data_time: 0.053s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.355e-03, size: 544, ETA: 2:33:47
2025-09-01 07:29:56.873 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 72/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.147s, data_time: 0.068s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.352e-03, size: 544, ETA: 2:33:46
2025-09-01 07:29:59.799 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 72/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.145s, data_time: 0.060s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.349e-03, size: 352, ETA: 2:33:45
2025-09-01 07:30:02.667 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 72/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 9.346e-03, size: 512, ETA: 2:33:44
2025-09-01 07:30:05.416 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 72/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 9.343e-03, size: 256, ETA: 2:33:41
2025-09-01 07:30:06.822 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:30:06.930 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch73
2025-09-01 07:30:09.802 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 73/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.143s, data_time: 0.060s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.338e-03, size: 512, ETA: 2:33:39
2025-09-01 07:30:12.670 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 73/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.143s, data_time: 0.060s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.335e-03, size: 448, ETA: 2:33:38
2025-09-01 07:30:15.493 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 73/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.332e-03, size: 352, ETA: 2:33:36
2025-09-01 07:30:18.289 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 73/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.329e-03, size: 448, ETA: 2:33:34
2025-09-01 07:30:21.040 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 73/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.326e-03, size: 416, ETA: 2:33:31
2025-09-01 07:30:23.781 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 73/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.057s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.323e-03, size: 512, ETA: 2:33:29
2025-09-01 07:30:24.998 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:30:25.037 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch74
2025-09-01 07:30:27.822 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 74/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.055s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.319e-03, size: 512, ETA: 2:33:25
2025-09-01 07:30:30.713 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 74/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.143s, data_time: 0.065s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.316e-03, size: 256, ETA: 2:33:23
2025-09-01 07:30:33.572 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 74/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.142s, data_time: 0.056s, total_loss: 7.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 9.313e-03, size: 384, ETA: 2:33:22
2025-09-01 07:30:36.417 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 74/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.141s, data_time: 0.064s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.310e-03, size: 288, ETA: 2:33:20
2025-09-01 07:30:39.318 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 74/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.144s, data_time: 0.064s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 9.307e-03, size: 256, ETA: 2:33:18
2025-09-01 07:30:42.061 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 74/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 7.7, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 9.304e-03, size: 288, ETA: 2:33:15
2025-09-01 07:30:43.335 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:30:43.372 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch75
2025-09-01 07:30:46.221 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 75/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.299e-03, size: 256, ETA: 2:33:12
2025-09-01 07:30:49.092 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 75/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.296e-03, size: 384, ETA: 2:33:11
2025-09-01 07:30:51.879 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 75/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.037s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.293e-03, size: 512, ETA: 2:33:08
2025-09-01 07:30:54.706 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 75/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.042s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 9.290e-03, size: 480, ETA: 2:33:06
2025-09-01 07:30:57.568 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 75/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.140s, data_time: 0.050s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 9.287e-03, size: 480, ETA: 2:33:03
2025-09-01 07:31:00.452 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 75/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.143s, data_time: 0.030s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 9.284e-03, size: 288, ETA: 2:33:02
2025-09-01 07:31:01.676 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:31:07.482 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:31:10.731 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:31:12.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4548
2025-09-01 07:31:13.389 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4404
2025-09-01 07:31:13.475 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2289
2025-09-01 07:31:13.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3747
2025-09-01 07:31:13.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:31:13.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:31:13.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.455
2025-09-01 07:31:13.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.440
2025-09-01 07:31:13.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.229
2025-09-01 07:31:13.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.375
2025-09-01 07:31:13.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:31:13.480 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:31:13.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:31:13.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:31:13.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:31:13.482 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:31:13.482 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:31:13.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:31:13.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:31:16.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:31:18.795 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:31:21.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:31:24.163 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:31:26.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:31:29.487 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:31:32.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:31:34.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:31:37.469 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:31:37.469 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-09-01 07:31:37.469 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-09-01 07:31:37.469 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:31:37.494 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.97 ms, Average inference time: 2.36 ms

2025-09-01 07:31:37.496 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:31:37.523 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:31:37.553 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch76
2025-09-01 07:31:39.958 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 76/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.119s, data_time: 0.042s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.280e-03, size: 512, ETA: 2:32:55
2025-09-01 07:31:42.779 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 76/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.276e-03, size: 256, ETA: 2:32:53
2025-09-01 07:31:45.638 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 76/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.026s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.273e-03, size: 544, ETA: 2:32:50
2025-09-01 07:31:48.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 76/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.132s, data_time: 0.013s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.270e-03, size: 512, ETA: 2:32:47
2025-09-01 07:31:51.341 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 76/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 8.3, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.267e-03, size: 288, ETA: 2:32:44
2025-09-01 07:31:54.075 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 76/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 9.264e-03, size: 288, ETA: 2:32:41
2025-09-01 07:31:55.227 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:31:55.296 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch77
2025-09-01 07:31:58.164 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 77/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.128s, data_time: 0.035s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.259e-03, size: 480, ETA: 2:32:36
2025-09-01 07:32:01.118 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 77/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.124s, data_time: 0.033s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 9.256e-03, size: 288, ETA: 2:32:31
2025-09-01 07:32:04.104 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 77/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.129s, data_time: 0.030s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.253e-03, size: 416, ETA: 2:32:28
2025-09-01 07:32:06.711 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 77/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.118s, data_time: 0.013s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.250e-03, size: 256, ETA: 2:32:23
2025-09-01 07:32:09.560 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 77/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.136s, data_time: 0.055s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.247e-03, size: 288, ETA: 2:32:20
2025-09-01 07:32:12.354 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 77/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.130s, data_time: 0.051s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.244e-03, size: 256, ETA: 2:32:17
2025-09-01 07:32:13.706 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:32:13.742 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch78
2025-09-01 07:32:16.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 78/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.127s, data_time: 0.045s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.239e-03, size: 544, ETA: 2:32:12
2025-09-01 07:32:19.322 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 78/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.133s, data_time: 0.037s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 9.236e-03, size: 576, ETA: 2:32:09
2025-09-01 07:32:22.162 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 78/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.129s, data_time: 0.007s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.233e-03, size: 448, ETA: 2:32:05
2025-09-01 07:32:25.060 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 78/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.229e-03, size: 384, ETA: 2:32:02
2025-09-01 07:32:27.986 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 78/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, 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: 0.7, lr: 9.226e-03, size: 512, ETA: 2:31:59
2025-09-01 07:32:30.790 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 78/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 9.223e-03, size: 480, ETA: 2:31:55
2025-09-01 07:32:32.010 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:32:32.158 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch79
2025-09-01 07:32:34.942 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 79/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.125s, data_time: 0.004s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.218e-03, size: 544, ETA: 2:31:49
2025-09-01 07:32:37.634 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 79/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 9.215e-03, size: 512, ETA: 2:31:45
2025-09-01 07:32:40.484 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 79/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.014s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.212e-03, size: 576, ETA: 2:31:42
2025-09-01 07:32:43.276 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 79/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.014s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 9.209e-03, size: 320, ETA: 2:31:40
2025-09-01 07:32:46.164 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 79/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.142s, data_time: 0.017s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.206e-03, size: 448, ETA: 2:31:38
2025-09-01 07:32:48.974 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 79/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 7.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 9.202e-03, size: 256, ETA: 2:31:36
2025-09-01 07:32:50.180 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:32:50.317 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch80
2025-09-01 07:32:53.184 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 80/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 9.198e-03, size: 384, ETA: 2:31:32
2025-09-01 07:32:55.925 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 80/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.006s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.194e-03, size: 384, ETA: 2:31:29
2025-09-01 07:32:58.816 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 80/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.144s, data_time: 0.055s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 9.191e-03, size: 448, ETA: 2:31:28
2025-09-01 07:33:01.639 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 80/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.133s, data_time: 0.051s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.188e-03, size: 480, ETA: 2:31:25
2025-09-01 07:33:04.428 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 80/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.028s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.184e-03, size: 512, ETA: 2:31:22
2025-09-01 07:33:07.199 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 80/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.129s, data_time: 0.024s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.181e-03, size: 448, ETA: 2:31:18
2025-09-01 07:33:08.489 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:33:14.301 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:33:16.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:33:17.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5251
2025-09-01 07:33:17.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4312
2025-09-01 07:33:17.704 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3163
2025-09-01 07:33:17.704 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4242
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.525
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.431
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.316
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.424
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:33:17.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:33:17.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:33:17.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:33:17.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:33:17.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:33:17.706 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:33:19.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:33:20.938 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:33:22.509 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:33:24.013 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:33:25.557 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:33:27.070 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:33:28.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:33:30.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:33:31.678 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:33:31.678 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-09-01 07:33:31.678 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-09-01 07:33:31.678 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:33:31.718 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.93 ms, Average inference time: 2.31 ms

2025-09-01 07:33:31.719 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:33:31.747 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:33:31.778 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch81
2025-09-01 07:33:34.257 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 81/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.121s, data_time: 0.033s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 9.176e-03, size: 448, ETA: 2:31:13
2025-09-01 07:33:36.980 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 81/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.057s, total_loss: 7.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.1, lr: 9.173e-03, size: 448, ETA: 2:31:10
2025-09-01 07:33:39.877 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 81/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.144s, data_time: 0.062s, total_loss: 8.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 9.170e-03, size: 256, ETA: 2:31:09
2025-09-01 07:33:42.615 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 81/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.132s, data_time: 0.024s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.166e-03, size: 480, ETA: 2:31:05
2025-09-01 07:33:45.400 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 81/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.041s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.163e-03, size: 320, ETA: 2:31:03
2025-09-01 07:33:48.343 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 81/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.145s, data_time: 0.063s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.160e-03, size: 256, ETA: 2:31:01
2025-09-01 07:33:49.466 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:33:49.624 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch82
2025-09-01 07:33:52.486 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 82/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.136s, data_time: 0.050s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 9.155e-03, size: 544, ETA: 2:30:57
2025-09-01 07:33:55.383 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 82/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.133s, data_time: 0.036s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.152e-03, size: 320, ETA: 2:30:54
2025-09-01 07:33:58.258 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 82/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.137s, data_time: 0.043s, total_loss: 7.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 9.148e-03, size: 352, ETA: 2:30:51
2025-09-01 07:34:01.067 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 82/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.145e-03, size: 256, ETA: 2:30:49
2025-09-01 07:34:03.928 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 82/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.056s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.142e-03, size: 384, ETA: 2:30:47
2025-09-01 07:34:06.756 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 82/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.039s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.138e-03, size: 576, ETA: 2:30:44
2025-09-01 07:34:08.016 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:34:08.074 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch83
2025-09-01 07:34:10.889 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 83/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.8Gb, iter_time: 0.129s, data_time: 0.008s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 9.133e-03, size: 480, ETA: 2:30:40
2025-09-01 07:34:13.620 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 83/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.131s, data_time: 0.044s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.130e-03, size: 320, ETA: 2:30:37
2025-09-01 07:34:16.469 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 83/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.054s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 9.127e-03, size: 448, ETA: 2:30:34
2025-09-01 07:34:19.391 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 83/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.142s, data_time: 0.013s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 9.123e-03, size: 416, ETA: 2:30:32
2025-09-01 07:34:22.206 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 83/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 9.120e-03, size: 288, ETA: 2:30:30
2025-09-01 07:34:25.133 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 83/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.144s, 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: 9.116e-03, size: 352, ETA: 2:30:28
2025-09-01 07:34:26.392 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:34:26.513 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch84
2025-09-01 07:34:29.335 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 84/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.112e-03, size: 576, ETA: 2:30:24
2025-09-01 07:34:32.153 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 84/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.009s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 9.108e-03, size: 288, ETA: 2:30:22
2025-09-01 07:34:34.930 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 84/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.135s, data_time: 0.058s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.105e-03, size: 544, ETA: 2:30:19
2025-09-01 07:34:37.819 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 84/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.037s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 9.101e-03, size: 352, ETA: 2:30:17
2025-09-01 07:34:40.675 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 84/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.129s, 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: 9.098e-03, size: 416, ETA: 2:30:13
2025-09-01 07:34:43.474 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 84/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 9.094e-03, size: 416, ETA: 2:30:10
2025-09-01 07:34:44.699 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:34:44.764 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch85
2025-09-01 07:34:47.544 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 85/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.124s, data_time: 0.014s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.089e-03, size: 544, ETA: 2:30:05
2025-09-01 07:34:50.302 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 85/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.126s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.086e-03, size: 544, ETA: 2:30:01
2025-09-01 07:34:53.248 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 85/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.082e-03, size: 256, ETA: 2:29:59
2025-09-01 07:34:55.997 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 85/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.008s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.079e-03, size: 512, ETA: 2:29:56
2025-09-01 07:34:58.770 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 85/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.038s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.076e-03, size: 384, ETA: 2:29:53
2025-09-01 07:35:01.587 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 85/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.030s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 9.072e-03, size: 320, ETA: 2:29:51
2025-09-01 07:35:02.800 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:35:08.793 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:35:09.747 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:35:10.217 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4847
2025-09-01 07:35:10.358 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.3996
2025-09-01 07:35:10.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3103
2025-09-01 07:35:10.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3982
2025-09-01 07:35:10.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:35:10.437 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:35:10.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.485
2025-09-01 07:35:10.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.400
2025-09-01 07:35:10.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.310
2025-09-01 07:35:10.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.398
2025-09-01 07:35:10.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:35:10.438 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:35:10.439 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:35:10.439 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:35:10.439 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:35:10.439 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:35:10.439 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:35:10.439 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:35:10.439 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:35:11.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:35:11.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:35:12.335 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:35:13.006 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:35:13.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:35:14.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:35:14.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:35:15.624 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:35:16.232 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:35:16.232 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-09-01 07:35:16.232 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-09-01 07:35:16.232 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:35:16.240 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.41 ms, Average NMS time: 0.95 ms, Average inference time: 2.36 ms

2025-09-01 07:35:16.246 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:35:16.267 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:35:16.296 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch86
2025-09-01 07:35:18.701 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 86/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.115s, data_time: 0.033s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.067e-03, size: 288, ETA: 2:29:45
2025-09-01 07:35:21.595 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 86/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 9.064e-03, size: 480, ETA: 2:29:43
2025-09-01 07:35:24.363 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 86/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 0.8, lr: 9.060e-03, size: 480, ETA: 2:29:40
2025-09-01 07:35:27.156 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 86/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.131s, data_time: 0.042s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 9.057e-03, size: 320, ETA: 2:29:37
2025-09-01 07:35:30.003 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 86/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.133s, data_time: 0.040s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 9.053e-03, size: 288, ETA: 2:29:34
2025-09-01 07:35:32.900 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 86/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.128s, data_time: 0.034s, total_loss: 6.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 9.050e-03, size: 384, ETA: 2:29:30
2025-09-01 07:35:34.095 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:35:34.143 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch87
2025-09-01 07:35:36.849 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 87/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.130s, data_time: 0.018s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.2, lr: 9.044e-03, size: 544, ETA: 2:29:25
2025-09-01 07:35:39.617 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 87/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.041e-03, size: 288, ETA: 2:29:23
2025-09-01 07:35:42.418 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 87/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 9.037e-03, size: 320, ETA: 2:29:20
2025-09-01 07:35:45.315 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 87/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.144s, data_time: 0.068s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 9.034e-03, size: 480, ETA: 2:29:19
2025-09-01 07:35:48.170 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 87/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.140s, data_time: 0.059s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 9.030e-03, size: 544, ETA: 2:29:17
2025-09-01 07:35:50.973 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 87/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.044s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 9.027e-03, size: 480, ETA: 2:29:14
2025-09-01 07:35:52.227 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:35:52.385 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch88
2025-09-01 07:35:55.271 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 88/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.031s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 9.022e-03, size: 320, ETA: 2:29:10
2025-09-01 07:35:58.051 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 88/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.018e-03, size: 320, ETA: 2:29:07
2025-09-01 07:36:00.714 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 88/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.014e-03, size: 320, ETA: 2:29:04
2025-09-01 07:36:03.554 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 88/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.126s, data_time: 0.042s, total_loss: 6.6, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.011e-03, size: 256, ETA: 2:29:00
2025-09-01 07:36:06.436 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 88/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.130s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 9.007e-03, size: 384, ETA: 2:28:57
2025-09-01 07:36:09.323 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 88/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.004e-03, size: 320, ETA: 2:28:53
2025-09-01 07:36:10.527 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:36:10.628 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch89
2025-09-01 07:36:13.281 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 89/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.124s, data_time: 0.015s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.3, lr: 8.998e-03, size: 256, ETA: 2:28:48
2025-09-01 07:36:16.199 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 89/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.128s, data_time: 0.005s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.995e-03, size: 288, ETA: 2:28:44
2025-09-01 07:36:19.028 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 89/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.991e-03, size: 384, ETA: 2:28:40
2025-09-01 07:36:21.942 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 89/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.988e-03, size: 384, ETA: 2:28:37
2025-09-01 07:36:24.831 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 89/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.120s, 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: 8.984e-03, size: 256, ETA: 2:28:32
2025-09-01 07:36:27.609 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 89/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.127s, data_time: 0.009s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 8.980e-03, size: 416, ETA: 2:28:28
2025-09-01 07:36:28.934 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:36:28.971 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch90
2025-09-01 07:36:31.724 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 90/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.132s, data_time: 0.041s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.975e-03, size: 416, ETA: 2:28:24
2025-09-01 07:36:34.622 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 90/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.133s, data_time: 0.028s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.972e-03, size: 448, ETA: 2:28:21
2025-09-01 07:36:37.400 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 90/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.129s, data_time: 0.017s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 8.968e-03, size: 448, ETA: 2:28:18
2025-09-01 07:36:40.241 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 90/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.035s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.964e-03, size: 480, ETA: 2:28:15
2025-09-01 07:36:43.090 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 90/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.043s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.961e-03, size: 512, ETA: 2:28:12
2025-09-01 07:36:45.850 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 90/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.130s, data_time: 0.037s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.957e-03, size: 576, ETA: 2:28:09
2025-09-01 07:36:47.095 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:36:53.057 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:36:54.731 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:36:55.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5016
2025-09-01 07:36:56.117 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4306
2025-09-01 07:36:56.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2990
2025-09-01 07:36:56.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4104
2025-09-01 07:36:56.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:36:56.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:36:56.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.502
2025-09-01 07:36:56.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.431
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.299
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.410
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:36:56.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:36:56.217 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:36:57.617 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:36:58.912 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:37:00.195 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:37:01.470 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:37:02.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:37:04.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:37:05.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:37:07.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:37:08.321 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:37:08.322 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.17
2025-09-01 07:37:08.322 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-09-01 07:37:08.322 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:37:08.333 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.96 ms, Average inference time: 2.35 ms

2025-09-01 07:37:08.337 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:37:08.363 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:37:08.395 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch91
2025-09-01 07:37:10.841 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 91/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.120s, data_time: 0.010s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.952e-03, size: 384, ETA: 2:28:03
2025-09-01 07:37:13.650 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 91/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.033s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.3, lr: 8.948e-03, size: 384, ETA: 2:28:00
2025-09-01 07:37:16.532 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 91/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.141s, data_time: 0.029s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 8.944e-03, size: 576, ETA: 2:27:58
2025-09-01 07:37:19.352 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 91/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.137s, data_time: 0.026s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.941e-03, size: 288, ETA: 2:27:56
2025-09-01 07:37:22.161 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 91/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.012s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.937e-03, size: 448, ETA: 2:27:53
2025-09-01 07:37:25.057 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 91/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.031s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.933e-03, size: 480, ETA: 2:27:51
2025-09-01 07:37:26.305 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:37:26.344 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch92
2025-09-01 07:37:29.060 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 92/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.128s, data_time: 0.035s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.928e-03, size: 448, ETA: 2:27:47
2025-09-01 07:37:31.844 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 92/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.924e-03, size: 480, ETA: 2:27:44
2025-09-01 07:37:34.743 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 92/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.144s, data_time: 0.060s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.920e-03, size: 416, ETA: 2:27:42
2025-09-01 07:37:37.656 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 92/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.144s, data_time: 0.063s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.917e-03, size: 352, ETA: 2:27:41
2025-09-01 07:37:40.449 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 92/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.054s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.913e-03, size: 544, ETA: 2:27:38
2025-09-01 07:37:43.231 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 92/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.134s, data_time: 0.055s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.909e-03, size: 544, ETA: 2:27:36
2025-09-01 07:37:44.450 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:37:44.491 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch93
2025-09-01 07:37:47.489 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 93/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.022s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 8.904e-03, size: 352, ETA: 2:27:32
2025-09-01 07:37:50.380 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 93/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.123s, data_time: 0.011s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.900e-03, size: 352, ETA: 2:27:28
2025-09-01 07:37:53.163 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 93/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.135s, data_time: 0.054s, total_loss: 6.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.896e-03, size: 256, ETA: 2:27:25
2025-09-01 07:37:56.074 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 93/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.145s, data_time: 0.065s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 8.893e-03, size: 544, ETA: 2:27:23
2025-09-01 07:37:58.793 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 93/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.054s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.889e-03, size: 320, ETA: 2:27:20
2025-09-01 07:38:01.664 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 93/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.885e-03, size: 576, ETA: 2:27:19
2025-09-01 07:38:02.893 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:38:02.943 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch94
2025-09-01 07:38:05.861 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 94/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.145s, data_time: 0.063s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 8.880e-03, size: 480, ETA: 2:27:16
2025-09-01 07:38:08.629 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 94/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.137s, data_time: 0.059s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.876e-03, size: 416, ETA: 2:27:13
2025-09-01 07:38:11.436 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 94/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.872e-03, size: 448, ETA: 2:27:11
2025-09-01 07:38:14.303 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 94/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.142s, data_time: 0.065s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.868e-03, size: 480, ETA: 2:27:09
2025-09-01 07:38:17.190 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 94/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.142s, data_time: 0.064s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.864e-03, size: 352, ETA: 2:27:07
2025-09-01 07:38:19.923 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 94/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.133s, data_time: 0.055s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 8.861e-03, size: 384, ETA: 2:27:04
2025-09-01 07:38:21.113 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:38:21.228 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch95
2025-09-01 07:38:23.997 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 95/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.120s, data_time: 0.015s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.855e-03, size: 544, ETA: 2:26:58
2025-09-01 07:38:26.759 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 95/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.125s, data_time: 0.007s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.851e-03, size: 256, ETA: 2:26:54
2025-09-01 07:38:29.654 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 95/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.052s, total_loss: 7.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 8.847e-03, size: 480, ETA: 2:26:52
2025-09-01 07:38:32.547 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 95/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.144s, data_time: 0.057s, total_loss: 5.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 8.844e-03, size: 256, ETA: 2:26:50
2025-09-01 07:38:35.308 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 95/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.840e-03, size: 512, ETA: 2:26:48
2025-09-01 07:38:38.098 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 95/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.137s, data_time: 0.047s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 8.836e-03, size: 480, ETA: 2:26:45
2025-09-01 07:38:39.303 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:38:45.102 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:38:46.733 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:38:47.936 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5123
2025-09-01 07:38:48.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4380
2025-09-01 07:38:48.163 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2761
2025-09-01 07:38:48.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4088
2025-09-01 07:38:48.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:38:48.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:38:48.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.512
2025-09-01 07:38:48.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.438
2025-09-01 07:38:48.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.276
2025-09-01 07:38:48.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.409
2025-09-01 07:38:48.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:38:48.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:38:48.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:38:48.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:38:48.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:38:48.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:38:48.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:38:48.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:38:48.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:38:49.540 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:38:51.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:38:52.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:38:53.818 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:38:55.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:38:56.611 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:38:57.942 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:38:59.309 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:39:00.765 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:39:00.766 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-09-01 07:39:00.766 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-09-01 07:39:00.766 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:39:00.775 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.42 ms, Average NMS time: 1.00 ms, Average inference time: 2.42 ms

2025-09-01 07:39:00.776 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:39:00.802 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:39:00.832 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch96
2025-09-01 07:39:03.385 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 96/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.127s, data_time: 0.045s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 8.830e-03, size: 512, ETA: 2:26:40
2025-09-01 07:39:06.150 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 96/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 8.826e-03, size: 384, ETA: 2:26:38
2025-09-01 07:39:08.987 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 96/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 7.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 8.823e-03, size: 544, ETA: 2:26:36
2025-09-01 07:39:11.818 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 96/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.819e-03, size: 384, ETA: 2:26:33
2025-09-01 07:39:14.686 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 96/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.049s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.815e-03, size: 384, ETA: 2:26:31
2025-09-01 07:39:17.605 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 96/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.145s, data_time: 0.063s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.811e-03, size: 288, ETA: 2:26:29
2025-09-01 07:39:18.937 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:39:18.973 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch97
2025-09-01 07:39:21.700 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 97/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.805e-03, size: 512, ETA: 2:26:26
2025-09-01 07:39:24.649 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 97/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.147s, data_time: 0.068s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.802e-03, size: 512, ETA: 2:26:24
2025-09-01 07:39:27.420 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 97/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.138s, data_time: 0.055s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.798e-03, size: 384, ETA: 2:26:22
2025-09-01 07:39:30.124 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 97/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.132s, data_time: 0.053s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.794e-03, size: 576, ETA: 2:26:19
2025-09-01 07:39:32.976 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 97/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.029s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 8.790e-03, size: 512, ETA: 2:26:17
2025-09-01 07:39:35.869 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 97/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.140s, data_time: 0.023s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 8.786e-03, size: 352, ETA: 2:26:14
2025-09-01 07:39:37.011 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:39:37.135 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch98
2025-09-01 07:39:39.960 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 98/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.780e-03, size: 448, ETA: 2:26:10
2025-09-01 07:39:42.904 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 98/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.142s, data_time: 0.053s, total_loss: 8.6, iou_loss: 3.8, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 8.776e-03, size: 320, ETA: 2:26:08
2025-09-01 07:39:45.685 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 98/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.134s, data_time: 0.024s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 8.772e-03, size: 320, ETA: 2:26:05
2025-09-01 07:39:48.496 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 98/600, iter: 80/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.054s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.768e-03, size: 512, ETA: 2:26:03
2025-09-01 07:39:51.366 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 98/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.143s, data_time: 0.061s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.765e-03, size: 320, ETA: 2:26:01
2025-09-01 07:39:54.137 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 98/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.138s, data_time: 0.054s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.761e-03, size: 576, ETA: 2:25:58
2025-09-01 07:39:55.303 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:39:55.458 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch99
2025-09-01 07:39:58.238 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 99/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.123s, data_time: 0.020s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.755e-03, size: 512, ETA: 2:25:52
2025-09-01 07:40:00.993 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 99/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.751e-03, size: 448, ETA: 2:25:50
2025-09-01 07:40:03.882 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 99/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.143s, data_time: 0.066s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.747e-03, size: 320, ETA: 2:25:48
2025-09-01 07:40:06.820 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 99/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.146s, data_time: 0.072s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.743e-03, size: 384, ETA: 2:25:46
2025-09-01 07:40:09.674 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 99/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.142s, data_time: 0.062s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 8.739e-03, size: 416, ETA: 2:25:44
2025-09-01 07:40:12.397 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 99/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.126s, data_time: 0.042s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.735e-03, size: 448, ETA: 2:25:40
2025-09-01 07:40:13.618 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:40:13.668 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch100
2025-09-01 07:40:16.458 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 100/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.128s, data_time: 0.009s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.729e-03, size: 448, ETA: 2:25:35
2025-09-01 07:40:19.272 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 100/600, iter: 40/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.130s, data_time: 0.039s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.725e-03, size: 288, ETA: 2:25:32
2025-09-01 07:40:22.008 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 100/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.721e-03, size: 480, ETA: 2:25:29
2025-09-01 07:40:24.936 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 100/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.145s, data_time: 0.066s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 8.717e-03, size: 480, ETA: 2:25:28
2025-09-01 07:40:27.837 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 100/600, iter: 100/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 8.713e-03, size: 448, ETA: 2:25:25
2025-09-01 07:40:30.672 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 100/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.022s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 8.709e-03, size: 352, ETA: 2:25:22
2025-09-01 07:40:31.899 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:40:37.814 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:40:40.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:40:41.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5128
2025-09-01 07:40:42.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4634
2025-09-01 07:40:42.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2797
2025-09-01 07:40:42.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4186
2025-09-01 07:40:42.426 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:40:42.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:40:42.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.513
2025-09-01 07:40:42.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.463
2025-09-01 07:40:42.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.280
2025-09-01 07:40:42.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.419
2025-09-01 07:40:42.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:40:42.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:40:42.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:40:42.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:40:42.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:40:42.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:40:42.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:40:42.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:40:42.428 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:40:44.537 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:40:46.613 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:40:48.669 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:40:50.734 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:40:52.757 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:40:54.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:40:56.845 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:40:58.903 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:41:00.952 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:41:00.953 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-09-01 07:41:00.953 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-09-01 07:41:00.953 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:41:00.979 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.95 ms, Average inference time: 2.33 ms

2025-09-01 07:41:00.980 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:41:01.012 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:41:01.042 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch101
2025-09-01 07:41:03.573 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 101/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.125s, data_time: 0.042s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 8.703e-03, size: 416, ETA: 2:25:17
2025-09-01 07:41:06.361 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 101/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.137s, data_time: 0.027s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.699e-03, size: 352, ETA: 2:25:15
2025-09-01 07:41:09.111 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 101/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.134s, data_time: 0.004s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.695e-03, size: 416, ETA: 2:25:12
2025-09-01 07:41:11.873 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 101/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.026s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 8.691e-03, size: 576, ETA: 2:25:09
2025-09-01 07:41:14.772 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 101/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.144s, data_time: 0.065s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.687e-03, size: 576, ETA: 2:25:08
2025-09-01 07:41:17.795 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 101/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.150s, data_time: 0.067s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 8.683e-03, size: 256, ETA: 2:25:06
2025-09-01 07:41:18.986 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:41:19.027 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch102
2025-09-01 07:41:21.851 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 102/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.055s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 8.677e-03, size: 352, ETA: 2:25:03
2025-09-01 07:41:24.695 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 102/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.673e-03, size: 480, ETA: 2:25:01
2025-09-01 07:41:27.436 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 102/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.048s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 8.669e-03, size: 480, ETA: 2:24:58
2025-09-01 07:41:30.263 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 102/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.055s, total_loss: 7.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.665e-03, size: 256, ETA: 2:24:56
2025-09-01 07:41:33.165 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 102/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.143s, data_time: 0.062s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.3, lr: 8.661e-03, size: 384, ETA: 2:24:54
2025-09-01 07:41:35.869 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 102/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.130s, data_time: 0.049s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.657e-03, size: 576, ETA: 2:24:51
2025-09-01 07:41:37.044 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:41:37.128 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch103
2025-09-01 07:41:40.059 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 103/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.128s, data_time: 0.013s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.651e-03, size: 448, ETA: 2:24:45
2025-09-01 07:41:42.862 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 103/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.121s, data_time: 0.006s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.647e-03, size: 320, ETA: 2:24:41
2025-09-01 07:41:45.721 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 103/600, iter: 60/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.132s, data_time: 0.041s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.643e-03, size: 544, ETA: 2:24:38
2025-09-01 07:41:48.561 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 103/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 8.639e-03, size: 384, ETA: 2:24:36
2025-09-01 07:41:51.408 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 103/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.142s, data_time: 0.066s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.635e-03, size: 320, ETA: 2:24:34
2025-09-01 07:41:54.242 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 103/600, iter: 120/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.631e-03, size: 320, ETA: 2:24:32
2025-09-01 07:41:55.427 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:41:55.483 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch104
2025-09-01 07:41:58.300 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 104/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.139s, data_time: 0.062s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.625e-03, size: 320, ETA: 2:24:28
2025-09-01 07:42:01.097 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 104/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 7.3, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.620e-03, size: 256, ETA: 2:24:26
2025-09-01 07:42:03.937 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 104/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 8.616e-03, size: 544, ETA: 2:24:23
2025-09-01 07:42:06.868 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 104/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.146s, data_time: 0.059s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.612e-03, size: 544, ETA: 2:24:22
2025-09-01 07:42:09.666 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 104/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 8.608e-03, size: 480, ETA: 2:24:19
2025-09-01 07:42:12.675 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 104/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.150s, data_time: 0.068s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 8.604e-03, size: 576, ETA: 2:24:18
2025-09-01 07:42:14.081 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:42:14.136 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch105
2025-09-01 07:42:16.930 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 105/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 8.598e-03, size: 512, ETA: 2:24:15
2025-09-01 07:42:19.806 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 105/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.143s, data_time: 0.065s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.594e-03, size: 352, ETA: 2:24:13
2025-09-01 07:42:22.519 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 105/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.135s, data_time: 0.057s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.590e-03, size: 448, ETA: 2:24:11
2025-09-01 07:42:25.464 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 105/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.147s, data_time: 0.066s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.3, lr: 8.585e-03, size: 416, ETA: 2:24:09
2025-09-01 07:42:28.396 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 105/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.146s, data_time: 0.061s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.581e-03, size: 480, ETA: 2:24:07
2025-09-01 07:42:31.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 105/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.134s, data_time: 0.054s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.577e-03, size: 448, ETA: 2:24:04
2025-09-01 07:42:32.257 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:42:38.433 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:42:42.295 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:42:45.066 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5238
2025-09-01 07:42:45.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4576
2025-09-01 07:42:45.580 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3239
2025-09-01 07:42:45.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4351
2025-09-01 07:42:45.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:42:45.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:42:45.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.524
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.458
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.324
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.435
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:42:45.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:42:45.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:42:45.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:42:48.806 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:42:52.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:42:55.481 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:42:58.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:43:01.950 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:43:05.225 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:43:08.443 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:43:11.642 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:43:14.839 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:43:14.839 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-09-01 07:43:14.840 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-09-01 07:43:14.840 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:43:14.865 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.96 ms, Average inference time: 2.30 ms

2025-09-01 07:43:14.866 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:43:14.888 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:43:14.920 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch106
2025-09-01 07:43:17.408 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 106/600, iter: 20/129, gpu mem: 1663Mb, mem: 45.9Gb, iter_time: 0.122s, data_time: 0.046s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.571e-03, size: 256, ETA: 2:23:59
2025-09-01 07:43:20.277 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 106/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.567e-03, size: 416, ETA: 2:23:57
2025-09-01 07:43:23.191 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 106/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.132s, data_time: 0.043s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.563e-03, size: 512, ETA: 2:23:54
2025-09-01 07:43:26.015 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 106/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.127s, data_time: 0.033s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 8.558e-03, size: 256, ETA: 2:23:50
2025-09-01 07:43:28.791 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 106/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, data_time: 0.040s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.554e-03, size: 448, ETA: 2:23:47
2025-09-01 07:43:31.674 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 106/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.130s, data_time: 0.014s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 8.550e-03, size: 448, ETA: 2:23:44
2025-09-01 07:43:32.785 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:43:32.908 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch107
2025-09-01 07:43:35.892 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 107/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.144s, data_time: 0.065s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.544e-03, size: 576, ETA: 2:23:40
2025-09-01 07:43:38.678 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 107/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.062s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.540e-03, size: 320, ETA: 2:23:37
2025-09-01 07:43:41.404 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 107/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.134s, data_time: 0.036s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.535e-03, size: 384, ETA: 2:23:34
2025-09-01 07:43:44.306 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 107/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.015s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.531e-03, size: 416, ETA: 2:23:32
2025-09-01 07:43:47.121 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 107/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.138s, 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: 8.527e-03, size: 416, ETA: 2:23:30
2025-09-01 07:43:49.840 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 107/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 8.523e-03, size: 288, ETA: 2:23:27
2025-09-01 07:43:51.073 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:43:51.176 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch108
2025-09-01 07:43:54.065 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 108/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.138s, data_time: 0.043s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.517e-03, size: 416, ETA: 2:23:23
2025-09-01 07:43:56.977 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 108/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.137s, data_time: 0.011s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.512e-03, size: 352, ETA: 2:23:20
2025-09-01 07:43:59.826 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 108/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.138s, data_time: 0.013s, total_loss: 7.9, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.7, lr: 8.508e-03, size: 448, ETA: 2:23:18
2025-09-01 07:44:02.571 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 108/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.058s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.504e-03, size: 288, ETA: 2:23:15
2025-09-01 07:44:05.294 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 108/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.135s, data_time: 0.060s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 8.500e-03, size: 512, ETA: 2:23:12
2025-09-01 07:44:08.143 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 108/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.142s, data_time: 0.062s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.495e-03, size: 416, ETA: 2:23:10
2025-09-01 07:44:09.342 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:44:09.379 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch109
2025-09-01 07:44:12.167 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 109/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.489e-03, size: 384, ETA: 2:23:07
2025-09-01 07:44:15.011 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 109/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.132s, data_time: 0.048s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.485e-03, size: 480, ETA: 2:23:04
2025-09-01 07:44:17.849 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 109/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.137s, data_time: 0.054s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 8.480e-03, size: 512, ETA: 2:23:01
2025-09-01 07:44:20.626 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 109/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.048s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.476e-03, size: 512, ETA: 2:22:58
2025-09-01 07:44:23.494 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 109/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.056s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 8.472e-03, size: 384, ETA: 2:22:56
2025-09-01 07:44:26.310 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 109/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.045s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 8.468e-03, size: 320, ETA: 2:22:53
2025-09-01 07:44:27.649 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:44:27.700 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch110
2025-09-01 07:44:30.587 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 110/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.144s, data_time: 0.061s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 8.461e-03, size: 320, ETA: 2:22:51
2025-09-01 07:44:33.443 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 110/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 8.457e-03, size: 544, ETA: 2:22:49
2025-09-01 07:44:36.148 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 110/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.134s, data_time: 0.056s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 8.453e-03, size: 544, ETA: 2:22:46
2025-09-01 07:44:39.003 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 110/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.448e-03, size: 448, ETA: 2:22:43
2025-09-01 07:44:42.057 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 110/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.144s, data_time: 0.010s, total_loss: 8.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 0.8, lr: 8.444e-03, size: 544, ETA: 2:22:41
2025-09-01 07:44:44.880 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 110/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.133s, data_time: 0.017s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.440e-03, size: 416, ETA: 2:22:39
2025-09-01 07:44:46.117 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:44:51.996 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:44:53.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:44:54.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4859
2025-09-01 07:44:54.980 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4264
2025-09-01 07:44:55.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2886
2025-09-01 07:44:55.057 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4003
2025-09-01 07:44:55.057 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:44:55.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:44:55.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.486
2025-09-01 07:44:55.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.426
2025-09-01 07:44:55.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.289
2025-09-01 07:44:55.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.400
2025-09-01 07:44:55.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:44:55.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:44:55.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:44:55.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:44:55.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:44:55.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:44:55.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:44:55.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:44:55.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:44:56.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:44:57.852 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:44:59.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:45:00.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:45:01.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:45:03.194 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:45:04.496 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:45:05.818 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:45:07.182 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:45:07.183 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-09-01 07:45:07.183 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-09-01 07:45:07.183 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:45:07.191 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.95 ms, Average inference time: 2.34 ms

2025-09-01 07:45:07.192 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:45:07.218 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:45:07.252 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch111
2025-09-01 07:45:09.612 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 111/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.117s, data_time: 0.042s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.433e-03, size: 288, ETA: 2:22:33
2025-09-01 07:45:12.468 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 111/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.041s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.429e-03, size: 416, ETA: 2:22:30
2025-09-01 07:45:15.315 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 111/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 7.3, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.425e-03, size: 288, ETA: 2:22:28
2025-09-01 07:45:18.137 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 111/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.420e-03, size: 576, ETA: 2:22:26
2025-09-01 07:45:20.964 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 111/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.056s, total_loss: 7.4, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.416e-03, size: 288, ETA: 2:22:24
2025-09-01 07:45:23.761 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 111/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.137s, data_time: 0.044s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 8.412e-03, size: 512, ETA: 2:22:21
2025-09-01 07:45:25.008 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:45:25.132 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch112
2025-09-01 07:45:27.965 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 112/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 8.405e-03, size: 320, ETA: 2:22:17
2025-09-01 07:45:30.949 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 112/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.140s, 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: 8.401e-03, size: 256, ETA: 2:22:15
2025-09-01 07:45:33.714 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 112/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.396e-03, size: 256, ETA: 2:22:12
2025-09-01 07:45:36.455 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 112/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.130s, data_time: 0.035s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.392e-03, size: 288, ETA: 2:22:09
2025-09-01 07:45:39.288 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 112/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.135s, data_time: 0.049s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 8.388e-03, size: 416, ETA: 2:22:06
2025-09-01 07:45:42.025 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 112/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.134s, data_time: 0.052s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.383e-03, size: 320, ETA: 2:22:03
2025-09-01 07:45:43.283 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:45:43.440 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch113
2025-09-01 07:45:46.154 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 113/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.127s, data_time: 0.048s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.377e-03, size: 544, ETA: 2:21:58
2025-09-01 07:45:48.958 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 113/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.139s, data_time: 0.063s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.7, lr: 8.372e-03, size: 320, ETA: 2:21:56
2025-09-01 07:45:51.827 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 113/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.041s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 8.368e-03, size: 544, ETA: 2:21:54
2025-09-01 07:45:54.575 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 113/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 8.364e-03, size: 480, ETA: 2:21:51
2025-09-01 07:45:57.468 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 113/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.134s, data_time: 0.007s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.359e-03, size: 448, ETA: 2:21:48
2025-09-01 07:46:00.413 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 113/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.129s, 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: 8.355e-03, size: 416, ETA: 2:21:45
2025-09-01 07:46:01.633 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:46:01.676 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch114
2025-09-01 07:46:04.472 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 114/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 8.348e-03, size: 352, ETA: 2:21:39
2025-09-01 07:46:07.321 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 114/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.129s, data_time: 0.006s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.344e-03, size: 544, ETA: 2:21:36
2025-09-01 07:46:10.026 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 114/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.119s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 8.339e-03, size: 256, ETA: 2:21:32
2025-09-01 07:46:12.844 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 114/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.037s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 8.335e-03, size: 256, ETA: 2:21:29
2025-09-01 07:46:15.662 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 114/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.130s, data_time: 0.022s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 8.331e-03, size: 416, ETA: 2:21:26
2025-09-01 07:46:18.484 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 114/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.040s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.326e-03, size: 512, ETA: 2:21:23
2025-09-01 07:46:19.806 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:46:19.860 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch115
2025-09-01 07:46:22.702 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 115/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.124s, 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: 8.320e-03, size: 480, ETA: 2:21:18
2025-09-01 07:46:25.573 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 115/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.124s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 8.315e-03, size: 288, ETA: 2:21:15
2025-09-01 07:46:28.301 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 115/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, data_time: 0.033s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.311e-03, size: 256, ETA: 2:21:12
2025-09-01 07:46:31.141 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 115/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.140s, data_time: 0.063s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 8.306e-03, size: 288, ETA: 2:21:09
2025-09-01 07:46:34.012 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 115/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 8.302e-03, size: 480, ETA: 2:21:07
2025-09-01 07:46:36.677 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 115/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.130s, data_time: 0.046s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 8.297e-03, size: 416, ETA: 2:21:04
2025-09-01 07:46:38.079 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:46:44.021 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:46:45.606 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:46:46.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4982
2025-09-01 07:46:46.718 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4162
2025-09-01 07:46:46.749 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2435
2025-09-01 07:46:46.749 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3859
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.498
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.416
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.243
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.386
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:46:46.750 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:46:46.751 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:46:46.751 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:46:46.751 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:46:47.821 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:46:48.924 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:46:49.996 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:46:51.079 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:46:52.142 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:46:53.220 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:46:54.285 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:46:55.350 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:46:56.410 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:46:56.411 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-09-01 07:46:56.411 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-09-01 07:46:56.411 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:46:56.419 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.40 ms, Average NMS time: 0.92 ms, Average inference time: 2.31 ms

2025-09-01 07:46:56.420 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:46:56.441 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:46:56.471 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch116
2025-09-01 07:46:58.963 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 116/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.124s, data_time: 0.043s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.291e-03, size: 544, ETA: 2:21:00
2025-09-01 07:47:01.797 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 116/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 8.286e-03, size: 416, ETA: 2:20:57
2025-09-01 07:47:04.663 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 116/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.132s, data_time: 0.019s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.282e-03, size: 576, ETA: 2:20:54
2025-09-01 07:47:07.491 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 116/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.2, lr: 8.277e-03, size: 416, ETA: 2:20:52
2025-09-01 07:47:10.296 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 116/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.273e-03, size: 384, ETA: 2:20:49
2025-09-01 07:47:13.179 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 116/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.143s, data_time: 0.062s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 8.268e-03, size: 448, ETA: 2:20:47
2025-09-01 07:47:14.527 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:47:14.575 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch117
2025-09-01 07:47:17.261 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 117/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.134s, data_time: 0.050s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.262e-03, size: 416, ETA: 2:20:44
2025-09-01 07:47:19.943 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 117/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.132s, data_time: 0.050s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.257e-03, size: 352, ETA: 2:20:41
2025-09-01 07:47:22.818 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 117/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.052s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 8.253e-03, size: 384, ETA: 2:20:38
2025-09-01 07:47:25.693 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 117/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.130s, data_time: 0.015s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 8.248e-03, size: 512, ETA: 2:20:35
2025-09-01 07:47:28.565 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 117/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 8.243e-03, size: 384, ETA: 2:20:33
2025-09-01 07:47:31.281 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 117/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.130s, data_time: 0.028s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.239e-03, size: 416, ETA: 2:20:30
2025-09-01 07:47:32.535 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:47:32.574 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch118
2025-09-01 07:47:35.343 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 118/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.137s, data_time: 0.051s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.0, lr: 8.232e-03, size: 384, ETA: 2:20:26
2025-09-01 07:47:38.209 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 118/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.142s, data_time: 0.063s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.228e-03, size: 544, ETA: 2:20:24
2025-09-01 07:47:41.151 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 118/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.146s, data_time: 0.067s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 8.223e-03, size: 512, ETA: 2:20:22
2025-09-01 07:47:43.901 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 118/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.055s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.219e-03, size: 544, ETA: 2:20:19
2025-09-01 07:47:46.699 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 118/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.130s, data_time: 0.047s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 8.214e-03, size: 480, ETA: 2:20:16
2025-09-01 07:47:49.513 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 118/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.064s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 8.209e-03, size: 384, ETA: 2:20:14
2025-09-01 07:47:50.731 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:47:50.781 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch119
2025-09-01 07:47:53.474 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 119/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.130s, data_time: 0.049s, total_loss: 8.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.8, cls_loss: 0.7, lr: 8.203e-03, size: 384, ETA: 2:20:09
2025-09-01 07:47:56.361 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 119/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.045s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.198e-03, size: 352, ETA: 2:20:07
2025-09-01 07:47:59.255 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 119/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.142s, data_time: 0.063s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 8.194e-03, size: 544, ETA: 2:20:05
2025-09-01 07:48:02.138 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 119/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.143s, data_time: 0.065s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.189e-03, size: 448, ETA: 2:20:03
2025-09-01 07:48:04.939 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 119/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 8.184e-03, size: 256, ETA: 2:20:00
2025-09-01 07:48:07.718 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 119/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.138s, data_time: 0.054s, total_loss: 8.5, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 8.180e-03, size: 480, ETA: 2:19:58
2025-09-01 07:48:09.079 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:48:09.120 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch120
2025-09-01 07:48:11.951 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 120/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.059s, total_loss: 5.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 8.173e-03, size: 384, ETA: 2:19:55
2025-09-01 07:48:14.781 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 120/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.168e-03, size: 320, ETA: 2:19:53
2025-09-01 07:48:17.522 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 120/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.131s, data_time: 0.045s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 8.164e-03, size: 480, ETA: 2:19:50
2025-09-01 07:48:20.383 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 120/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.136s, data_time: 0.011s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.159e-03, size: 384, ETA: 2:19:47
2025-09-01 07:48:23.212 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 120/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.129s, data_time: 0.012s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.155e-03, size: 544, ETA: 2:19:44
2025-09-01 07:48:26.063 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 120/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.126s, 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: 8.150e-03, size: 288, ETA: 2:19:40
2025-09-01 07:48:27.382 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:48:33.380 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:48:37.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:48:40.430 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4655
2025-09-01 07:48:40.682 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4488
2025-09-01 07:48:40.775 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2433
2025-09-01 07:48:40.776 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3859
2025-09-01 07:48:40.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:48:40.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:48:40.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.465
2025-09-01 07:48:40.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.449
2025-09-01 07:48:40.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.243
2025-09-01 07:48:40.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.386
2025-09-01 07:48:40.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:48:40.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:48:40.777 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:48:40.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:48:40.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:48:40.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:48:40.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:48:40.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:48:40.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:48:44.659 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:48:48.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:48:52.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:48:55.733 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:48:59.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:49:03.487 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:49:07.540 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:49:10.978 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:49:14.732 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:49:14.732 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-09-01 07:49:14.732 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-09-01 07:49:14.732 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:49:14.761 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.93 ms, Average inference time: 2.28 ms

2025-09-01 07:49:14.762 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:49:14.799 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:49:14.846 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch121
2025-09-01 07:49:17.282 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 121/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.118s, data_time: 0.032s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.143e-03, size: 480, ETA: 2:19:35
2025-09-01 07:49:20.041 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 121/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 8.139e-03, size: 320, ETA: 2:19:32
2025-09-01 07:49:22.886 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 121/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.134e-03, size: 288, ETA: 2:19:30
2025-09-01 07:49:25.738 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 121/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.141s, data_time: 0.063s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 8.129e-03, size: 384, ETA: 2:19:28
2025-09-01 07:49:28.626 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 121/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.144s, data_time: 0.067s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 8.125e-03, size: 480, ETA: 2:19:26
2025-09-01 07:49:31.361 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 121/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.136s, data_time: 0.058s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 8.120e-03, size: 544, ETA: 2:19:23
2025-09-01 07:49:32.577 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:49:32.617 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch122
2025-09-01 07:49:35.368 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 122/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.113e-03, size: 448, ETA: 2:19:19
2025-09-01 07:49:38.194 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 122/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 8.108e-03, size: 256, ETA: 2:19:17
2025-09-01 07:49:41.154 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 122/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.147s, data_time: 0.069s, total_loss: 7.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 8.104e-03, size: 448, ETA: 2:19:15
2025-09-01 07:49:43.905 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 122/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.135s, data_time: 0.054s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 8.099e-03, size: 416, ETA: 2:19:12
2025-09-01 07:49:46.842 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 122/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.133s, data_time: 0.019s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.094e-03, size: 480, ETA: 2:19:09
2025-09-01 07:49:49.718 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 122/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.131s, data_time: 0.031s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.090e-03, size: 320, ETA: 2:19:06
2025-09-01 07:49:50.959 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:49:51.009 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch123
2025-09-01 07:49:53.748 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 123/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.0Gb, iter_time: 0.135s, data_time: 0.056s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 8.083e-03, size: 384, ETA: 2:19:02
2025-09-01 07:49:56.601 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 123/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.141s, data_time: 0.060s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.078e-03, size: 576, ETA: 2:19:00
2025-09-01 07:49:59.453 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 123/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.074e-03, size: 416, ETA: 2:18:57
2025-09-01 07:50:02.195 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 123/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.131s, data_time: 0.050s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 8.069e-03, size: 288, ETA: 2:18:54
2025-09-01 07:50:05.094 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 123/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.144s, data_time: 0.060s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.064e-03, size: 288, ETA: 2:18:52
2025-09-01 07:50:07.979 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 123/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.059e-03, size: 256, ETA: 2:18:50
2025-09-01 07:50:09.226 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:50:09.279 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch124
2025-09-01 07:50:12.045 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 124/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.137s, data_time: 0.060s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.053e-03, size: 384, ETA: 2:18:47
2025-09-01 07:50:14.954 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 124/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 8.048e-03, size: 288, ETA: 2:18:44
2025-09-01 07:50:17.909 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 124/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.146s, data_time: 0.066s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 8.043e-03, size: 448, ETA: 2:18:42
2025-09-01 07:50:20.725 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 124/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 8.038e-03, size: 480, ETA: 2:18:40
2025-09-01 07:50:23.556 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 124/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.141s, data_time: 0.063s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 8.034e-03, size: 288, ETA: 2:18:38
2025-09-01 07:50:26.413 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 124/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.029e-03, size: 256, ETA: 2:18:35
2025-09-01 07:50:27.588 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:50:27.662 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch125
2025-09-01 07:50:30.536 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 125/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.126s, data_time: 0.024s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 8.022e-03, size: 320, ETA: 2:18:31
2025-09-01 07:50:33.348 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 125/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.127s, data_time: 0.041s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.017e-03, size: 320, ETA: 2:18:27
2025-09-01 07:50:36.179 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 125/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.127s, data_time: 0.027s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 8.012e-03, size: 416, ETA: 2:18:24
2025-09-01 07:50:39.007 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 125/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 8.008e-03, size: 384, ETA: 2:18:22
2025-09-01 07:50:41.927 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 125/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.145s, data_time: 0.063s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.003e-03, size: 544, ETA: 2:18:19
2025-09-01 07:50:44.876 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 125/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.147s, data_time: 0.067s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.998e-03, size: 448, ETA: 2:18:18
2025-09-01 07:50:46.140 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:50:51.987 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:50:56.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:50:59.318 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5063
2025-09-01 07:50:59.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4352
2025-09-01 07:50:59.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2727
2025-09-01 07:50:59.801 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4047
2025-09-01 07:50:59.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:50:59.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:50:59.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.506
2025-09-01 07:50:59.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.435
2025-09-01 07:50:59.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.273
2025-09-01 07:50:59.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.405
2025-09-01 07:50:59.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:50:59.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:50:59.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:50:59.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:50:59.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:50:59.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:50:59.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:50:59.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:50:59.804 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:51:03.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:51:07.374 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:51:11.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:51:14.810 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:51:18.528 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:51:22.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:51:26.117 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:51:29.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:51:33.444 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:51:33.444 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-09-01 07:51:33.444 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-09-01 07:51:33.444 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:51:33.470 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.33 ms, Average NMS time: 0.95 ms, Average inference time: 2.29 ms

2025-09-01 07:51:33.472 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:51:33.500 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:51:33.531 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch126
2025-09-01 07:51:35.999 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 126/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.121s, data_time: 0.043s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 7.991e-03, size: 544, ETA: 2:18:13
2025-09-01 07:51:38.849 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 126/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 7.986e-03, size: 480, ETA: 2:18:10
2025-09-01 07:51:41.712 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 126/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 7.982e-03, size: 448, ETA: 2:18:07
2025-09-01 07:51:44.587 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 126/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.136s, data_time: 0.042s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 7.977e-03, size: 320, ETA: 2:18:05
2025-09-01 07:51:47.343 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 126/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.131s, data_time: 0.033s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.972e-03, size: 448, ETA: 2:18:02
2025-09-01 07:51:50.135 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 126/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.128s, data_time: 0.020s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.967e-03, size: 544, ETA: 2:17:58
2025-09-01 07:51:51.452 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:51:51.511 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch127
2025-09-01 07:51:54.246 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 127/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 7.960e-03, size: 448, ETA: 2:17:55
2025-09-01 07:51:57.017 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 127/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.126s, data_time: 0.041s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.955e-03, size: 512, ETA: 2:17:52
2025-09-01 07:51:59.812 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 127/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.131s, data_time: 0.049s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.3, lr: 7.951e-03, size: 288, ETA: 2:17:48
2025-09-01 07:52:02.761 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 127/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.127s, data_time: 0.037s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.7, lr: 7.946e-03, size: 480, ETA: 2:17:45
2025-09-01 07:52:05.705 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 127/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, data_time: 0.032s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.941e-03, size: 544, ETA: 2:17:42
2025-09-01 07:52:08.662 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 127/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 7.936e-03, size: 448, ETA: 2:17:39
2025-09-01 07:52:09.877 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:52:09.914 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch128
2025-09-01 07:52:12.718 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 128/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.124s, 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: 7.929e-03, size: 256, ETA: 2:17:33
2025-09-01 07:52:15.438 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 128/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, data_time: 0.045s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 7.924e-03, size: 544, ETA: 2:17:30
2025-09-01 07:52:18.286 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 128/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, data_time: 0.031s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.919e-03, size: 320, ETA: 2:17:27
2025-09-01 07:52:21.111 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 128/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.133s, data_time: 0.045s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.915e-03, size: 576, ETA: 2:17:24
2025-09-01 07:52:23.923 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 128/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.126s, data_time: 0.013s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.910e-03, size: 384, ETA: 2:17:21
2025-09-01 07:52:26.736 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 128/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.134s, data_time: 0.040s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.2, lr: 7.905e-03, size: 512, ETA: 2:17:18
2025-09-01 07:52:27.967 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:52:28.026 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch129
2025-09-01 07:52:30.893 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 129/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.138s, data_time: 0.061s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.898e-03, size: 384, ETA: 2:17:14
2025-09-01 07:52:33.701 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 129/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.893e-03, size: 256, ETA: 2:17:11
2025-09-01 07:52:36.525 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 129/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.133s, data_time: 0.023s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 7.888e-03, size: 576, ETA: 2:17:09
2025-09-01 07:52:39.384 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 129/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 7.883e-03, size: 512, ETA: 2:17:06
2025-09-01 07:52:42.227 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 129/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.140s, data_time: 0.056s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.878e-03, size: 512, ETA: 2:17:04
2025-09-01 07:52:45.041 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 129/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.873e-03, size: 352, ETA: 2:17:01
2025-09-01 07:52:46.286 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:52:46.325 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch130
2025-09-01 07:52:49.072 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 130/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.128s, data_time: 0.048s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 7.866e-03, size: 512, ETA: 2:16:57
2025-09-01 07:52:51.906 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 130/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.127s, data_time: 0.043s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 7.861e-03, size: 320, ETA: 2:16:54
2025-09-01 07:52:54.790 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 130/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.135s, data_time: 0.006s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 7.857e-03, size: 480, ETA: 2:16:51
2025-09-01 07:52:57.659 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 130/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, 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: 7.852e-03, size: 544, ETA: 2:16:48
2025-09-01 07:53:00.419 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 130/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.126s, data_time: 0.008s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.7, lr: 7.847e-03, size: 544, ETA: 2:16:44
2025-09-01 07:53:03.179 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 130/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.128s, data_time: 0.011s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 7.842e-03, size: 480, ETA: 2:16:41
2025-09-01 07:53:04.458 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:53:10.496 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:53:12.482 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:53:13.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5350
2025-09-01 07:53:13.986 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4555
2025-09-01 07:53:14.040 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2930
2025-09-01 07:53:14.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4278
2025-09-01 07:53:14.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:53:14.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:53:14.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.535
2025-09-01 07:53:14.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.455
2025-09-01 07:53:14.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.293
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.428
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:53:14.042 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:53:15.601 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:53:17.106 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:53:18.668 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:53:20.156 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:53:21.724 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:53:23.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:53:24.800 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:53:26.355 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:53:27.896 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:53:27.896 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-09-01 07:53:27.896 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-09-01 07:53:27.896 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:53:27.920 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.43 ms, Average NMS time: 0.93 ms, Average inference time: 2.36 ms

2025-09-01 07:53:27.922 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:53:27.950 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:53:27.984 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch131
2025-09-01 07:53:30.550 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 131/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.128s, data_time: 0.052s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.835e-03, size: 448, ETA: 2:16:37
2025-09-01 07:53:33.568 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 131/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.150s, data_time: 0.067s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.830e-03, size: 480, ETA: 2:16:35
2025-09-01 07:53:36.381 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 131/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 7.825e-03, size: 416, ETA: 2:16:33
2025-09-01 07:53:39.145 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 131/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.820e-03, size: 352, ETA: 2:16:30
2025-09-01 07:53:41.975 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 131/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.141s, data_time: 0.064s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 7.815e-03, size: 256, ETA: 2:16:28
2025-09-01 07:53:44.832 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 131/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 7.810e-03, size: 288, ETA: 2:16:25
2025-09-01 07:53:45.947 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:53:46.069 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch132
2025-09-01 07:53:48.799 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 132/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.134s, data_time: 0.050s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.803e-03, size: 352, ETA: 2:16:21
2025-09-01 07:53:51.591 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 132/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.131s, data_time: 0.017s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.798e-03, size: 448, ETA: 2:16:18
2025-09-01 07:53:54.303 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 132/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.120s, data_time: 0.011s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.793e-03, size: 384, ETA: 2:16:14
2025-09-01 07:53:57.198 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 132/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.126s, data_time: 0.017s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 7.788e-03, size: 512, ETA: 2:16:11
2025-09-01 07:54:00.074 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 132/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.141s, data_time: 0.050s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 7.783e-03, size: 256, ETA: 2:16:09
2025-09-01 07:54:03.006 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 132/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.143s, data_time: 0.057s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.778e-03, size: 416, ETA: 2:16:06
2025-09-01 07:54:04.222 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:54:04.260 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch133
2025-09-01 07:54:06.959 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 133/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.133s, data_time: 0.052s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.771e-03, size: 448, ETA: 2:16:02
2025-09-01 07:54:09.780 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 133/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.140s, data_time: 0.059s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.766e-03, size: 288, ETA: 2:16:00
2025-09-01 07:54:12.629 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 133/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.761e-03, size: 544, ETA: 2:15:58
2025-09-01 07:54:15.550 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 133/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.143s, data_time: 0.048s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.756e-03, size: 480, ETA: 2:15:55
2025-09-01 07:54:18.316 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 133/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.130s, data_time: 0.027s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.751e-03, size: 384, ETA: 2:15:52
2025-09-01 07:54:21.266 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 133/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.746e-03, size: 320, ETA: 2:15:49
2025-09-01 07:54:22.492 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:54:22.529 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch134
2025-09-01 07:54:25.346 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 134/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.127s, data_time: 0.009s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 7.739e-03, size: 512, ETA: 2:15:44
2025-09-01 07:54:28.261 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 134/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.135s, data_time: 0.005s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 7.734e-03, size: 320, ETA: 2:15:42
2025-09-01 07:54:31.123 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 134/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, data_time: 0.008s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.729e-03, size: 544, ETA: 2:15:38
2025-09-01 07:54:33.939 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 134/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.724e-03, size: 512, ETA: 2:15:36
2025-09-01 07:54:36.715 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 134/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.131s, data_time: 0.034s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.719e-03, size: 288, ETA: 2:15:33
2025-09-01 07:54:39.549 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 134/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.137s, data_time: 0.041s, total_loss: 5.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 7.714e-03, size: 352, ETA: 2:15:30
2025-09-01 07:54:40.806 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:54:40.946 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch135
2025-09-01 07:54:43.635 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 135/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, data_time: 0.032s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.707e-03, size: 544, ETA: 2:15:25
2025-09-01 07:54:46.453 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 135/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.137s, data_time: 0.050s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 7.702e-03, size: 480, ETA: 2:15:23
2025-09-01 07:54:49.232 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 135/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.127s, data_time: 0.042s, total_loss: 7.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.697e-03, size: 288, ETA: 2:15:19
2025-09-01 07:54:52.082 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 135/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.137s, data_time: 0.064s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.692e-03, size: 480, ETA: 2:15:17
2025-09-01 07:54:54.996 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 135/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.144s, data_time: 0.068s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 7.687e-03, size: 352, ETA: 2:15:15
2025-09-01 07:54:57.902 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 135/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.132s, data_time: 0.055s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.682e-03, size: 480, ETA: 2:15:12
2025-09-01 07:54:59.085 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:55:05.069 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:55:11.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:55:17.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4919
2025-09-01 07:55:17.818 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4464
2025-09-01 07:55:17.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2292
2025-09-01 07:55:17.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3892
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.492
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.446
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.229
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.389
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:55:17.931 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:55:17.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:55:17.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:55:17.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:55:17.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:55:24.086 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:55:30.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:55:36.308 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:55:42.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:55:49.246 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:55:55.886 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:56:02.009 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:56:08.196 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:56:14.267 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:56:14.267 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-09-01 07:56:14.267 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.39
2025-09-01 07:56:14.268 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:56:14.294 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.41 ms, Average NMS time: 1.01 ms, Average inference time: 2.42 ms

2025-09-01 07:56:14.295 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:56:14.321 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:56:14.353 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch136
2025-09-01 07:56:16.842 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 136/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.120s, data_time: 0.039s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 7.674e-03, size: 448, ETA: 2:15:07
2025-09-01 07:56:19.764 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 136/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.145s, data_time: 0.066s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.669e-03, size: 544, ETA: 2:15:05
2025-09-01 07:56:22.631 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 136/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.134s, data_time: 0.031s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 7.664e-03, size: 288, ETA: 2:15:02
2025-09-01 07:56:25.378 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 136/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.121s, data_time: 0.005s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.659e-03, size: 384, ETA: 2:14:58
2025-09-01 07:56:28.301 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 136/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 7.654e-03, size: 416, ETA: 2:14:55
2025-09-01 07:56:31.224 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 136/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.130s, 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: 7.649e-03, size: 576, ETA: 2:14:52
2025-09-01 07:56:32.415 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:56:32.586 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch137
2025-09-01 07:56:35.465 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 137/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.126s, 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: 7.642e-03, size: 544, ETA: 2:14:47
2025-09-01 07:56:38.258 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 137/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.126s, data_time: 0.012s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.637e-03, size: 512, ETA: 2:14:44
2025-09-01 07:56:41.124 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 137/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.124s, data_time: 0.005s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 7.632e-03, size: 544, ETA: 2:14:40
2025-09-01 07:56:43.983 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 137/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.121s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.627e-03, size: 256, ETA: 2:14:37
2025-09-01 07:56:46.879 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 137/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.621e-03, size: 256, ETA: 2:14:33
2025-09-01 07:56:49.679 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 137/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.124s, data_time: 0.005s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 7.616e-03, size: 416, ETA: 2:14:30
2025-09-01 07:56:50.907 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:56:50.945 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch138
2025-09-01 07:56:53.851 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 138/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.128s, data_time: 0.007s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.609e-03, size: 384, ETA: 2:14:25
2025-09-01 07:56:56.593 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 138/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.604e-03, size: 320, ETA: 2:14:21
2025-09-01 07:56:59.352 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 138/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.126s, data_time: 0.020s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.599e-03, size: 320, ETA: 2:14:18
2025-09-01 07:57:02.167 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 138/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.130s, data_time: 0.005s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 7.594e-03, size: 448, ETA: 2:14:15
2025-09-01 07:57:05.048 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 138/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.131s, data_time: 0.007s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.2, lr: 7.589e-03, size: 480, ETA: 2:14:12
2025-09-01 07:57:07.849 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 138/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.130s, data_time: 0.017s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.584e-03, size: 544, ETA: 2:14:09
2025-09-01 07:57:09.120 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:57:09.215 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch139
2025-09-01 07:57:12.018 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 139/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.122s, data_time: 0.020s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 7.576e-03, size: 320, ETA: 2:14:04
2025-09-01 07:57:14.885 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 139/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.134s, data_time: 0.035s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.571e-03, size: 256, ETA: 2:14:02
2025-09-01 07:57:17.640 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 139/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.566e-03, size: 320, ETA: 2:13:59
2025-09-01 07:57:20.591 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 139/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.147s, data_time: 0.066s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 7.561e-03, size: 480, ETA: 2:13:57
2025-09-01 07:57:23.494 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 139/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.144s, data_time: 0.060s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 7.556e-03, size: 352, ETA: 2:13:55
2025-09-01 07:57:26.388 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 139/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.144s, data_time: 0.061s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 7.551e-03, size: 480, ETA: 2:13:53
2025-09-01 07:57:27.686 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:57:27.736 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch140
2025-09-01 07:57:30.520 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 140/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.138s, data_time: 0.056s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 7.543e-03, size: 256, ETA: 2:13:49
2025-09-01 07:57:33.306 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 140/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.136s, data_time: 0.058s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.538e-03, size: 416, ETA: 2:13:47
2025-09-01 07:57:36.080 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 140/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.130s, data_time: 0.051s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 7.533e-03, size: 448, ETA: 2:13:44
2025-09-01 07:57:39.001 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 140/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.138s, data_time: 0.021s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.528e-03, size: 352, ETA: 2:13:41
2025-09-01 07:57:41.865 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 140/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.017s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 7.523e-03, size: 352, ETA: 2:13:38
2025-09-01 07:57:44.702 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 140/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.127s, data_time: 0.004s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.517e-03, size: 384, ETA: 2:13:35
2025-09-01 07:57:45.902 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:57:51.960 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 07:57:56.901 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 07:58:00.324 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4956
2025-09-01 07:58:00.912 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4784
2025-09-01 07:58:01.027 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2664
2025-09-01 07:58:01.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4135
2025-09-01 07:58:01.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 07:58:01.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 07:58:01.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.496
2025-09-01 07:58:01.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.478
2025-09-01 07:58:01.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.266
2025-09-01 07:58:01.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.413
2025-09-01 07:58:01.028 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 07:58:01.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 07:58:01.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 07:58:01.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 07:58:01.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 07:58:01.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 07:58:01.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 07:58:01.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 07:58:01.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 07:58:05.307 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 07:58:09.525 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 07:58:13.732 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 07:58:17.876 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 07:58:22.004 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 07:58:26.165 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 07:58:30.332 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 07:58:34.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 07:58:38.564 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 07:58:38.565 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-09-01 07:58:38.565 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.41
2025-09-01 07:58:38.565 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 07:58:38.593 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.95 ms, Average inference time: 2.33 ms

2025-09-01 07:58:38.594 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:58:38.626 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:58:38.658 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch141
2025-09-01 07:58:41.138 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 141/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.123s, data_time: 0.043s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.510e-03, size: 544, ETA: 2:13:30
2025-09-01 07:58:43.878 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 141/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.055s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 7.505e-03, size: 320, ETA: 2:13:27
2025-09-01 07:58:46.741 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 141/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.138s, data_time: 0.049s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 7.500e-03, size: 448, ETA: 2:13:25
2025-09-01 07:58:49.723 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 141/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.023s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 7.494e-03, size: 544, ETA: 2:13:22
2025-09-01 07:58:52.652 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 141/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 7.489e-03, size: 256, ETA: 2:13:19
2025-09-01 07:58:55.408 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 141/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.124s, data_time: 0.017s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 7.484e-03, size: 320, ETA: 2:13:16
2025-09-01 07:58:56.728 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:58:56.765 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch142
2025-09-01 07:58:59.599 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 142/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.129s, 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: 7.477e-03, size: 320, ETA: 2:13:12
2025-09-01 07:59:02.410 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 142/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.128s, data_time: 0.012s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.471e-03, size: 352, ETA: 2:13:09
2025-09-01 07:59:05.382 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 142/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 7.466e-03, size: 448, ETA: 2:13:06
2025-09-01 07:59:08.277 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 142/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 7.461e-03, size: 576, ETA: 2:13:03
2025-09-01 07:59:11.092 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 142/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 7.456e-03, size: 352, ETA: 2:13:00
2025-09-01 07:59:13.963 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 142/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.129s, data_time: 0.005s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.451e-03, size: 384, ETA: 2:12:57
2025-09-01 07:59:15.238 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:59:15.356 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch143
2025-09-01 07:59:18.118 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 143/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.122s, data_time: 0.009s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 7.443e-03, size: 480, ETA: 2:12:52
2025-09-01 07:59:20.840 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 143/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.132s, data_time: 0.034s, total_loss: 5.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.7, lr: 7.438e-03, size: 384, ETA: 2:12:49
2025-09-01 07:59:23.748 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 143/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.144s, data_time: 0.063s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.433e-03, size: 256, ETA: 2:12:47
2025-09-01 07:59:26.541 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 143/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.048s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 7.428e-03, size: 448, ETA: 2:12:44
2025-09-01 07:59:29.386 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 143/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.140s, data_time: 0.012s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.422e-03, size: 352, ETA: 2:12:42
2025-09-01 07:59:32.181 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 143/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.136s, data_time: 0.047s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 7.417e-03, size: 416, ETA: 2:12:39
2025-09-01 07:59:33.483 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:59:33.533 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch144
2025-09-01 07:59:36.409 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 144/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.410e-03, size: 544, ETA: 2:12:36
2025-09-01 07:59:39.257 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 144/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.139s, data_time: 0.061s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 7.404e-03, size: 576, ETA: 2:12:33
2025-09-01 07:59:42.210 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 144/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.147s, data_time: 0.064s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 7.399e-03, size: 384, ETA: 2:12:31
2025-09-01 07:59:45.011 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 144/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 7.394e-03, size: 448, ETA: 2:12:29
2025-09-01 07:59:47.888 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 144/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.142s, data_time: 0.068s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.389e-03, size: 288, ETA: 2:12:26
2025-09-01 07:59:50.759 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 144/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.143s, data_time: 0.060s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.384e-03, size: 512, ETA: 2:12:24
2025-09-01 07:59:51.932 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 07:59:51.969 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch145
2025-09-01 07:59:54.793 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 145/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 7.376e-03, size: 288, ETA: 2:12:20
2025-09-01 07:59:57.567 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 145/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.371e-03, size: 416, ETA: 2:12:18
2025-09-01 08:00:00.338 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 145/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.054s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 7.365e-03, size: 320, ETA: 2:12:15
2025-09-01 08:00:03.242 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 145/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.143s, data_time: 0.064s, total_loss: 8.1, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 7.360e-03, size: 256, ETA: 2:12:13
2025-09-01 08:00:06.025 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 145/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.355e-03, size: 512, ETA: 2:12:11
2025-09-01 08:00:08.847 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 145/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.131s, data_time: 0.049s, 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: 480, ETA: 2:12:08
2025-09-01 08:00:10.089 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:00:16.027 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:00:17.794 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:00:18.878 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4839
2025-09-01 08:00:19.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4152
2025-09-01 08:00:19.263 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2092
2025-09-01 08:00:19.264 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3694
2025-09-01 08:00:19.264 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:00:19.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:00:19.265 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.484
2025-09-01 08:00:19.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.415
2025-09-01 08:00:19.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.209
2025-09-01 08:00:19.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.369
2025-09-01 08:00:19.267 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:00:19.267 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:00:19.268 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:00:19.268 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:00:19.268 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:00:19.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:00:19.269 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:00:19.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:00:19.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:00:20.710 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:00:22.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:00:23.540 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:00:24.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:00:26.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:00:27.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:00:29.158 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:00:30.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:00:31.951 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:00:31.951 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.18
2025-09-01 08:00:31.951 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.37
2025-09-01 08:00:31.951 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:00:31.960 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.98 ms, Average inference time: 2.38 ms

2025-09-01 08:00:31.962 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:00:31.988 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:00:32.018 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch146
2025-09-01 08:00:34.488 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 146/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.123s, data_time: 0.042s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.342e-03, size: 448, ETA: 2:12:03
2025-09-01 08:00:37.418 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 146/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.040s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.337e-03, size: 384, ETA: 2:12:00
2025-09-01 08:00:40.233 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 146/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.139s, data_time: 0.054s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 7.332e-03, size: 512, ETA: 2:11:58
2025-09-01 08:00:42.966 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 146/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.054s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 7.326e-03, size: 416, ETA: 2:11:55
2025-09-01 08:00:45.832 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 146/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.138s, data_time: 0.060s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 7.321e-03, size: 288, ETA: 2:11:52
2025-09-01 08:00:48.754 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 146/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.140s, data_time: 0.062s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 7.316e-03, size: 576, ETA: 2:11:50
2025-09-01 08:00:49.904 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:00:49.942 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch147
2025-09-01 08:00:52.815 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 147/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.141s, data_time: 0.023s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.308e-03, size: 416, ETA: 2:11:46
2025-09-01 08:00:55.724 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 147/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.143s, data_time: 0.017s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.303e-03, size: 384, ETA: 2:11:44
2025-09-01 08:00:58.643 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 147/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.298e-03, size: 288, ETA: 2:11:42
2025-09-01 08:01:01.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 147/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.132s, data_time: 0.020s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 7.292e-03, size: 416, ETA: 2:11:39
2025-09-01 08:01:04.213 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 147/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.141s, data_time: 0.064s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.287e-03, size: 448, ETA: 2:11:37
2025-09-01 08:01:07.093 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 147/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.143s, data_time: 0.058s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.282e-03, size: 416, ETA: 2:11:34
2025-09-01 08:01:08.313 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:01:08.352 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch148
2025-09-01 08:01:11.187 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 148/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.141s, data_time: 0.056s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.1, lr: 7.274e-03, size: 448, ETA: 2:11:31
2025-09-01 08:01:13.969 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 148/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.047s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.269e-03, size: 256, ETA: 2:11:28
2025-09-01 08:01:16.735 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 148/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 7.263e-03, size: 416, ETA: 2:11:25
2025-09-01 08:01:19.563 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 148/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.138s, data_time: 0.055s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.258e-03, size: 352, ETA: 2:11:23
2025-09-01 08:01:22.437 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 148/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.253e-03, size: 576, ETA: 2:11:21
2025-09-01 08:01:25.308 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 148/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.143s, data_time: 0.056s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 7.247e-03, size: 480, ETA: 2:11:18
2025-09-01 08:01:26.641 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:01:26.686 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch149
2025-09-01 08:01:29.379 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 149/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.059s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 7.240e-03, size: 320, ETA: 2:11:15
2025-09-01 08:01:32.254 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 149/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.142s, data_time: 0.071s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 7.234e-03, size: 544, ETA: 2:11:13
2025-09-01 08:01:35.128 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 149/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.229e-03, size: 448, ETA: 2:11:10
2025-09-01 08:01:37.946 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 149/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.224e-03, size: 288, ETA: 2:11:08
2025-09-01 08:01:40.781 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 149/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.140s, data_time: 0.056s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.218e-03, size: 416, ETA: 2:11:05
2025-09-01 08:01:43.588 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 149/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.133s, data_time: 0.039s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 7.213e-03, size: 416, ETA: 2:11:03
2025-09-01 08:01:44.718 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:01:44.807 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch150
2025-09-01 08:01:47.572 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 150/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.133s, data_time: 0.036s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 7.205e-03, size: 384, ETA: 2:10:58
2025-09-01 08:01:50.519 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 150/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.143s, data_time: 0.062s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.200e-03, size: 576, ETA: 2:10:56
2025-09-01 08:01:53.365 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 150/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.134s, data_time: 0.010s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 7.195e-03, size: 352, ETA: 2:10:53
2025-09-01 08:01:56.247 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 150/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.1, lr: 7.189e-03, size: 416, ETA: 2:10:51
2025-09-01 08:01:59.323 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 150/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.1Gb, iter_time: 0.142s, data_time: 0.004s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.184e-03, size: 576, ETA: 2:10:48
2025-09-01 08:02:02.236 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 150/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, 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: 7.179e-03, size: 576, ETA: 2:10:46
2025-09-01 08:02:03.430 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:02:09.309 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:02:10.661 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:02:11.352 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4914
2025-09-01 08:02:11.418 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4663
2025-09-01 08:02:11.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2302
2025-09-01 08:02:11.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3960
2025-09-01 08:02:11.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:02:11.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:02:11.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.491
2025-09-01 08:02:11.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.466
2025-09-01 08:02:11.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.230
2025-09-01 08:02:11.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.396
2025-09-01 08:02:11.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:02:11.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:02:11.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:02:11.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:02:11.512 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:02:11.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:02:11.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:02:11.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:02:11.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:02:12.285 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:02:13.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:02:13.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:02:14.615 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:02:15.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:02:16.152 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:02:16.972 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:02:17.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:02:18.484 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:02:18.485 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-09-01 08:02:18.485 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-09-01 08:02:18.485 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:02:18.495 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.93 ms, Average inference time: 2.30 ms

2025-09-01 08:02:18.496 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:02:18.578 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:02:18.620 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch151
2025-09-01 08:02:21.045 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 151/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.120s, data_time: 0.030s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 7.171e-03, size: 416, ETA: 2:10:41
2025-09-01 08:02:23.797 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 151/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.030s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 7.166e-03, size: 384, ETA: 2:10:38
2025-09-01 08:02:26.707 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 151/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.144s, data_time: 0.039s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.160e-03, size: 320, ETA: 2:10:36
2025-09-01 08:02:29.633 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 151/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.143s, data_time: 0.023s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.155e-03, size: 512, ETA: 2:10:34
2025-09-01 08:02:32.653 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 151/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.150s, data_time: 0.004s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 7.149e-03, size: 416, ETA: 2:10:32
2025-09-01 08:02:35.414 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 151/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.136s, 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: 7.144e-03, size: 512, ETA: 2:10:29
2025-09-01 08:02:36.634 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:02:36.782 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch152
2025-09-01 08:02:39.671 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 152/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, 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: 7.136e-03, size: 480, ETA: 2:10:25
2025-09-01 08:02:42.533 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 152/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 7.131e-03, size: 512, ETA: 2:10:23
2025-09-01 08:02:45.396 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 152/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 7.126e-03, size: 512, ETA: 2:10:20
2025-09-01 08:02:48.153 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 152/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.120e-03, size: 416, ETA: 2:10:17
2025-09-01 08:02:51.064 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 152/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, 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: 7.115e-03, size: 544, ETA: 2:10:14
2025-09-01 08:02:53.976 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 152/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.109e-03, size: 352, ETA: 2:10:12
2025-09-01 08:02:55.161 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:02:55.198 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch153
2025-09-01 08:02:58.054 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 153/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.141s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 7.102e-03, size: 448, ETA: 2:10:08
2025-09-01 08:03:00.826 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 153/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.136s, data_time: 0.007s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 7.096e-03, size: 320, ETA: 2:10:05
2025-09-01 08:03:03.822 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 153/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.147s, data_time: 0.004s, total_loss: 7.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.091e-03, size: 288, ETA: 2:10:03
2025-09-01 08:03:06.627 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 153/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.138s, 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: 7.085e-03, size: 480, ETA: 2:10:01
2025-09-01 08:03:09.489 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 153/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.140s, data_time: 0.050s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 7.080e-03, size: 320, ETA: 2:09:58
2025-09-01 08:03:12.226 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 153/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.058s, total_loss: 7.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 7.075e-03, size: 320, ETA: 2:09:56
2025-09-01 08:03:13.705 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:03:13.742 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch154
2025-09-01 08:03:16.378 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 154/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.130s, data_time: 0.047s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 7.067e-03, size: 416, ETA: 2:09:52
2025-09-01 08:03:19.277 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 154/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.138s, data_time: 0.008s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 7.061e-03, size: 576, ETA: 2:09:49
2025-09-01 08:03:22.120 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 154/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.1, lr: 7.056e-03, size: 288, ETA: 2:09:47
2025-09-01 08:03:24.961 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 154/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.050e-03, size: 416, ETA: 2:09:44
2025-09-01 08:03:27.790 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 154/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.136s, 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: 7.045e-03, size: 352, ETA: 2:09:41
2025-09-01 08:03:30.657 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 154/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.022s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.040e-03, size: 480, ETA: 2:09:39
2025-09-01 08:03:31.907 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:03:31.950 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch155
2025-09-01 08:03:34.722 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 155/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.013s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.032e-03, size: 416, ETA: 2:09:35
2025-09-01 08:03:37.533 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 155/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.136s, data_time: 0.012s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 7.026e-03, size: 480, ETA: 2:09:32
2025-09-01 08:03:40.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 155/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.141s, data_time: 0.011s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.021e-03, size: 544, ETA: 2:09:30
2025-09-01 08:03:43.123 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 155/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.131s, data_time: 0.026s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.015e-03, size: 416, ETA: 2:09:27
2025-09-01 08:03:45.908 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 155/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.136s, data_time: 0.047s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 7.010e-03, size: 320, ETA: 2:09:24
2025-09-01 08:03:48.802 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 155/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.141s, data_time: 0.026s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.005e-03, size: 448, ETA: 2:09:22
2025-09-01 08:03:49.985 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:03:56.099 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:04:02.577 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:04:06.837 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5432
2025-09-01 08:04:07.406 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4876
2025-09-01 08:04:07.561 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3080
2025-09-01 08:04:07.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4463
2025-09-01 08:04:07.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.543
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.488
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.308
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.446
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:04:07.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:04:07.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:04:07.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:04:07.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:04:12.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:04:17.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:04:22.328 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:04:27.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:04:31.975 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:04:36.795 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:04:41.515 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:04:46.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:04:50.902 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:04:50.903 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-09-01 08:04:50.903 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-09-01 08:04:50.903 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:04:50.929 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.42 ms, Average NMS time: 0.98 ms, Average inference time: 2.41 ms

2025-09-01 08:04:50.931 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:04:50.965 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:04:50.998 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch156
2025-09-01 08:04:53.490 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 156/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.122s, data_time: 0.044s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 6.997e-03, size: 352, ETA: 2:09:17
2025-09-01 08:04:56.329 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 156/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.060s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.991e-03, size: 320, ETA: 2:09:15
2025-09-01 08:04:59.137 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 156/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.986e-03, size: 512, ETA: 2:09:12
2025-09-01 08:05:01.971 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 156/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.980e-03, size: 480, ETA: 2:09:10
2025-09-01 08:05:04.843 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 156/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.032s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.9, lr: 6.975e-03, size: 512, ETA: 2:09:07
2025-09-01 08:05:07.781 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 156/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.005s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 6.969e-03, size: 288, ETA: 2:09:04
2025-09-01 08:05:08.901 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:05:09.015 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch157
2025-09-01 08:05:11.834 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 157/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.961e-03, size: 448, ETA: 2:09:00
2025-09-01 08:05:14.700 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 157/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.140s, data_time: 0.007s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 6.956e-03, size: 256, ETA: 2:08:57
2025-09-01 08:05:17.475 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 157/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.136s, data_time: 0.031s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.951e-03, size: 288, ETA: 2:08:55
2025-09-01 08:05:20.480 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 157/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.145s, data_time: 0.036s, total_loss: 8.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.6, lr: 6.945e-03, size: 352, ETA: 2:08:52
2025-09-01 08:05:23.297 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 157/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.940e-03, size: 256, ETA: 2:08:50
2025-09-01 08:05:26.110 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 157/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.013s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.934e-03, size: 288, ETA: 2:08:47
2025-09-01 08:05:27.268 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:05:27.459 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch158
2025-09-01 08:05:30.349 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 158/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.031s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 6.926e-03, size: 448, ETA: 2:08:43
2025-09-01 08:05:33.185 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 158/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.133s, 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: 6.921e-03, size: 416, ETA: 2:08:40
2025-09-01 08:05:35.856 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 158/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.125s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.915e-03, size: 320, ETA: 2:08:37
2025-09-01 08:05:38.748 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 158/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.012s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.910e-03, size: 480, ETA: 2:08:34
2025-09-01 08:05:41.642 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 158/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.046s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.904e-03, size: 512, ETA: 2:08:31
2025-09-01 08:05:44.409 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 158/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.133s, data_time: 0.048s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 6.899e-03, size: 256, ETA: 2:08:29
2025-09-01 08:05:45.703 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:05:45.742 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch159
2025-09-01 08:05:48.521 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 159/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.013s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 6.891e-03, size: 256, ETA: 2:08:25
2025-09-01 08:05:51.341 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 159/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.128s, data_time: 0.015s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 6.885e-03, size: 480, ETA: 2:08:22
2025-09-01 08:05:54.118 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 159/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 6.880e-03, size: 512, ETA: 2:08:19
2025-09-01 08:05:56.813 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 159/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.128s, data_time: 0.034s, total_loss: 7.9, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 6.874e-03, size: 448, ETA: 2:08:15
2025-09-01 08:05:59.620 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 159/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.134s, data_time: 0.037s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.869e-03, size: 576, ETA: 2:08:13
2025-09-01 08:06:02.452 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 159/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.130s, data_time: 0.036s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.3, lr: 6.863e-03, size: 288, ETA: 2:08:10
2025-09-01 08:06:03.699 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:06:03.743 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch160
2025-09-01 08:06:06.605 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 160/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.132s, data_time: 0.005s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.855e-03, size: 448, ETA: 2:08:05
2025-09-01 08:06:09.420 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 160/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.127s, data_time: 0.009s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 6.850e-03, size: 288, ETA: 2:08:02
2025-09-01 08:06:12.223 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 160/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 6.844e-03, size: 320, ETA: 2:08:00
2025-09-01 08:06:15.063 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 160/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.839e-03, size: 544, ETA: 2:07:57
2025-09-01 08:06:17.875 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 160/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.134s, data_time: 0.055s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.833e-03, size: 416, ETA: 2:07:54
2025-09-01 08:06:20.715 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 160/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.044s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 6.828e-03, size: 544, ETA: 2:07:52
2025-09-01 08:06:21.967 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:06:27.916 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:06:28.824 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:06:29.401 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5362
2025-09-01 08:06:29.488 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4675
2025-09-01 08:06:29.571 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2747
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4261
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.536
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.468
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.275
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.426
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:06:29.572 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:06:29.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:06:29.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:06:29.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:06:29.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:06:29.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:06:29.573 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:06:30.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:06:30.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:06:31.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:06:32.307 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:06:33.013 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:06:33.679 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:06:34.356 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:06:35.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:06:35.725 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:06:35.725 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-09-01 08:06:35.725 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-09-01 08:06:35.725 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:06:35.732 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.95 ms, Average inference time: 2.30 ms

2025-09-01 08:06:35.734 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:06:35.760 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:06:35.790 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch161
2025-09-01 08:06:38.237 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 161/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.117s, data_time: 0.026s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.820e-03, size: 352, ETA: 2:07:47
2025-09-01 08:06:41.060 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 161/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.139s, data_time: 0.060s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.814e-03, size: 384, ETA: 2:07:44
2025-09-01 08:06:43.986 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 161/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.146s, data_time: 0.065s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 6.809e-03, size: 448, ETA: 2:07:42
2025-09-01 08:06:46.822 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 161/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.136s, data_time: 0.040s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 6.803e-03, size: 480, ETA: 2:07:39
2025-09-01 08:06:49.642 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 161/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.134s, data_time: 0.044s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.798e-03, size: 384, ETA: 2:07:37
2025-09-01 08:06:52.501 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 161/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.132s, data_time: 0.009s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.792e-03, size: 288, ETA: 2:07:34
2025-09-01 08:06:53.704 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:06:53.763 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch162
2025-09-01 08:06:56.515 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 162/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.131s, data_time: 0.042s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.784e-03, size: 352, ETA: 2:07:29
2025-09-01 08:06:59.394 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 162/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.130s, data_time: 0.005s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.778e-03, size: 320, ETA: 2:07:26
2025-09-01 08:07:02.283 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 162/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.773e-03, size: 480, ETA: 2:07:24
2025-09-01 08:07:05.090 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 162/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.131s, data_time: 0.006s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 6.767e-03, size: 544, ETA: 2:07:21
2025-09-01 08:07:07.980 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 162/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 6.762e-03, size: 320, ETA: 2:07:18
2025-09-01 08:07:10.797 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 162/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.129s, data_time: 0.034s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.756e-03, size: 384, ETA: 2:07:15
2025-09-01 08:07:11.971 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:07:12.140 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch163
2025-09-01 08:07:14.975 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 163/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.127s, data_time: 0.038s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.748e-03, size: 576, ETA: 2:07:10
2025-09-01 08:07:17.829 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 163/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.130s, data_time: 0.045s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.743e-03, size: 416, ETA: 2:07:07
2025-09-01 08:07:20.667 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 163/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.127s, data_time: 0.022s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 6.737e-03, size: 576, ETA: 2:07:04
2025-09-01 08:07:23.532 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 163/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.129s, 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: 6.731e-03, size: 352, ETA: 2:07:01
2025-09-01 08:07:26.272 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 163/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.124s, data_time: 0.018s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 6.726e-03, size: 448, ETA: 2:06:58
2025-09-01 08:07:29.177 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 163/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 6.720e-03, size: 544, ETA: 2:06:54
2025-09-01 08:07:30.320 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:07:30.373 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch164
2025-09-01 08:07:33.114 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 164/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.125s, 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: 6.712e-03, size: 256, ETA: 2:06:50
2025-09-01 08:07:35.958 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 164/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.130s, data_time: 0.006s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.707e-03, size: 576, ETA: 2:06:47
2025-09-01 08:07:38.826 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 164/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 6.701e-03, size: 576, ETA: 2:06:44
2025-09-01 08:07:41.701 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 164/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 6.696e-03, size: 448, ETA: 2:06:41
2025-09-01 08:07:44.660 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 164/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.015s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.690e-03, size: 288, ETA: 2:06:38
2025-09-01 08:07:47.461 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 164/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.133s, data_time: 0.007s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 6.684e-03, size: 256, ETA: 2:06:35
2025-09-01 08:07:48.697 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:07:48.747 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch165
2025-09-01 08:07:51.494 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 165/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.045s, total_loss: 8.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 6.676e-03, size: 256, ETA: 2:06:31
2025-09-01 08:07:54.486 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 165/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.147s, data_time: 0.065s, total_loss: 6.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.6, lr: 6.671e-03, size: 480, ETA: 2:06:29
2025-09-01 08:07:57.439 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 165/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.143s, data_time: 0.015s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.665e-03, size: 384, ETA: 2:06:27
2025-09-01 08:08:00.225 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 165/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.134s, data_time: 0.013s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.659e-03, size: 512, ETA: 2:06:24
2025-09-01 08:08:03.085 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 165/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.142s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 6.654e-03, size: 448, ETA: 2:06:22
2025-09-01 08:08:05.967 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 165/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.141s, 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: 6.648e-03, size: 512, ETA: 2:06:20
2025-09-01 08:08:07.101 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:08:13.285 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:08:15.734 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:08:17.714 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5395
2025-09-01 08:08:17.842 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4868
2025-09-01 08:08:17.916 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2604
2025-09-01 08:08:17.917 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4289
2025-09-01 08:08:17.917 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:08:17.917 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:08:17.917 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.540
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.487
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.260
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.429
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:08:17.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:08:17.919 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:08:20.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:08:22.306 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:08:24.497 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:08:26.719 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:08:28.856 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:08:31.053 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:08:33.198 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:08:35.295 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:08:37.389 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:08:37.390 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-09-01 08:08:37.390 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-09-01 08:08:37.390 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:08:37.418 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.96 ms, Average inference time: 2.33 ms

2025-09-01 08:08:37.419 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:08:37.444 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:08:37.476 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch166
2025-09-01 08:08:39.954 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 166/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.120s, data_time: 0.036s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.640e-03, size: 448, ETA: 2:06:15
2025-09-01 08:08:42.813 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 166/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.132s, data_time: 0.021s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.635e-03, size: 256, ETA: 2:06:12
2025-09-01 08:08:45.550 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 166/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.127s, data_time: 0.044s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.629e-03, size: 480, ETA: 2:06:09
2025-09-01 08:08:48.384 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 166/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.133s, data_time: 0.031s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 6.623e-03, size: 416, ETA: 2:06:06
2025-09-01 08:08:51.168 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 166/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.133s, data_time: 0.031s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 6.618e-03, size: 448, ETA: 2:06:03
2025-09-01 08:08:54.140 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 166/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.140s, data_time: 0.032s, total_loss: 7.8, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 6.612e-03, size: 288, ETA: 2:06:01
2025-09-01 08:08:55.393 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:08:55.431 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch167
2025-09-01 08:08:58.037 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 167/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.125s, data_time: 0.024s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 6.604e-03, size: 288, ETA: 2:05:56
2025-09-01 08:09:01.017 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 167/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.145s, data_time: 0.026s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.598e-03, size: 576, ETA: 2:05:54
2025-09-01 08:09:03.853 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 167/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 6.593e-03, size: 320, ETA: 2:05:52
2025-09-01 08:09:06.679 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 167/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.587e-03, size: 288, ETA: 2:05:49
2025-09-01 08:09:09.575 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 167/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.144s, data_time: 0.062s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 6.582e-03, size: 416, ETA: 2:05:47
2025-09-01 08:09:12.325 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 167/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.011s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.576e-03, size: 448, ETA: 2:05:44
2025-09-01 08:09:13.518 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:09:13.642 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch168
2025-09-01 08:09:16.495 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 168/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.135s, data_time: 0.008s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.568e-03, size: 288, ETA: 2:05:40
2025-09-01 08:09:19.295 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 168/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.136s, data_time: 0.045s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 6.562e-03, size: 384, ETA: 2:05:37
2025-09-01 08:09:22.092 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 168/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 6.557e-03, size: 576, ETA: 2:05:35
2025-09-01 08:09:24.813 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 168/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.133s, data_time: 0.053s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.551e-03, size: 288, ETA: 2:05:32
2025-09-01 08:09:27.715 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 168/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.144s, data_time: 0.067s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 6.545e-03, size: 416, ETA: 2:05:30
2025-09-01 08:09:30.506 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 168/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.058s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 6.540e-03, size: 384, ETA: 2:05:27
2025-09-01 08:09:31.727 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:09:31.763 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch169
2025-09-01 08:09:34.713 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 169/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.144s, data_time: 0.014s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 6.531e-03, size: 256, ETA: 2:05:24
2025-09-01 08:09:37.585 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 169/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.141s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 6.526e-03, size: 544, ETA: 2:05:21
2025-09-01 08:09:40.340 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 169/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.137s, 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: 6.520e-03, size: 544, ETA: 2:05:19
2025-09-01 08:09:43.209 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 169/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.141s, 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: 6.515e-03, size: 256, ETA: 2:05:16
2025-09-01 08:09:46.033 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 169/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.139s, data_time: 0.035s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 6.509e-03, size: 352, ETA: 2:05:14
2025-09-01 08:09:48.908 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 169/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.503e-03, size: 416, ETA: 2:05:11
2025-09-01 08:09:50.253 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:09:50.294 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch170
2025-09-01 08:09:53.074 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 170/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.137s, data_time: 0.063s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.495e-03, size: 544, ETA: 2:05:08
2025-09-01 08:09:55.927 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 170/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.136s, data_time: 0.025s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 6.489e-03, size: 352, ETA: 2:05:05
2025-09-01 08:09:58.672 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 170/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.133s, data_time: 0.041s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.484e-03, size: 352, ETA: 2:05:03
2025-09-01 08:10:01.714 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 170/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.143s, data_time: 0.031s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.478e-03, size: 576, ETA: 2:05:00
2025-09-01 08:10:04.542 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 170/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.133s, data_time: 0.011s, total_loss: 8.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.0, lr: 6.472e-03, size: 448, ETA: 2:04:57
2025-09-01 08:10:07.376 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 170/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.134s, 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: 6.467e-03, size: 480, ETA: 2:04:55
2025-09-01 08:10:08.558 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:10:14.459 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:10:16.358 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:10:17.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5267
2025-09-01 08:10:18.040 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4624
2025-09-01 08:10:18.092 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2948
2025-09-01 08:10:18.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4280
2025-09-01 08:10:18.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:10:18.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:10:18.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.527
2025-09-01 08:10:18.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.462
2025-09-01 08:10:18.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.295
2025-09-01 08:10:18.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.428
2025-09-01 08:10:18.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:10:18.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:10:18.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:10:18.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:10:18.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:10:18.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:10:18.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:10:18.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:10:18.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:10:19.659 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:10:21.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:10:22.720 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:10:24.378 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:10:26.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:10:27.885 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:10:29.443 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:10:31.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:10:32.658 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:10:32.658 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.19
2025-09-01 08:10:32.658 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-09-01 08:10:32.658 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:10:32.687 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.96 ms, Average inference time: 2.31 ms

2025-09-01 08:10:32.688 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:10:32.720 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:10:32.752 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch171
2025-09-01 08:10:35.314 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 171/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.127s, data_time: 0.047s, total_loss: 7.6, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 6.459e-03, size: 288, ETA: 2:04:50
2025-09-01 08:10:38.213 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 171/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.144s, data_time: 0.020s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 6.453e-03, size: 544, ETA: 2:04:48
2025-09-01 08:10:40.975 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 171/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.133s, data_time: 0.006s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.447e-03, size: 256, ETA: 2:04:45
2025-09-01 08:10:43.831 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 171/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.140s, data_time: 0.008s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.442e-03, size: 256, ETA: 2:04:43
2025-09-01 08:10:46.831 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 171/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.148s, data_time: 0.001s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.436e-03, size: 480, ETA: 2:04:41
2025-09-01 08:10:49.610 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 171/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.137s, data_time: 0.024s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.430e-03, size: 416, ETA: 2:04:38
2025-09-01 08:10:50.987 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:10:51.023 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch172
2025-09-01 08:10:53.802 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 172/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.058s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.422e-03, size: 448, ETA: 2:04:35
2025-09-01 08:10:56.759 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 172/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.146s, data_time: 0.063s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.416e-03, size: 576, ETA: 2:04:32
2025-09-01 08:10:59.491 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 172/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.134s, data_time: 0.052s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 6.411e-03, size: 512, ETA: 2:04:30
2025-09-01 08:11:02.331 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 172/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.131s, data_time: 0.025s, total_loss: 5.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 6.405e-03, size: 256, ETA: 2:04:27
2025-09-01 08:11:05.122 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 172/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.399e-03, size: 352, ETA: 2:04:24
2025-09-01 08:11:07.950 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 172/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 4.3, cls_loss: 0.7, lr: 6.394e-03, size: 448, ETA: 2:04:21
2025-09-01 08:11:09.084 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:11:09.141 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch173
2025-09-01 08:11:11.956 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 173/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 6.385e-03, size: 288, ETA: 2:04:17
2025-09-01 08:11:14.772 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 173/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.380e-03, size: 288, ETA: 2:04:14
2025-09-01 08:11:17.626 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 173/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.374e-03, size: 256, ETA: 2:04:12
2025-09-01 08:11:20.511 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 173/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.141s, data_time: 0.001s, total_loss: 8.5, iou_loss: 3.6, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 6.368e-03, size: 256, ETA: 2:04:10
2025-09-01 08:11:23.466 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 173/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.2Gb, iter_time: 0.145s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.363e-03, size: 384, ETA: 2:04:07
2025-09-01 08:11:26.171 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 173/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.132s, data_time: 0.014s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.357e-03, size: 320, ETA: 2:04:04
2025-09-01 08:11:27.383 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:11:27.546 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch174
2025-09-01 08:11:30.258 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 174/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.058s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.349e-03, size: 576, ETA: 2:04:00
2025-09-01 08:11:33.156 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 174/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.143s, data_time: 0.066s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 6.343e-03, size: 384, ETA: 2:03:58
2025-09-01 08:11:36.018 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 174/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.142s, data_time: 0.066s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 6.337e-03, size: 352, ETA: 2:03:56
2025-09-01 08:11:38.878 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 174/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.331e-03, size: 512, ETA: 2:03:53
2025-09-01 08:11:41.691 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 174/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.326e-03, size: 576, ETA: 2:03:51
2025-09-01 08:11:44.554 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 174/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.142s, data_time: 0.063s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 6.320e-03, size: 448, ETA: 2:03:48
2025-09-01 08:11:45.829 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:11:45.882 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch175
2025-09-01 08:11:48.635 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 175/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.055s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 6.312e-03, size: 384, ETA: 2:03:45
2025-09-01 08:11:51.500 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 175/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 6.306e-03, size: 352, ETA: 2:03:42
2025-09-01 08:11:54.290 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 175/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.139s, data_time: 0.054s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.300e-03, size: 448, ETA: 2:03:40
2025-09-01 08:11:57.014 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 175/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.057s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.295e-03, size: 480, ETA: 2:03:37
2025-09-01 08:11:59.794 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 175/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.133s, data_time: 0.052s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 6.289e-03, size: 544, ETA: 2:03:34
2025-09-01 08:12:02.682 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 175/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 6.283e-03, size: 448, ETA: 2:03:32
2025-09-01 08:12:03.882 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:12:09.840 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:12:14.258 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:12:17.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5320
2025-09-01 08:12:18.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4659
2025-09-01 08:12:18.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2758
2025-09-01 08:12:18.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4246
2025-09-01 08:12:18.414 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:12:18.414 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:12:18.414 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.532
2025-09-01 08:12:18.414 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.466
2025-09-01 08:12:18.414 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.276
2025-09-01 08:12:18.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.425
2025-09-01 08:12:18.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:12:18.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:12:18.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:12:18.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:12:18.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:12:18.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:12:18.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:12:18.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:12:18.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:12:22.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:12:26.267 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:12:30.122 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:12:33.985 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:12:37.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:12:41.700 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:12:45.496 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:12:49.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:12:53.668 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:12:53.668 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-09-01 08:12:53.668 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.42
2025-09-01 08:12:53.668 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:12:53.696 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.40 ms, Average NMS time: 0.96 ms, Average inference time: 2.36 ms

2025-09-01 08:12:53.697 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:12:53.727 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:12:53.759 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch176
2025-09-01 08:12:56.305 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 176/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.126s, data_time: 0.049s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 6.275e-03, size: 352, ETA: 2:03:27
2025-09-01 08:12:59.209 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 176/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.144s, data_time: 0.065s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.269e-03, size: 512, ETA: 2:03:25
2025-09-01 08:13:02.079 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 176/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.143s, data_time: 0.062s, total_loss: 5.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 6.263e-03, size: 544, ETA: 2:03:23
2025-09-01 08:13:04.928 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 176/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.142s, data_time: 0.064s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.258e-03, size: 576, ETA: 2:03:20
2025-09-01 08:13:07.718 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 176/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 6.252e-03, size: 320, ETA: 2:03:18
2025-09-01 08:13:10.524 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 176/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.132s, data_time: 0.039s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 6.246e-03, size: 352, ETA: 2:03:15
2025-09-01 08:13:11.782 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:13:11.876 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch177
2025-09-01 08:13:14.797 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 177/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.238e-03, size: 416, ETA: 2:03:10
2025-09-01 08:13:17.520 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 177/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.132s, data_time: 0.011s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.232e-03, size: 416, ETA: 2:03:08
2025-09-01 08:13:20.405 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 177/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.130s, data_time: 0.040s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.227e-03, size: 512, ETA: 2:03:05
2025-09-01 08:13:23.242 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 177/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 7.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 6.221e-03, size: 256, ETA: 2:03:02
2025-09-01 08:13:26.209 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 177/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.147s, data_time: 0.066s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 6.215e-03, size: 448, ETA: 2:03:00
2025-09-01 08:13:29.005 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 177/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.137s, data_time: 0.042s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 6.209e-03, size: 512, ETA: 2:02:57
2025-09-01 08:13:30.233 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:13:30.296 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch178
2025-09-01 08:13:33.016 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 178/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.133s, data_time: 0.044s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 6.201e-03, size: 352, ETA: 2:02:53
2025-09-01 08:13:35.828 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 178/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.134s, data_time: 0.032s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.195e-03, size: 288, ETA: 2:02:50
2025-09-01 08:13:38.665 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 178/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.132s, data_time: 0.025s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.190e-03, size: 480, ETA: 2:02:48
2025-09-01 08:13:41.534 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 178/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, 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: 6.184e-03, size: 512, ETA: 2:02:45
2025-09-01 08:13:44.477 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 178/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, 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: 6.178e-03, size: 512, ETA: 2:02:42
2025-09-01 08:13:47.335 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 178/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, 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: 6.172e-03, size: 320, ETA: 2:02:40
2025-09-01 08:13:48.600 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:13:48.636 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch179
2025-09-01 08:13:51.455 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 179/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.011s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 6.164e-03, size: 320, ETA: 2:02:36
2025-09-01 08:13:54.271 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 179/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.136s, data_time: 0.010s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 6.158e-03, size: 512, ETA: 2:02:33
2025-09-01 08:13:57.201 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 179/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.143s, data_time: 0.011s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 6.152e-03, size: 480, ETA: 2:02:31
2025-09-01 08:14:00.149 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 179/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.144s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 6.147e-03, size: 352, ETA: 2:02:29
2025-09-01 08:14:02.948 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 179/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.136s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 6.141e-03, size: 576, ETA: 2:02:26
2025-09-01 08:14:05.806 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 179/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.140s, 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: 6.135e-03, size: 544, ETA: 2:02:23
2025-09-01 08:14:07.051 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:14:07.175 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch180
2025-09-01 08:14:09.916 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 180/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.134s, data_time: 0.004s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 6.127e-03, size: 512, ETA: 2:02:19
2025-09-01 08:14:12.642 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 180/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.130s, 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: 6.121e-03, size: 544, ETA: 2:02:17
2025-09-01 08:14:15.534 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 180/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.138s, data_time: 0.030s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 6.115e-03, size: 480, ETA: 2:02:14
2025-09-01 08:14:18.386 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 180/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.134s, data_time: 0.014s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.9, lr: 6.110e-03, size: 320, ETA: 2:02:11
2025-09-01 08:14:21.171 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 180/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.104e-03, size: 416, ETA: 2:02:08
2025-09-01 08:14:24.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 180/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.134s, 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: 6.098e-03, size: 256, ETA: 2:02:05
2025-09-01 08:14:25.338 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:14:31.404 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:14:41.543 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:14:48.105 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.4412
2025-09-01 08:14:49.478 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4663
2025-09-01 08:14:49.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2917
2025-09-01 08:14:49.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.3997
2025-09-01 08:14:49.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:14:49.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:14:49.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.441
2025-09-01 08:14:49.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.466
2025-09-01 08:14:49.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.292
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.400
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:14:49.553 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:14:57.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:15:05.470 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:15:13.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:15:21.406 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:15:29.301 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:15:37.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:15:45.318 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:15:53.613 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:16:01.557 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:16:01.558 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-09-01 08:16:01.558 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.40
2025-09-01 08:16:01.558 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:16:01.584 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 1.02 ms, Average inference time: 2.41 ms

2025-09-01 08:16:01.585 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:16:01.614 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:16:01.647 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch181
2025-09-01 08:16:04.126 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 181/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.121s, data_time: 0.042s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 6.090e-03, size: 576, ETA: 2:02:01
2025-09-01 08:16:07.002 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 181/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.141s, data_time: 0.065s, total_loss: 8.3, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.9, lr: 6.084e-03, size: 320, ETA: 2:01:58
2025-09-01 08:16:09.806 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 181/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.078e-03, size: 576, ETA: 2:01:56
2025-09-01 08:16:12.568 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 181/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.072e-03, size: 288, ETA: 2:01:53
2025-09-01 08:16:15.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 181/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.033s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.067e-03, size: 256, ETA: 2:01:50
2025-09-01 08:16:18.229 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 181/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.141s, 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: 6.061e-03, size: 320, ETA: 2:01:48
2025-09-01 08:16:19.405 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:16:19.617 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch182
2025-09-01 08:16:22.368 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 182/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.130s, data_time: 0.036s, total_loss: 7.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 6.053e-03, size: 576, ETA: 2:01:44
2025-09-01 08:16:25.184 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 182/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.047e-03, size: 448, ETA: 2:01:41
2025-09-01 08:16:28.059 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 182/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.136s, data_time: 0.033s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 6.041e-03, size: 448, ETA: 2:01:38
2025-09-01 08:16:30.941 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 182/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.134s, data_time: 0.013s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.035e-03, size: 544, ETA: 2:01:36
2025-09-01 08:16:33.802 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 182/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.020s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.029e-03, size: 512, ETA: 2:01:33
2025-09-01 08:16:36.695 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 182/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.010s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.024e-03, size: 512, ETA: 2:01:30
2025-09-01 08:16:37.930 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:16:37.967 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch183
2025-09-01 08:16:40.824 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 183/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.142s, 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: 6.015e-03, size: 384, ETA: 2:01:26
2025-09-01 08:16:43.637 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 183/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.009e-03, size: 544, ETA: 2:01:24
2025-09-01 08:16:46.521 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 183/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.139s, data_time: 0.024s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 6.004e-03, size: 448, ETA: 2:01:21
2025-09-01 08:16:49.338 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 183/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.139s, data_time: 0.041s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.998e-03, size: 544, ETA: 2:01:19
2025-09-01 08:16:52.178 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 183/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.046s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.992e-03, size: 384, ETA: 2:01:16
2025-09-01 08:16:55.088 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 183/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.125s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.986e-03, size: 512, ETA: 2:01:13
2025-09-01 08:16:56.363 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:16:56.399 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch184
2025-09-01 08:16:59.061 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 184/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.121s, data_time: 0.032s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 5.978e-03, size: 352, ETA: 2:01:08
2025-09-01 08:17:01.947 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 184/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.054s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.972e-03, size: 352, ETA: 2:01:06
2025-09-01 08:17:04.716 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 184/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.966e-03, size: 448, ETA: 2:01:03
2025-09-01 08:17:07.511 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 184/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.132s, data_time: 0.048s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.961e-03, size: 480, ETA: 2:01:00
2025-09-01 08:17:10.379 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 184/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.051s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.955e-03, size: 288, ETA: 2:00:58
2025-09-01 08:17:13.180 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 184/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.050s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 5.949e-03, size: 320, ETA: 2:00:55
2025-09-01 08:17:14.441 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:17:14.477 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch185
2025-09-01 08:17:17.222 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 185/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.9, lr: 5.941e-03, size: 416, ETA: 2:00:51
2025-09-01 08:17:20.109 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 185/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.139s, data_time: 0.056s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.935e-03, size: 384, ETA: 2:00:49
2025-09-01 08:17:22.987 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 185/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.143s, data_time: 0.064s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 5.929e-03, size: 320, ETA: 2:00:46
2025-09-01 08:17:25.789 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 185/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.139s, data_time: 0.054s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.923e-03, size: 448, ETA: 2:00:44
2025-09-01 08:17:28.566 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 185/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, data_time: 0.050s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.917e-03, size: 480, ETA: 2:00:41
2025-09-01 08:17:31.485 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 185/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.145s, data_time: 0.064s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.912e-03, size: 352, ETA: 2:00:39
2025-09-01 08:17:32.816 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:17:38.765 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:17:43.147 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:17:45.772 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5191
2025-09-01 08:17:46.245 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4788
2025-09-01 08:17:46.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2925
2025-09-01 08:17:46.389 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4301
2025-09-01 08:17:46.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:17:46.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:17:46.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.519
2025-09-01 08:17:46.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.479
2025-09-01 08:17:46.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.292
2025-09-01 08:17:46.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.430
2025-09-01 08:17:46.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:17:46.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:17:46.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:17:46.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:17:46.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:17:46.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:17:46.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:17:46.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:17:46.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:17:49.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:17:52.661 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:17:55.783 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:17:58.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:18:01.994 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:18:05.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:18:08.236 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:18:11.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:18:14.593 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:18:14.594 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-09-01 08:18:14.594 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-09-01 08:18:14.594 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:18:14.619 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.98 ms, Average inference time: 2.35 ms

2025-09-01 08:18:14.625 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:18:14.653 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:18:14.686 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch186
2025-09-01 08:18:17.156 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 186/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.122s, data_time: 0.043s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.903e-03, size: 256, ETA: 2:00:35
2025-09-01 08:18:19.987 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 186/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.133s, data_time: 0.030s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.897e-03, size: 256, ETA: 2:00:32
2025-09-01 08:18:22.850 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 186/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.128s, data_time: 0.027s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.892e-03, size: 448, ETA: 2:00:29
2025-09-01 08:18:25.658 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 186/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.130s, data_time: 0.024s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.886e-03, size: 544, ETA: 2:00:26
2025-09-01 08:18:28.446 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 186/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.880e-03, size: 512, ETA: 2:00:23
2025-09-01 08:18:31.396 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 186/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.139s, data_time: 0.042s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.874e-03, size: 480, ETA: 2:00:21
2025-09-01 08:18:32.458 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:18:32.570 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch187
2025-09-01 08:18:35.407 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 187/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.866e-03, size: 256, ETA: 2:00:16
2025-09-01 08:18:38.282 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 187/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.141s, data_time: 0.051s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 5.860e-03, size: 512, ETA: 2:00:14
2025-09-01 08:18:41.229 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 187/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.142s, data_time: 0.034s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 5.854e-03, size: 320, ETA: 2:00:12
2025-09-01 08:18:44.062 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 187/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.139s, data_time: 0.015s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.848e-03, size: 512, ETA: 2:00:09
2025-09-01 08:18:46.901 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 187/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 5.843e-03, size: 288, ETA: 2:00:06
2025-09-01 08:18:49.734 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 187/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.139s, data_time: 0.014s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.837e-03, size: 480, ETA: 2:00:04
2025-09-01 08:18:50.942 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:18:51.061 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch188
2025-09-01 08:18:53.846 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 188/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.131s, data_time: 0.008s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.828e-03, size: 352, ETA: 2:00:00
2025-09-01 08:18:56.804 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 188/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.001s, total_loss: 7.7, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 5.822e-03, size: 320, ETA: 1:59:57
2025-09-01 08:18:59.789 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 188/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.143s, data_time: 0.004s, total_loss: 4.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.6, cls_loss: 0.7, lr: 5.817e-03, size: 384, ETA: 1:59:55
2025-09-01 08:19:02.488 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 188/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.131s, data_time: 0.019s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.811e-03, size: 544, ETA: 1:59:52
2025-09-01 08:19:05.193 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 188/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.132s, data_time: 0.024s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 5.805e-03, size: 448, ETA: 1:59:49
2025-09-01 08:19:08.079 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 188/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.127s, data_time: 0.019s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.799e-03, size: 544, ETA: 1:59:46
2025-09-01 08:19:09.340 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:19:09.393 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch189
2025-09-01 08:19:12.309 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 189/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.142s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.791e-03, size: 576, ETA: 1:59:42
2025-09-01 08:19:15.059 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 189/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.004s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.785e-03, size: 576, ETA: 1:59:40
2025-09-01 08:19:17.903 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 189/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.137s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.779e-03, size: 256, ETA: 1:59:37
2025-09-01 08:19:20.820 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 189/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.125s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.773e-03, size: 544, ETA: 1:59:34
2025-09-01 08:19:23.602 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 189/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.132s, 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: 5.767e-03, size: 544, ETA: 1:59:31
2025-09-01 08:19:26.425 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 189/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.131s, data_time: 0.009s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 5.762e-03, size: 480, ETA: 1:59:28
2025-09-01 08:19:27.651 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:19:27.752 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch190
2025-09-01 08:19:30.621 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 190/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.130s, data_time: 0.011s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.753e-03, size: 576, ETA: 1:59:24
2025-09-01 08:19:33.491 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 190/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 5.747e-03, size: 384, ETA: 1:59:21
2025-09-01 08:19:36.415 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 190/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.742e-03, size: 576, ETA: 1:59:18
2025-09-01 08:19:39.192 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 190/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.125s, data_time: 0.004s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.736e-03, size: 512, ETA: 1:59:15
2025-09-01 08:19:42.069 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 190/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.132s, 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: 5.730e-03, size: 288, ETA: 1:59:12
2025-09-01 08:19:44.946 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 190/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.135s, data_time: 0.008s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.724e-03, size: 576, ETA: 1:59:09
2025-09-01 08:19:46.229 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:19:51.968 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:19:53.259 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:19:54.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5452
2025-09-01 08:19:54.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4920
2025-09-01 08:19:54.288 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2495
2025-09-01 08:19:54.289 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4289
2025-09-01 08:19:54.289 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:19:54.290 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:19:54.290 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.545
2025-09-01 08:19:54.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.492
2025-09-01 08:19:54.291 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.250
2025-09-01 08:19:54.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.429
2025-09-01 08:19:54.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:19:54.292 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:19:54.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:19:54.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:19:54.294 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:19:54.294 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:19:54.294 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:19:54.295 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:19:54.295 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:19:55.394 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:19:56.397 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:19:57.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:19:58.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:19:59.418 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:20:00.377 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:20:01.496 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:20:02.471 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:20:03.515 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:20:03.515 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.20
2025-09-01 08:20:03.516 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-09-01 08:20:03.516 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:20:03.523 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.92 ms, Average inference time: 2.30 ms

2025-09-01 08:20:03.525 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:20:03.550 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:20:03.582 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch191
2025-09-01 08:20:06.050 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 191/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.120s, data_time: 0.035s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.716e-03, size: 256, ETA: 1:59:05
2025-09-01 08:20:08.958 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 191/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.143s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 5.710e-03, size: 384, ETA: 1:59:02
2025-09-01 08:20:11.735 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 191/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.704e-03, size: 320, ETA: 1:59:00
2025-09-01 08:20:14.511 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 191/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.134s, data_time: 0.013s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.698e-03, size: 480, ETA: 1:58:57
2025-09-01 08:20:17.446 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 191/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.144s, data_time: 0.013s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 5.692e-03, size: 416, ETA: 1:58:55
2025-09-01 08:20:20.231 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 191/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, data_time: 0.011s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 5.686e-03, size: 512, ETA: 1:58:52
2025-09-01 08:20:21.486 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:20:21.565 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch192
2025-09-01 08:20:24.378 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 192/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.033s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.678e-03, size: 256, ETA: 1:58:48
2025-09-01 08:20:27.309 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 192/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.3Gb, iter_time: 0.136s, data_time: 0.025s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.672e-03, size: 576, ETA: 1:58:45
2025-09-01 08:20:30.137 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 192/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.666e-03, size: 256, ETA: 1:58:43
2025-09-01 08:20:32.907 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 192/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.132s, data_time: 0.022s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.661e-03, size: 480, ETA: 1:58:40
2025-09-01 08:20:35.755 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 192/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 7.1, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.655e-03, size: 416, ETA: 1:58:37
2025-09-01 08:20:38.566 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 192/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.139s, data_time: 0.064s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.649e-03, size: 544, ETA: 1:58:35
2025-09-01 08:20:39.807 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:20:39.852 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch193
2025-09-01 08:20:42.665 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 193/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.138s, data_time: 0.064s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.640e-03, size: 256, ETA: 1:58:31
2025-09-01 08:20:45.480 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 193/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.635e-03, size: 416, ETA: 1:58:28
2025-09-01 08:20:48.279 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 193/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.132s, data_time: 0.031s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.629e-03, size: 576, ETA: 1:58:25
2025-09-01 08:20:51.055 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 193/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, data_time: 0.033s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 5.623e-03, size: 576, ETA: 1:58:23
2025-09-01 08:20:53.892 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 193/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.617e-03, size: 320, ETA: 1:58:20
2025-09-01 08:20:56.713 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 193/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.130s, data_time: 0.053s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 5.611e-03, size: 320, ETA: 1:58:17
2025-09-01 08:20:57.995 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:20:58.035 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch194
2025-09-01 08:21:00.866 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 194/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.129s, data_time: 0.042s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.603e-03, size: 544, ETA: 1:58:13
2025-09-01 08:21:03.688 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 194/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.127s, data_time: 0.031s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 5.597e-03, size: 416, ETA: 1:58:10
2025-09-01 08:21:06.522 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 194/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.129s, data_time: 0.011s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 5.591e-03, size: 288, ETA: 1:58:07
2025-09-01 08:21:09.311 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 194/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.129s, data_time: 0.011s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.585e-03, size: 320, ETA: 1:58:04
2025-09-01 08:21:12.050 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 194/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.126s, data_time: 0.042s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.579e-03, size: 480, ETA: 1:58:01
2025-09-01 08:21:14.997 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 194/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.574e-03, size: 576, ETA: 1:57:58
2025-09-01 08:21:16.257 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:21:16.296 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch195
2025-09-01 08:21:19.095 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 195/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, data_time: 0.011s, total_loss: 7.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 5.565e-03, size: 512, ETA: 1:57:54
2025-09-01 08:21:21.887 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 195/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.134s, data_time: 0.051s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.559e-03, size: 320, ETA: 1:57:52
2025-09-01 08:21:24.683 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 195/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.059s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.553e-03, size: 416, ETA: 1:57:49
2025-09-01 08:21:27.435 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 195/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.131s, data_time: 0.051s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.2, lr: 5.547e-03, size: 288, ETA: 1:57:46
2025-09-01 08:21:30.208 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 195/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.135s, data_time: 0.055s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 5.542e-03, size: 352, ETA: 1:57:43
2025-09-01 08:21:33.103 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 195/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.142s, data_time: 0.059s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.536e-03, size: 480, ETA: 1:57:41
2025-09-01 08:21:34.363 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:21:40.244 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:21:44.190 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:21:47.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5637
2025-09-01 08:21:47.656 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5030
2025-09-01 08:21:47.728 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3258
2025-09-01 08:21:47.729 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4642
2025-09-01 08:21:47.729 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.503
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.326
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.464
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:21:47.730 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:21:47.731 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:21:47.731 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:21:51.303 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:21:55.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:21:58.590 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:22:02.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:22:05.703 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:22:09.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:22:12.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:22:16.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:22:20.141 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:22:20.141 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-09-01 08:22:20.142 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-09-01 08:22:20.142 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:22:20.168 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.96 ms, Average inference time: 2.32 ms

2025-09-01 08:22:20.169 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:22:20.192 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:22:20.229 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch196
2025-09-01 08:22:22.660 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 196/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.116s, data_time: 0.039s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.527e-03, size: 544, ETA: 1:57:36
2025-09-01 08:22:25.411 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 196/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.134s, data_time: 0.057s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 5.521e-03, size: 352, ETA: 1:57:34
2025-09-01 08:22:28.227 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 196/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.140s, data_time: 0.059s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.516e-03, size: 576, ETA: 1:57:31
2025-09-01 08:22:31.064 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 196/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.510e-03, size: 448, ETA: 1:57:29
2025-09-01 08:22:34.035 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 196/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.148s, data_time: 0.066s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.504e-03, size: 480, ETA: 1:57:26
2025-09-01 08:22:36.812 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 196/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.498e-03, size: 512, ETA: 1:57:24
2025-09-01 08:22:38.120 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:22:38.164 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch197
2025-09-01 08:22:40.955 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 197/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.490e-03, size: 256, ETA: 1:57:20
2025-09-01 08:22:43.837 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 197/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.143s, data_time: 0.066s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 5.484e-03, size: 544, ETA: 1:57:18
2025-09-01 08:22:46.581 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 197/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.126s, data_time: 0.039s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.478e-03, size: 384, ETA: 1:57:15
2025-09-01 08:22:49.295 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 197/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.122s, data_time: 0.006s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.472e-03, size: 576, ETA: 1:57:12
2025-09-01 08:22:52.153 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 197/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.011s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 5.466e-03, size: 256, ETA: 1:57:09
2025-09-01 08:22:54.941 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 197/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.126s, data_time: 0.045s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.460e-03, size: 320, ETA: 1:57:06
2025-09-01 08:22:56.155 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:22:56.199 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch198
2025-09-01 08:22:59.034 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 198/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.141s, data_time: 0.064s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 5.452e-03, size: 448, ETA: 1:57:02
2025-09-01 08:23:01.912 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 198/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.143s, data_time: 0.057s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.446e-03, size: 544, ETA: 1:57:00
2025-09-01 08:23:04.821 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 198/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.144s, data_time: 0.065s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.1, lr: 5.440e-03, size: 384, ETA: 1:56:57
2025-09-01 08:23:07.691 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 198/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.139s, data_time: 0.063s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.434e-03, size: 320, ETA: 1:56:55
2025-09-01 08:23:10.607 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 198/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.143s, data_time: 0.061s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 5.428e-03, size: 448, ETA: 1:56:52
2025-09-01 08:23:13.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 198/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 5.423e-03, size: 544, ETA: 1:56:50
2025-09-01 08:23:14.704 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:23:14.742 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch199
2025-09-01 08:23:17.615 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 199/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.141s, data_time: 0.063s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 5.414e-03, size: 448, ETA: 1:56:46
2025-09-01 08:23:20.302 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 199/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.132s, data_time: 0.052s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.408e-03, size: 416, ETA: 1:56:43
2025-09-01 08:23:23.130 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 199/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, data_time: 0.028s, total_loss: 5.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.402e-03, size: 544, ETA: 1:56:41
2025-09-01 08:23:26.076 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 199/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.145s, 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: 5.397e-03, size: 256, ETA: 1:56:38
2025-09-01 08:23:28.716 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 199/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.127s, 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: 5.391e-03, size: 256, ETA: 1:56:35
2025-09-01 08:23:31.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 199/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 5.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.385e-03, size: 480, ETA: 1:56:33
2025-09-01 08:23:32.813 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:23:32.983 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch200
2025-09-01 08:23:35.783 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 200/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.376e-03, size: 448, ETA: 1:56:28
2025-09-01 08:23:38.559 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 200/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.370e-03, size: 448, ETA: 1:56:26
2025-09-01 08:23:41.381 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 200/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, 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: 5.365e-03, size: 416, ETA: 1:56:23
2025-09-01 08:23:44.277 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 200/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, 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: 5.359e-03, size: 384, ETA: 1:56:20
2025-09-01 08:23:47.024 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 200/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.130s, data_time: 0.009s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 5.353e-03, size: 448, ETA: 1:56:17
2025-09-01 08:23:49.858 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 200/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.128s, 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: 5.347e-03, size: 544, ETA: 1:56:14
2025-09-01 08:23:51.180 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:23:57.122 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:23:58.138 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:23:58.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5207
2025-09-01 08:23:58.896 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5054
2025-09-01 08:23:58.980 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2815
2025-09-01 08:23:58.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4358
2025-09-01 08:23:58.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:23:58.981 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:23:58.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.521
2025-09-01 08:23:58.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.505
2025-09-01 08:23:58.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.281
2025-09-01 08:23:58.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.436
2025-09-01 08:23:58.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:23:58.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:23:58.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:23:58.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:23:58.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:23:58.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:23:58.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:23:58.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:23:58.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:23:59.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:24:00.557 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:24:01.316 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:24:02.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:24:02.888 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:24:03.698 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:24:04.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:24:05.271 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:24:06.042 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:24:06.042 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-09-01 08:24:06.042 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-09-01 08:24:06.042 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:24:06.050 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.91 ms, Average inference time: 2.26 ms

2025-09-01 08:24:06.051 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:24:06.077 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:24:06.157 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch201
2025-09-01 08:24:08.616 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 201/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.122s, data_time: 0.042s, total_loss: 7.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 5.339e-03, size: 256, ETA: 1:56:10
2025-09-01 08:24:11.457 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 201/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.139s, data_time: 0.060s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.333e-03, size: 544, ETA: 1:56:07
2025-09-01 08:24:14.252 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 201/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, data_time: 0.042s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.327e-03, size: 288, ETA: 1:56:05
2025-09-01 08:24:17.091 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 201/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.138s, data_time: 0.055s, total_loss: 6.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.321e-03, size: 288, ETA: 1:56:02
2025-09-01 08:24:19.994 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 201/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.144s, data_time: 0.065s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 5.315e-03, size: 448, ETA: 1:56:00
2025-09-01 08:24:22.800 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 201/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.309e-03, size: 384, ETA: 1:55:57
2025-09-01 08:24:24.032 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:24:24.077 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch202
2025-09-01 08:24:26.760 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 202/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.133s, data_time: 0.052s, total_loss: 8.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 1.0, lr: 5.301e-03, size: 416, ETA: 1:55:53
2025-09-01 08:24:29.680 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 202/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.295e-03, size: 512, ETA: 1:55:51
2025-09-01 08:24:32.541 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 202/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 6.8, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.6, lr: 5.289e-03, size: 320, ETA: 1:55:48
2025-09-01 08:24:35.445 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 202/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.144s, data_time: 0.065s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.283e-03, size: 448, ETA: 1:55:46
2025-09-01 08:24:38.232 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 202/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.277e-03, size: 384, ETA: 1:55:43
2025-09-01 08:24:41.322 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 202/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.143s, data_time: 0.019s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.272e-03, size: 416, ETA: 1:55:41
2025-09-01 08:24:42.621 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:24:42.658 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch203
2025-09-01 08:24:45.409 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 203/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.263e-03, size: 480, ETA: 1:55:37
2025-09-01 08:24:48.241 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 203/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.023s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 5.257e-03, size: 288, ETA: 1:55:34
2025-09-01 08:24:51.182 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 203/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.144s, data_time: 0.003s, total_loss: 8.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 5.251e-03, size: 544, ETA: 1:55:32
2025-09-01 08:24:54.028 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 203/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.140s, data_time: 0.008s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.245e-03, size: 480, ETA: 1:55:29
2025-09-01 08:24:56.967 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 203/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.144s, 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: 5.240e-03, size: 512, ETA: 1:55:27
2025-09-01 08:24:59.792 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 203/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.138s, data_time: 0.014s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.234e-03, size: 352, ETA: 1:55:24
2025-09-01 08:25:01.089 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:25:01.227 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch204
2025-09-01 08:25:04.097 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 204/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.133s, data_time: 0.007s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.225e-03, size: 544, ETA: 1:55:21
2025-09-01 08:25:07.041 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 204/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.021s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.1, lr: 5.219e-03, size: 352, ETA: 1:55:18
2025-09-01 08:25:09.913 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 204/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.214e-03, size: 544, ETA: 1:55:15
2025-09-01 08:25:12.723 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 204/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.134s, 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: 5.208e-03, size: 576, ETA: 1:55:13
2025-09-01 08:25:15.613 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 204/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, 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: 5.202e-03, size: 448, ETA: 1:55:10
2025-09-01 08:25:18.439 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 204/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, 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: 5.196e-03, size: 416, ETA: 1:55:07
2025-09-01 08:25:19.692 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:25:19.756 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch205
2025-09-01 08:25:22.493 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 205/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.187e-03, size: 384, ETA: 1:55:03
2025-09-01 08:25:25.421 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 205/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.142s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 1.0, lr: 5.182e-03, size: 352, ETA: 1:55:01
2025-09-01 08:25:28.165 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 205/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.130s, data_time: 0.036s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 5.176e-03, size: 544, ETA: 1:54:58
2025-09-01 08:25:30.975 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 205/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.135s, data_time: 0.032s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.170e-03, size: 480, ETA: 1:54:55
2025-09-01 08:25:33.806 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 205/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.138s, data_time: 0.008s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.164e-03, size: 544, ETA: 1:54:52
2025-09-01 08:25:36.649 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 205/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.135s, data_time: 0.023s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.158e-03, size: 448, ETA: 1:54:50
2025-09-01 08:25:37.921 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:25:44.093 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:25:45.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:25:46.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5698
2025-09-01 08:25:46.914 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5280
2025-09-01 08:25:47.019 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3267
2025-09-01 08:25:47.020 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4749
2025-09-01 08:25:47.020 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:25:47.020 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:25:47.020 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.570
2025-09-01 08:25:47.020 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.528
2025-09-01 08:25:47.020 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.327
2025-09-01 08:25:47.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.475
2025-09-01 08:25:47.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:25:47.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:25:47.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:25:47.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:25:47.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:25:47.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:25:47.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:25:47.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:25:47.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:25:48.310 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:25:49.576 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:25:50.886 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:25:52.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:25:53.525 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:25:54.810 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:25:56.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:25:57.343 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:25:58.666 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:25:58.666 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-09-01 08:25:58.666 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-09-01 08:25:58.666 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:25:58.680 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.95 ms, Average inference time: 2.34 ms

2025-09-01 08:25:58.681 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:25:58.704 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:25:58.784 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch206
2025-09-01 08:26:01.168 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 206/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.117s, data_time: 0.035s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.150e-03, size: 544, ETA: 1:54:45
2025-09-01 08:26:03.943 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 206/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.053s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.144e-03, size: 512, ETA: 1:54:42
2025-09-01 08:26:06.726 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 206/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 5.138e-03, size: 320, ETA: 1:54:40
2025-09-01 08:26:09.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 206/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.138s, data_time: 0.006s, total_loss: 7.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.2, lr: 5.132e-03, size: 256, ETA: 1:54:37
2025-09-01 08:26:12.527 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 206/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.135s, data_time: 0.003s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 5.126e-03, size: 448, ETA: 1:54:34
2025-09-01 08:26:15.368 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 206/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.120e-03, size: 288, ETA: 1:54:32
2025-09-01 08:26:16.588 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:26:16.636 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch207
2025-09-01 08:26:19.588 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 207/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.145s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 5.112e-03, size: 320, ETA: 1:54:28
2025-09-01 08:26:22.422 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 207/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.138s, 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: 5.106e-03, size: 480, ETA: 1:54:26
2025-09-01 08:26:25.218 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 207/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.135s, data_time: 0.014s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.100e-03, size: 480, ETA: 1:54:23
2025-09-01 08:26:28.172 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 207/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.145s, data_time: 0.005s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.094e-03, size: 384, ETA: 1:54:21
2025-09-01 08:26:31.058 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 207/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.142s, data_time: 0.005s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.2, lr: 5.089e-03, size: 576, ETA: 1:54:18
2025-09-01 08:26:33.864 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 207/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.007s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.083e-03, size: 320, ETA: 1:54:16
2025-09-01 08:26:35.101 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:26:35.215 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch208
2025-09-01 08:26:37.997 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 208/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 5.074e-03, size: 256, ETA: 1:54:12
2025-09-01 08:26:40.824 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 208/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.131s, data_time: 0.016s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.068e-03, size: 320, ETA: 1:54:09
2025-09-01 08:26:43.738 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 208/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.145s, data_time: 0.063s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.062e-03, size: 416, ETA: 1:54:06
2025-09-01 08:26:46.580 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 208/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.3, lr: 5.057e-03, size: 480, ETA: 1:54:04
2025-09-01 08:26:49.380 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 208/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.134s, data_time: 0.051s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.051e-03, size: 448, ETA: 1:54:01
2025-09-01 08:26:52.168 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 208/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.131s, data_time: 0.007s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.7, lr: 5.045e-03, size: 256, ETA: 1:53:58
2025-09-01 08:26:53.466 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:26:53.508 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch209
2025-09-01 08:26:56.340 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 209/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.132s, data_time: 0.008s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.036e-03, size: 448, ETA: 1:53:54
2025-09-01 08:26:59.095 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 209/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.123s, data_time: 0.005s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 5.031e-03, size: 576, ETA: 1:53:51
2025-09-01 08:27:02.004 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 209/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.125s, data_time: 0.026s, total_loss: 6.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.025e-03, size: 320, ETA: 1:53:48
2025-09-01 08:27:04.723 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 209/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.120s, data_time: 0.021s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 5.019e-03, size: 480, ETA: 1:53:45
2025-09-01 08:27:07.455 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 209/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.126s, data_time: 0.045s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.013e-03, size: 576, ETA: 1:53:42
2025-09-01 08:27:10.346 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 209/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.124s, data_time: 0.037s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.6, lr: 5.007e-03, size: 480, ETA: 1:53:39
2025-09-01 08:27:11.677 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:27:11.712 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch210
2025-09-01 08:27:14.482 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 210/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.128s, data_time: 0.042s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 4.999e-03, size: 352, ETA: 1:53:34
2025-09-01 08:27:17.279 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 210/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.126s, data_time: 0.044s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 4.993e-03, size: 256, ETA: 1:53:31
2025-09-01 08:27:20.291 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 210/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.030s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 4.987e-03, size: 256, ETA: 1:53:29
2025-09-01 08:27:23.019 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 210/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, data_time: 0.048s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.981e-03, size: 512, ETA: 1:53:26
2025-09-01 08:27:25.874 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 210/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.134s, data_time: 0.049s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 4.975e-03, size: 384, ETA: 1:53:23
2025-09-01 08:27:28.810 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 210/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.129s, data_time: 0.038s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.969e-03, size: 512, ETA: 1:53:20
2025-09-01 08:27:30.101 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:27:36.107 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:27:37.378 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:27:38.224 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5512
2025-09-01 08:27:38.344 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5224
2025-09-01 08:27:38.389 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3016
2025-09-01 08:27:38.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4584
2025-09-01 08:27:38.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:27:38.390 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.551
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.522
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.302
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.458
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:27:38.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:27:38.392 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:27:39.445 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:27:40.497 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:27:41.527 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:27:42.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:27:43.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:27:44.644 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:27:45.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:27:46.689 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:27:47.765 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:27:47.765 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-09-01 08:27:47.766 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-09-01 08:27:47.766 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:27:47.773 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.92 ms, Average inference time: 2.27 ms

2025-09-01 08:27:47.774 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:27:47.800 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:27:47.829 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch211
2025-09-01 08:27:50.330 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 211/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.122s, data_time: 0.047s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 4.961e-03, size: 320, ETA: 1:53:16
2025-09-01 08:27:53.169 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 211/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.059s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.955e-03, size: 288, ETA: 1:53:13
2025-09-01 08:27:55.996 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 211/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 4.949e-03, size: 480, ETA: 1:53:11
2025-09-01 08:27:58.816 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 211/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.139s, data_time: 0.042s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.943e-03, size: 384, ETA: 1:53:08
2025-09-01 08:28:01.611 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 211/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.138s, data_time: 0.056s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 4.938e-03, size: 256, ETA: 1:53:06
2025-09-01 08:28:04.412 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 211/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.139s, data_time: 0.060s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.932e-03, size: 576, ETA: 1:53:03
2025-09-01 08:28:05.700 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:28:05.737 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch212
2025-09-01 08:28:08.572 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 212/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.923e-03, size: 448, ETA: 1:52:59
2025-09-01 08:28:11.360 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 212/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.917e-03, size: 480, ETA: 1:52:57
2025-09-01 08:28:14.130 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 212/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 4.912e-03, size: 352, ETA: 1:52:54
2025-09-01 08:28:17.094 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 212/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.136s, data_time: 0.048s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.906e-03, size: 384, ETA: 1:52:51
2025-09-01 08:28:19.806 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 212/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.134s, data_time: 0.053s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.900e-03, size: 576, ETA: 1:52:49
2025-09-01 08:28:22.812 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 212/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.149s, data_time: 0.069s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.894e-03, size: 512, ETA: 1:52:46
2025-09-01 08:28:24.185 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:28:24.224 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch213
2025-09-01 08:28:27.091 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 213/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.143s, data_time: 0.060s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 4.886e-03, size: 448, ETA: 1:52:43
2025-09-01 08:28:29.844 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 213/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.054s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 4.880e-03, size: 416, ETA: 1:52:40
2025-09-01 08:28:32.573 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 213/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.132s, data_time: 0.043s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.1, lr: 4.874e-03, size: 256, ETA: 1:52:38
2025-09-01 08:28:35.600 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 213/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.138s, data_time: 0.037s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 4.868e-03, size: 352, ETA: 1:52:35
2025-09-01 08:28:38.446 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 213/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 4.862e-03, size: 448, ETA: 1:52:32
2025-09-01 08:28:41.324 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 213/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.125s, data_time: 0.009s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 4.856e-03, size: 480, ETA: 1:52:29
2025-09-01 08:28:42.503 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:28:42.557 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch214
2025-09-01 08:28:45.237 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 214/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.125s, data_time: 0.040s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 4.848e-03, size: 512, ETA: 1:52:24
2025-09-01 08:28:48.143 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 214/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 4.842e-03, size: 576, ETA: 1:52:22
2025-09-01 08:28:50.902 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 214/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.050s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.836e-03, size: 512, ETA: 1:52:19
2025-09-01 08:28:53.764 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 214/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 8.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.6, cls_loss: 0.8, lr: 4.830e-03, size: 352, ETA: 1:52:17
2025-09-01 08:28:56.743 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 214/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.139s, data_time: 0.048s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.825e-03, size: 576, ETA: 1:52:14
2025-09-01 08:28:59.470 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 214/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.128s, data_time: 0.033s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.819e-03, size: 352, ETA: 1:52:11
2025-09-01 08:29:00.713 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:29:00.757 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch215
2025-09-01 08:29:03.609 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 215/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.142s, data_time: 0.062s, total_loss: 5.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 4.810e-03, size: 480, ETA: 1:52:07
2025-09-01 08:29:06.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 215/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.064s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.804e-03, size: 576, ETA: 1:52:05
2025-09-01 08:29:09.274 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 215/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.135s, data_time: 0.036s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 4.799e-03, size: 352, ETA: 1:52:02
2025-09-01 08:29:12.168 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 215/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.144s, data_time: 0.066s, total_loss: 5.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 4.793e-03, size: 256, ETA: 1:52:00
2025-09-01 08:29:15.030 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 215/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 4.787e-03, size: 512, ETA: 1:51:57
2025-09-01 08:29:17.799 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 215/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.135s, data_time: 0.049s, 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: 352, ETA: 1:51:55
2025-09-01 08:29:18.945 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:29:24.715 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:29:27.011 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:29:28.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5723
2025-09-01 08:29:28.947 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4953
2025-09-01 08:29:29.000 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3398
2025-09-01 08:29:29.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4691
2025-09-01 08:29:29.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:29:29.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:29:29.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.572
2025-09-01 08:29:29.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.495
2025-09-01 08:29:29.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.340
2025-09-01 08:29:29.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.469
2025-09-01 08:29:29.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:29:29.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:29:29.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:29:29.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:29:29.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:29:29.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:29:29.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:29:29.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:29:29.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:29:31.057 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:29:32.989 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:29:34.955 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:29:36.907 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:29:38.881 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:29:41.006 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:29:43.024 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:29:45.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:29:46.978 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:29:46.978 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-09-01 08:29:46.978 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-09-01 08:29:46.978 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:29:47.003 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.94 ms, Average inference time: 2.32 ms

2025-09-01 08:29:47.005 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:29:47.026 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:29:47.058 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch216
2025-09-01 08:29:49.571 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 216/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.118s, data_time: 0.024s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 4.773e-03, size: 512, ETA: 1:51:50
2025-09-01 08:29:52.298 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 216/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.123s, data_time: 0.016s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 4.767e-03, size: 352, ETA: 1:51:47
2025-09-01 08:29:55.274 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 216/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.132s, data_time: 0.010s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 4.761e-03, size: 384, ETA: 1:51:44
2025-09-01 08:29:58.158 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 216/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.131s, data_time: 0.001s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.755e-03, size: 416, ETA: 1:51:41
2025-09-01 08:30:00.996 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 216/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.129s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 4.749e-03, size: 288, ETA: 1:51:38
2025-09-01 08:30:03.855 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 216/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.126s, 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: 4.744e-03, size: 448, ETA: 1:51:35
2025-09-01 08:30:05.004 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:30:05.166 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch217
2025-09-01 08:30:07.937 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 217/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.122s, data_time: 0.044s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.735e-03, size: 384, ETA: 1:51:30
2025-09-01 08:30:10.730 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 217/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.129s, data_time: 0.052s, total_loss: 7.7, iou_loss: 3.5, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 4.729e-03, size: 320, ETA: 1:51:27
2025-09-01 08:30:13.588 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 217/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.121s, data_time: 0.012s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 4.724e-03, size: 544, ETA: 1:51:24
2025-09-01 08:30:16.307 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 217/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.123s, data_time: 0.017s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.718e-03, size: 544, ETA: 1:51:21
2025-09-01 08:30:19.182 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 217/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.138s, data_time: 0.044s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 4.712e-03, size: 480, ETA: 1:51:19
2025-09-01 08:30:22.009 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 217/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.056s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.706e-03, size: 576, ETA: 1:51:16
2025-09-01 08:30:23.192 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:30:23.266 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch218
2025-09-01 08:30:26.115 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 218/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.128s, data_time: 0.016s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 4.698e-03, size: 288, ETA: 1:51:12
2025-09-01 08:30:29.041 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 218/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.137s, data_time: 0.018s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.692e-03, size: 384, ETA: 1:51:09
2025-09-01 08:30:31.907 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 218/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.686e-03, size: 480, ETA: 1:51:06
2025-09-01 08:30:34.842 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 218/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 4.680e-03, size: 544, ETA: 1:51:04
2025-09-01 08:30:37.709 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 218/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.133s, data_time: 0.006s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 4.674e-03, size: 288, ETA: 1:51:01
2025-09-01 08:30:40.575 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 218/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.4Gb, iter_time: 0.131s, data_time: 0.009s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 4.669e-03, size: 480, ETA: 1:50:58
2025-09-01 08:30:41.832 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:30:41.944 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch219
2025-09-01 08:30:44.674 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 219/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.124s, data_time: 0.005s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 4.660e-03, size: 256, ETA: 1:50:53
2025-09-01 08:30:47.616 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 219/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.131s, data_time: 0.005s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 4.654e-03, size: 448, ETA: 1:50:51
2025-09-01 08:30:50.384 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 219/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 4.648e-03, size: 288, ETA: 1:50:48
2025-09-01 08:30:53.214 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 219/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.127s, data_time: 0.021s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.643e-03, size: 384, ETA: 1:50:45
2025-09-01 08:30:56.079 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 219/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 4.637e-03, size: 352, ETA: 1:50:42
2025-09-01 08:30:58.974 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 219/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.2, lr: 4.631e-03, size: 320, ETA: 1:50:38
2025-09-01 08:31:00.310 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:31:00.352 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch220
2025-09-01 08:31:03.208 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 220/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.127s, data_time: 0.010s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 4.623e-03, size: 288, ETA: 1:50:34
2025-09-01 08:31:06.055 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 220/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.129s, data_time: 0.008s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 4.617e-03, size: 544, ETA: 1:50:31
2025-09-01 08:31:08.954 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 220/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.139s, data_time: 0.028s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.611e-03, size: 256, ETA: 1:50:29
2025-09-01 08:31:11.835 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 220/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.128s, data_time: 0.022s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.0, lr: 4.605e-03, size: 352, ETA: 1:50:26
2025-09-01 08:31:14.572 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 220/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.131s, data_time: 0.041s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.599e-03, size: 352, ETA: 1:50:23
2025-09-01 08:31:17.359 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 220/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.135s, data_time: 0.043s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 4.594e-03, size: 448, ETA: 1:50:20
2025-09-01 08:31:18.623 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:31:24.641 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:31:27.194 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:31:28.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5512
2025-09-01 08:31:29.225 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4912
2025-09-01 08:31:29.286 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2979
2025-09-01 08:31:29.286 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4467
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.551
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.491
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.298
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.447
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:31:29.287 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:31:29.288 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:31:29.288 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:31:29.288 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:31:29.288 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:31:29.288 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:31:31.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:31:33.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:31:34.997 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:31:36.869 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:31:38.857 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:31:40.767 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:31:42.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:31:44.466 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:31:46.430 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:31:46.430 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-09-01 08:31:46.430 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-09-01 08:31:46.431 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:31:46.456 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.97 ms, Average inference time: 2.35 ms

2025-09-01 08:31:46.457 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:31:46.504 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:31:46.634 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch221
2025-09-01 08:31:49.088 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 221/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.121s, data_time: 0.042s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.1, lr: 4.585e-03, size: 416, ETA: 1:50:16
2025-09-01 08:31:51.879 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 221/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.047s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 4.579e-03, size: 256, ETA: 1:50:13
2025-09-01 08:31:54.707 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 221/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.138s, data_time: 0.005s, total_loss: 7.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 4.574e-03, size: 480, ETA: 1:50:11
2025-09-01 08:31:57.554 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 221/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.011s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 4.568e-03, size: 416, ETA: 1:50:08
2025-09-01 08:32:00.374 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 221/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.130s, data_time: 0.009s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 4.562e-03, size: 256, ETA: 1:50:05
2025-09-01 08:32:03.216 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 221/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.129s, data_time: 0.027s, total_loss: 4.7, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 4.556e-03, size: 384, ETA: 1:50:02
2025-09-01 08:32:04.449 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:32:04.561 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch222
2025-09-01 08:32:07.424 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 222/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, 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: 4.548e-03, size: 384, ETA: 1:49:58
2025-09-01 08:32:10.251 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 222/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.030s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 4.542e-03, size: 544, ETA: 1:49:56
2025-09-01 08:32:13.161 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 222/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.133s, data_time: 0.052s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 4.536e-03, size: 576, ETA: 1:49:53
2025-09-01 08:32:15.890 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 222/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.131s, data_time: 0.017s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.530e-03, size: 384, ETA: 1:49:50
2025-09-01 08:32:18.653 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 222/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.132s, data_time: 0.050s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.3, lr: 4.525e-03, size: 256, ETA: 1:49:47
2025-09-01 08:32:21.506 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 222/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, data_time: 0.014s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.8, lr: 4.519e-03, size: 544, ETA: 1:49:45
2025-09-01 08:32:22.629 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:32:22.666 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch223
2025-09-01 08:32:25.477 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 223/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 4.510e-03, size: 384, ETA: 1:49:41
2025-09-01 08:32:28.330 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 223/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.142s, data_time: 0.058s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 4.505e-03, size: 512, ETA: 1:49:38
2025-09-01 08:32:31.209 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 223/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.142s, data_time: 0.058s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 4.499e-03, size: 448, ETA: 1:49:36
2025-09-01 08:32:34.129 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 223/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, data_time: 0.014s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 4.493e-03, size: 512, ETA: 1:49:33
2025-09-01 08:32:36.950 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 223/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.131s, data_time: 0.014s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 4.487e-03, size: 576, ETA: 1:49:30
2025-09-01 08:32:39.825 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 223/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.036s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 4.482e-03, size: 352, ETA: 1:49:28
2025-09-01 08:32:41.110 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:32:41.145 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch224
2025-09-01 08:32:43.975 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 224/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 4.473e-03, size: 448, ETA: 1:49:24
2025-09-01 08:32:46.792 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 224/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.135s, data_time: 0.060s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.467e-03, size: 416, ETA: 1:49:21
2025-09-01 08:32:49.757 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 224/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.462e-03, size: 256, ETA: 1:49:19
2025-09-01 08:32:52.536 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 224/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 4.456e-03, size: 448, ETA: 1:49:16
2025-09-01 08:32:55.289 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 224/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.126s, data_time: 0.015s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.450e-03, size: 512, ETA: 1:49:13
2025-09-01 08:32:58.200 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 224/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.145s, data_time: 0.062s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 4.444e-03, size: 512, ETA: 1:49:11
2025-09-01 08:32:59.541 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:32:59.579 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch225
2025-09-01 08:33:02.449 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 225/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.143s, data_time: 0.066s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.2, lr: 4.436e-03, size: 256, ETA: 1:49:07
2025-09-01 08:33:05.144 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 225/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.133s, data_time: 0.059s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.430e-03, size: 320, ETA: 1:49:04
2025-09-01 08:33:07.924 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 225/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.132s, data_time: 0.057s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 4.424e-03, size: 448, ETA: 1:49:02
2025-09-01 08:33:10.872 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 225/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.133s, data_time: 0.029s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.419e-03, size: 288, ETA: 1:48:59
2025-09-01 08:33:13.703 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 225/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.123s, data_time: 0.041s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 4.413e-03, size: 544, ETA: 1:48:56
2025-09-01 08:33:16.492 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 225/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.127s, data_time: 0.049s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 4.407e-03, size: 480, ETA: 1:48:53
2025-09-01 08:33:17.686 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:33:23.678 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:33:25.523 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:33:26.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5631
2025-09-01 08:33:26.994 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5377
2025-09-01 08:33:27.043 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2998
2025-09-01 08:33:27.044 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4669
2025-09-01 08:33:27.044 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:33:27.044 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:33:27.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.563
2025-09-01 08:33:27.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.538
2025-09-01 08:33:27.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.300
2025-09-01 08:33:27.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.467
2025-09-01 08:33:27.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:33:27.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:33:27.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:33:27.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:33:27.045 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:33:27.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:33:27.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:33:27.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:33:27.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:33:28.667 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:33:30.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:33:31.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:33:33.471 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:33:35.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:33:36.633 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:33:38.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:33:39.731 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:33:41.267 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:33:41.267 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-09-01 08:33:41.268 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-09-01 08:33:41.268 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:33:41.293 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.92 ms, Average inference time: 2.29 ms

2025-09-01 08:33:41.295 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:33:41.384 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:33:41.421 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch226
2025-09-01 08:33:43.802 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 226/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.109s, data_time: 0.032s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 4.399e-03, size: 352, ETA: 1:48:48
2025-09-01 08:33:46.614 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 226/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.133s, data_time: 0.042s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 4.393e-03, size: 384, ETA: 1:48:45
2025-09-01 08:33:49.405 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 226/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.132s, data_time: 0.030s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 4.387e-03, size: 352, ETA: 1:48:42
2025-09-01 08:33:52.290 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 226/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.126s, data_time: 0.015s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 4.381e-03, size: 448, ETA: 1:48:39
2025-09-01 08:33:55.121 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 226/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.132s, data_time: 0.004s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 4.376e-03, size: 448, ETA: 1:48:37
2025-09-01 08:33:58.076 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 226/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.005s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 4.370e-03, size: 416, ETA: 1:48:34
2025-09-01 08:33:59.280 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:33:59.316 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch227
2025-09-01 08:34:02.109 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 227/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.134s, data_time: 0.008s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.362e-03, size: 448, ETA: 1:48:30
2025-09-01 08:34:04.900 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 227/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.005s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 4.356e-03, size: 512, ETA: 1:48:27
2025-09-01 08:34:07.718 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 227/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.2, lr: 4.350e-03, size: 320, ETA: 1:48:25
2025-09-01 08:34:10.587 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 227/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.4, lr: 4.344e-03, size: 480, ETA: 1:48:22
2025-09-01 08:34:13.360 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 227/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.016s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 4.339e-03, size: 576, ETA: 1:48:20
2025-09-01 08:34:16.260 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 227/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.037s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 4.333e-03, size: 480, ETA: 1:48:17
2025-09-01 08:34:17.580 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:34:17.617 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch228
2025-09-01 08:34:20.432 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 228/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 4.325e-03, size: 512, ETA: 1:48:13
2025-09-01 08:34:23.350 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 228/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.138s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 4.319e-03, size: 384, ETA: 1:48:11
2025-09-01 08:34:26.057 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 228/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.134s, data_time: 0.049s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 4.313e-03, size: 416, ETA: 1:48:08
2025-09-01 08:34:28.804 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 228/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.136s, data_time: 0.059s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 4.307e-03, size: 416, ETA: 1:48:05
2025-09-01 08:34:31.621 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 228/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.138s, data_time: 0.061s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 4.302e-03, size: 576, ETA: 1:48:03
2025-09-01 08:34:34.654 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 228/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.151s, data_time: 0.070s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.4, lr: 4.296e-03, size: 352, ETA: 1:48:00
2025-09-01 08:34:35.931 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:34:35.968 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch229
2025-09-01 08:34:38.731 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 229/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 5.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.7, lr: 4.287e-03, size: 256, ETA: 1:47:57
2025-09-01 08:34:41.490 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 229/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 4.282e-03, size: 288, ETA: 1:47:54
2025-09-01 08:34:44.444 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 229/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.147s, data_time: 0.069s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 4.276e-03, size: 416, ETA: 1:47:52
2025-09-01 08:34:47.138 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 229/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.130s, data_time: 0.025s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 4.270e-03, size: 480, ETA: 1:47:49
2025-09-01 08:34:50.008 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 229/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.045s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.265e-03, size: 448, ETA: 1:47:46
2025-09-01 08:34:52.882 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 229/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.048s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.259e-03, size: 384, ETA: 1:47:44
2025-09-01 08:34:54.248 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:34:54.297 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch230
2025-09-01 08:34:57.192 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 230/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.144s, data_time: 0.062s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 4.251e-03, size: 512, ETA: 1:47:40
2025-09-01 08:35:00.132 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 230/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.145s, data_time: 0.063s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 4.245e-03, size: 384, ETA: 1:47:38
2025-09-01 08:35:02.995 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 230/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.142s, data_time: 0.057s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 4.239e-03, size: 480, ETA: 1:47:35
2025-09-01 08:35:05.714 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 230/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.129s, data_time: 0.037s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 4.233e-03, size: 416, ETA: 1:47:33
2025-09-01 08:35:08.581 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 230/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, data_time: 0.025s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.228e-03, size: 256, ETA: 1:47:30
2025-09-01 08:35:11.393 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 230/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.138s, data_time: 0.042s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.222e-03, size: 544, ETA: 1:47:27
2025-09-01 08:35:12.650 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:35:18.635 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:35:20.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:35:21.788 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5730
2025-09-01 08:35:22.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5265
2025-09-01 08:35:22.083 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3322
2025-09-01 08:35:22.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4772
2025-09-01 08:35:22.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:35:22.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:35:22.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.573
2025-09-01 08:35:22.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.526
2025-09-01 08:35:22.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.332
2025-09-01 08:35:22.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.477
2025-09-01 08:35:22.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:35:22.084 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:35:22.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:35:22.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:35:22.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:35:22.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:35:22.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:35:22.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:35:22.085 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:35:23.732 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:35:25.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:35:26.824 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:35:28.396 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:35:30.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:35:31.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:35:33.081 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:35:34.611 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:35:36.207 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:35:36.207 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-09-01 08:35:36.207 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-09-01 08:35:36.208 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:35:36.232 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.97 ms, Average inference time: 2.35 ms

2025-09-01 08:35:36.233 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:35:36.272 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:35:36.316 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch231
2025-09-01 08:35:38.871 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 231/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.127s, data_time: 0.047s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 4.214e-03, size: 480, ETA: 1:47:23
2025-09-01 08:35:41.701 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 231/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.055s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 4.208e-03, size: 576, ETA: 1:47:21
2025-09-01 08:35:44.592 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 231/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 4.202e-03, size: 448, ETA: 1:47:18
2025-09-01 08:35:47.431 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 231/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.051s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 4.196e-03, size: 448, ETA: 1:47:16
2025-09-01 08:35:50.314 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 231/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.143s, data_time: 0.062s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 4.191e-03, size: 544, ETA: 1:47:13
2025-09-01 08:35:53.140 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 231/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 4.185e-03, size: 352, ETA: 1:47:11
2025-09-01 08:35:54.438 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:35:54.476 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch232
2025-09-01 08:35:57.259 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 232/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.135s, data_time: 0.036s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.177e-03, size: 576, ETA: 1:47:07
2025-09-01 08:36:00.149 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 232/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.044s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 4.171e-03, size: 544, ETA: 1:47:04
2025-09-01 08:36:03.013 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 232/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.140s, data_time: 0.040s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 4.165e-03, size: 352, ETA: 1:47:02
2025-09-01 08:36:05.903 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 232/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 4.160e-03, size: 544, ETA: 1:46:59
2025-09-01 08:36:08.615 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 232/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.131s, data_time: 0.036s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 4.154e-03, size: 352, ETA: 1:46:56
2025-09-01 08:36:11.462 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 232/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.135s, data_time: 0.020s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 4.148e-03, size: 416, ETA: 1:46:54
2025-09-01 08:36:12.766 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:36:12.811 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch233
2025-09-01 08:36:15.559 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 233/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, data_time: 0.059s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 4.140e-03, size: 576, ETA: 1:46:50
2025-09-01 08:36:18.428 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 233/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.134e-03, size: 384, ETA: 1:46:47
2025-09-01 08:36:21.324 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 233/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.139s, data_time: 0.024s, total_loss: 5.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 4.129e-03, size: 288, ETA: 1:46:45
2025-09-01 08:36:24.267 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 233/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, data_time: 0.044s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 4.123e-03, size: 480, ETA: 1:46:42
2025-09-01 08:36:27.161 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 233/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.143s, data_time: 0.061s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 4.117e-03, size: 544, ETA: 1:46:40
2025-09-01 08:36:29.936 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 233/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.138s, data_time: 0.056s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.112e-03, size: 320, ETA: 1:46:37
2025-09-01 08:36:31.281 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:36:31.310 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch234
2025-09-01 08:36:34.155 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 234/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.064s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 4.103e-03, size: 384, ETA: 1:46:33
2025-09-01 08:36:36.971 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 234/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.136s, data_time: 0.040s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 4.098e-03, size: 544, ETA: 1:46:31
2025-09-01 08:36:39.773 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 234/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.021s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 4.092e-03, size: 352, ETA: 1:46:28
2025-09-01 08:36:42.641 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 234/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.139s, data_time: 0.033s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 4.086e-03, size: 384, ETA: 1:46:26
2025-09-01 08:36:45.516 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 234/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.142s, data_time: 0.063s, total_loss: 7.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 4.081e-03, size: 320, ETA: 1:46:23
2025-09-01 08:36:48.275 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 234/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.132s, data_time: 0.052s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 4.075e-03, size: 512, ETA: 1:46:20
2025-09-01 08:36:49.565 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:36:49.602 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch235
2025-09-01 08:36:52.372 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 235/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.137s, data_time: 0.054s, total_loss: 8.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.4, lr: 4.067e-03, size: 288, ETA: 1:46:16
2025-09-01 08:36:55.295 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 235/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.143s, data_time: 0.037s, total_loss: 8.7, iou_loss: 3.7, l1_loss: 0.0, conf_loss: 4.1, cls_loss: 0.9, lr: 4.061e-03, size: 512, ETA: 1:46:14
2025-09-01 08:36:58.031 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 235/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.129s, data_time: 0.016s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 4.055e-03, size: 288, ETA: 1:46:11
2025-09-01 08:37:00.920 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 235/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.010s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.050e-03, size: 320, ETA: 1:46:09
2025-09-01 08:37:03.691 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 235/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.136s, data_time: 0.026s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 4.044e-03, size: 544, ETA: 1:46:06
2025-09-01 08:37:06.541 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 235/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 4.038e-03, size: 480, ETA: 1:46:03
2025-09-01 08:37:07.802 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:37:13.580 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:37:15.423 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:37:16.581 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5409
2025-09-01 08:37:16.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5301
2025-09-01 08:37:16.924 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3265
2025-09-01 08:37:16.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4658
2025-09-01 08:37:16.925 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:37:16.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:37:16.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.541
2025-09-01 08:37:16.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.530
2025-09-01 08:37:16.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.327
2025-09-01 08:37:16.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.466
2025-09-01 08:37:16.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:37:16.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:37:16.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:37:16.926 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:37:16.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:37:16.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:37:16.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:37:16.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:37:16.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:37:18.542 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:37:20.176 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:37:21.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:37:23.414 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:37:25.107 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:37:26.621 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:37:28.314 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:37:29.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:37:31.372 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:37:31.372 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-09-01 08:37:31.372 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-09-01 08:37:31.372 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:37:31.398 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.97 ms, Average inference time: 2.35 ms

2025-09-01 08:37:31.399 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:37:31.425 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:37:31.467 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch236
2025-09-01 08:37:33.886 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 236/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.116s, data_time: 0.033s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 4.030e-03, size: 512, ETA: 1:45:59
2025-09-01 08:37:36.670 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 236/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, data_time: 0.042s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 4.024e-03, size: 480, ETA: 1:45:56
2025-09-01 08:37:39.580 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 236/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.143s, data_time: 0.064s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 4.019e-03, size: 288, ETA: 1:45:54
2025-09-01 08:37:42.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 236/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.142s, data_time: 0.062s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 4.013e-03, size: 576, ETA: 1:45:51
2025-09-01 08:37:45.301 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 236/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.143s, data_time: 0.065s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 4.008e-03, size: 576, ETA: 1:45:49
2025-09-01 08:37:48.176 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 236/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 4.002e-03, size: 544, ETA: 1:45:46
2025-09-01 08:37:49.456 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:37:49.504 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch237
2025-09-01 08:37:52.270 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 237/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.134s, data_time: 0.033s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.994e-03, size: 352, ETA: 1:45:42
2025-09-01 08:37:55.025 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 237/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, data_time: 0.041s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.988e-03, size: 576, ETA: 1:45:40
2025-09-01 08:37:57.829 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 237/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 5.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.5, lr: 3.982e-03, size: 384, ETA: 1:45:37
2025-09-01 08:38:00.789 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 237/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.977e-03, size: 448, ETA: 1:45:34
2025-09-01 08:38:03.712 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 237/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.124s, data_time: 0.042s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.971e-03, size: 288, ETA: 1:45:31
2025-09-01 08:38:06.598 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 237/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.130s, data_time: 0.015s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 3.965e-03, size: 544, ETA: 1:45:29
2025-09-01 08:38:07.812 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:38:07.852 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch238
2025-09-01 08:38:10.671 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 238/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.128s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.957e-03, size: 448, ETA: 1:45:24
2025-09-01 08:38:13.582 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 238/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.131s, 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: 3.952e-03, size: 320, ETA: 1:45:21
2025-09-01 08:38:16.329 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 238/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 5.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 3.946e-03, size: 544, ETA: 1:45:18
2025-09-01 08:38:19.126 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 238/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.125s, data_time: 0.010s, total_loss: 7.5, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 3.940e-03, size: 288, ETA: 1:45:15
2025-09-01 08:38:22.050 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 238/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 3.935e-03, size: 384, ETA: 1:45:13
2025-09-01 08:38:24.935 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 238/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.137s, data_time: 0.040s, total_loss: 8.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 4.2, cls_loss: 1.0, lr: 3.929e-03, size: 416, ETA: 1:45:10
2025-09-01 08:38:26.216 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:38:26.273 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch239
2025-09-01 08:38:29.024 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 239/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.133s, data_time: 0.045s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 3.921e-03, size: 320, ETA: 1:45:06
2025-09-01 08:38:31.925 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 239/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.143s, data_time: 0.069s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.915e-03, size: 544, ETA: 1:45:04
2025-09-01 08:38:34.695 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 239/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.136s, data_time: 0.056s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.910e-03, size: 256, ETA: 1:45:01
2025-09-01 08:38:37.555 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 239/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.129s, data_time: 0.041s, total_loss: 6.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.904e-03, size: 352, ETA: 1:44:58
2025-09-01 08:38:40.531 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 239/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.129s, data_time: 0.008s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 3.899e-03, size: 576, ETA: 1:44:55
2025-09-01 08:38:43.476 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 239/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.133s, 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: 3.893e-03, size: 288, ETA: 1:44:53
2025-09-01 08:38:44.815 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:38:44.851 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch240
2025-09-01 08:38:47.565 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 240/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.125s, 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: 3.885e-03, size: 320, ETA: 1:44:48
2025-09-01 08:38:50.404 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 240/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.126s, data_time: 0.014s, total_loss: 6.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 3.879e-03, size: 480, ETA: 1:44:45
2025-09-01 08:38:53.204 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 240/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.133s, data_time: 0.032s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 3.874e-03, size: 448, ETA: 1:44:43
2025-09-01 08:38:56.035 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 240/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.135s, data_time: 0.043s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 3.868e-03, size: 256, ETA: 1:44:40
2025-09-01 08:38:58.989 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 240/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.142s, data_time: 0.039s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.862e-03, size: 576, ETA: 1:44:37
2025-09-01 08:39:01.890 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 240/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.131s, data_time: 0.019s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 3.857e-03, size: 544, ETA: 1:44:35
2025-09-01 08:39:03.194 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:39:09.061 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:39:11.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:39:12.323 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5396
2025-09-01 08:39:12.815 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4905
2025-09-01 08:39:12.861 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3251
2025-09-01 08:39:12.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4517
2025-09-01 08:39:12.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:39:12.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:39:12.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.540
2025-09-01 08:39:12.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.490
2025-09-01 08:39:12.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.325
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.452
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:39:12.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:39:14.508 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:39:16.159 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:39:18.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:39:19.889 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:39:21.485 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:39:23.119 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:39:24.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:39:26.578 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:39:28.166 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:39:28.166 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-09-01 08:39:28.166 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.45
2025-09-01 08:39:28.166 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:39:28.192 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.94 ms, Average inference time: 2.32 ms

2025-09-01 08:39:28.193 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:39:28.215 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:39:28.248 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch241
2025-09-01 08:39:30.861 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 241/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.125s, data_time: 0.050s, total_loss: 4.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.6, cls_loss: 0.6, lr: 3.849e-03, size: 256, ETA: 1:44:30
2025-09-01 08:39:33.871 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 241/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.5Gb, iter_time: 0.131s, data_time: 0.024s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 3.843e-03, size: 448, ETA: 1:44:27
2025-09-01 08:39:36.767 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 241/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.837e-03, size: 576, ETA: 1:44:25
2025-09-01 08:39:39.582 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 241/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.129s, data_time: 0.011s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 3.832e-03, size: 288, ETA: 1:44:22
2025-09-01 08:39:42.444 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 241/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, 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: 0.7, lr: 3.826e-03, size: 576, ETA: 1:44:19
2025-09-01 08:39:45.285 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 241/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.123s, data_time: 0.009s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.821e-03, size: 480, ETA: 1:44:16
2025-09-01 08:39:46.536 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:39:46.659 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch242
2025-09-01 08:39:49.465 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 242/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.048s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 3.813e-03, size: 320, ETA: 1:44:12
2025-09-01 08:39:52.258 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 242/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 3.807e-03, size: 256, ETA: 1:44:09
2025-09-01 08:39:55.030 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 242/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.134s, data_time: 0.050s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.801e-03, size: 288, ETA: 1:44:07
2025-09-01 08:39:57.951 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 242/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.137s, data_time: 0.053s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.796e-03, size: 416, ETA: 1:44:04
2025-09-01 08:40:00.805 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 242/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 3.790e-03, size: 384, ETA: 1:44:01
2025-09-01 08:40:03.519 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 242/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, data_time: 0.028s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 3.785e-03, size: 544, ETA: 1:43:59
2025-09-01 08:40:04.830 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:40:04.866 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch243
2025-09-01 08:40:07.748 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 243/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.139s, data_time: 0.042s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.777e-03, size: 352, ETA: 1:43:55
2025-09-01 08:40:10.555 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 243/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.125s, data_time: 0.023s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.771e-03, size: 256, ETA: 1:43:52
2025-09-01 08:40:13.384 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 243/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.127s, data_time: 0.018s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 3.765e-03, size: 256, ETA: 1:43:49
2025-09-01 08:40:16.289 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 243/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.127s, data_time: 0.019s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.760e-03, size: 576, ETA: 1:43:46
2025-09-01 08:40:19.289 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 243/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.130s, 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: 3.754e-03, size: 576, ETA: 1:43:43
2025-09-01 08:40:22.090 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 243/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.122s, 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: 3.749e-03, size: 448, ETA: 1:43:40
2025-09-01 08:40:23.274 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:40:23.334 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch244
2025-09-01 08:40:26.299 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 244/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.130s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 3.741e-03, size: 384, ETA: 1:43:36
2025-09-01 08:40:29.040 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 244/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.125s, data_time: 0.005s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.735e-03, size: 512, ETA: 1:43:33
2025-09-01 08:40:32.106 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 244/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.138s, 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: 3.730e-03, size: 576, ETA: 1:43:30
2025-09-01 08:40:35.030 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 244/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.1, lr: 3.724e-03, size: 256, ETA: 1:43:27
2025-09-01 08:40:37.802 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 244/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.123s, data_time: 0.019s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.719e-03, size: 384, ETA: 1:43:24
2025-09-01 08:40:40.666 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 244/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.142s, data_time: 0.065s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 3.713e-03, size: 480, ETA: 1:43:22
2025-09-01 08:40:42.023 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:40:42.070 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch245
2025-09-01 08:40:44.992 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 245/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.145s, data_time: 0.065s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 3.705e-03, size: 416, ETA: 1:43:18
2025-09-01 08:40:47.757 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 245/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.138s, data_time: 0.058s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 3.699e-03, size: 256, ETA: 1:43:16
2025-09-01 08:40:50.584 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 245/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.141s, data_time: 0.060s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 3.694e-03, size: 480, ETA: 1:43:13
2025-09-01 08:40:53.309 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 245/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, data_time: 0.049s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.688e-03, size: 544, ETA: 1:43:10
2025-09-01 08:40:56.216 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 245/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.145s, data_time: 0.067s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 3.683e-03, size: 512, ETA: 1:43:08
2025-09-01 08:40:58.910 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 245/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.133s, data_time: 0.053s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 3.677e-03, size: 384, ETA: 1:43:05
2025-09-01 08:41:00.229 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:41:06.132 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:41:07.842 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:41:08.954 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5862
2025-09-01 08:41:09.175 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5408
2025-09-01 08:41:09.274 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3228
2025-09-01 08:41:09.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4833
2025-09-01 08:41:09.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:41:09.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:41:09.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.586
2025-09-01 08:41:09.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.541
2025-09-01 08:41:09.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.323
2025-09-01 08:41:09.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.483
2025-09-01 08:41:09.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:41:09.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:41:09.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:41:09.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:41:09.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:41:09.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:41:09.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:41:09.277 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:41:09.277 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:41:10.624 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:41:11.933 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:41:13.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:41:15.040 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:41:16.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:41:17.878 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:41:19.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:41:20.759 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:41:22.215 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:41:22.215 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-09-01 08:41:22.216 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-09-01 08:41:22.216 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:41:22.226 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.95 ms, Average inference time: 2.31 ms

2025-09-01 08:41:22.227 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:41:22.332 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:41:22.387 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch246
2025-09-01 08:41:24.862 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 246/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.123s, data_time: 0.043s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.669e-03, size: 288, ETA: 1:43:01
2025-09-01 08:41:27.719 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 246/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, data_time: 0.037s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 3.664e-03, size: 448, ETA: 1:42:58
2025-09-01 08:41:30.502 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 246/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.127s, data_time: 0.014s, total_loss: 7.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.658e-03, size: 384, ETA: 1:42:55
2025-09-01 08:41:33.295 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 246/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.128s, data_time: 0.012s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 3.653e-03, size: 576, ETA: 1:42:52
2025-09-01 08:41:36.232 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 246/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.130s, data_time: 0.021s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.647e-03, size: 416, ETA: 1:42:50
2025-09-01 08:41:39.073 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 246/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 3.642e-03, size: 320, ETA: 1:42:47
2025-09-01 08:41:40.363 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:41:40.511 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch247
2025-09-01 08:41:43.323 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 247/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.121s, 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: 3.634e-03, size: 512, ETA: 1:42:42
2025-09-01 08:41:46.266 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 247/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, 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: 3.628e-03, size: 320, ETA: 1:42:39
2025-09-01 08:41:49.058 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 247/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.128s, data_time: 0.022s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 3.623e-03, size: 544, ETA: 1:42:37
2025-09-01 08:41:51.937 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 247/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.143s, data_time: 0.065s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.617e-03, size: 512, ETA: 1:42:34
2025-09-01 08:41:54.801 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 247/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.143s, data_time: 0.060s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 3.612e-03, size: 512, ETA: 1:42:32
2025-09-01 08:41:57.693 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 247/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.144s, data_time: 0.061s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 3.606e-03, size: 576, ETA: 1:42:29
2025-09-01 08:41:58.891 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:41:58.930 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch248
2025-09-01 08:42:01.720 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 248/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.135s, data_time: 0.051s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 3.598e-03, size: 416, ETA: 1:42:25
2025-09-01 08:42:04.666 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 248/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.137s, data_time: 0.052s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 3.593e-03, size: 352, ETA: 1:42:22
2025-09-01 08:42:07.566 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 248/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.136s, data_time: 0.040s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 3.587e-03, size: 384, ETA: 1:42:20
2025-09-01 08:42:10.410 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 248/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.582e-03, size: 256, ETA: 1:42:17
2025-09-01 08:42:13.368 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 248/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, 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: 3.576e-03, size: 352, ETA: 1:42:14
2025-09-01 08:42:16.280 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 248/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 4.4, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 1.5, cls_loss: 0.6, lr: 3.571e-03, size: 352, ETA: 1:42:11
2025-09-01 08:42:17.502 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:42:17.589 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch249
2025-09-01 08:42:20.270 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 249/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.122s, data_time: 0.005s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.563e-03, size: 448, ETA: 1:42:07
2025-09-01 08:42:23.014 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 249/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.557e-03, size: 384, ETA: 1:42:04
2025-09-01 08:42:26.027 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 249/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.146s, data_time: 0.026s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 3.552e-03, size: 288, ETA: 1:42:02
2025-09-01 08:42:28.836 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 249/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.137s, data_time: 0.022s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 3.546e-03, size: 256, ETA: 1:41:59
2025-09-01 08:42:31.649 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 249/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 3.541e-03, size: 352, ETA: 1:41:56
2025-09-01 08:42:34.414 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 249/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 3.536e-03, size: 416, ETA: 1:41:54
2025-09-01 08:42:35.766 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:42:35.807 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch250
2025-09-01 08:42:38.546 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 250/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.135s, data_time: 0.058s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.528e-03, size: 416, ETA: 1:41:50
2025-09-01 08:42:41.425 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 250/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.142s, data_time: 0.065s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 3.522e-03, size: 512, ETA: 1:41:48
2025-09-01 08:42:44.226 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 250/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.138s, data_time: 0.061s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.517e-03, size: 576, ETA: 1:41:45
2025-09-01 08:42:47.135 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 250/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.145s, data_time: 0.064s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.511e-03, size: 256, ETA: 1:41:42
2025-09-01 08:42:49.988 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 250/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.142s, data_time: 0.065s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 3.506e-03, size: 320, ETA: 1:41:40
2025-09-01 08:42:52.831 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 250/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.140s, data_time: 0.059s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 3.500e-03, size: 288, ETA: 1:41:37
2025-09-01 08:42:54.013 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:42:59.928 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:43:04.819 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:43:08.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5479
2025-09-01 08:43:08.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5300
2025-09-01 08:43:09.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3159
2025-09-01 08:43:09.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4646
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.548
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.530
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.316
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.465
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:43:09.033 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:43:09.034 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:43:09.034 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:43:09.034 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:43:09.034 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:43:13.370 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:43:17.585 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:43:21.961 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:43:26.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:43:30.350 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:43:34.507 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:43:39.047 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:43:43.419 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:43:47.917 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:43:47.917 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.23
2025-09-01 08:43:47.917 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.46
2025-09-01 08:43:47.917 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:43:47.951 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.43 ms, Average NMS time: 0.98 ms, Average inference time: 2.40 ms

2025-09-01 08:43:47.953 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:43:47.979 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:43:48.011 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch251
2025-09-01 08:43:50.576 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 251/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.126s, data_time: 0.051s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.492e-03, size: 512, ETA: 1:41:33
2025-09-01 08:43:53.468 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 251/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 3.487e-03, size: 256, ETA: 1:41:31
2025-09-01 08:43:56.267 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 251/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.138s, data_time: 0.056s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 3.482e-03, size: 416, ETA: 1:41:28
2025-09-01 08:43:59.049 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 251/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.136s, data_time: 0.031s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.476e-03, size: 352, ETA: 1:41:25
2025-09-01 08:44:01.922 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 251/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 5.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.7, lr: 3.471e-03, size: 288, ETA: 1:41:23
2025-09-01 08:44:04.755 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 251/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.139s, data_time: 0.046s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 3.465e-03, size: 320, ETA: 1:41:20
2025-09-01 08:44:06.081 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:44:06.119 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch252
2025-09-01 08:44:08.853 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 252/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 3.457e-03, size: 352, ETA: 1:41:16
2025-09-01 08:44:11.717 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 252/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.136s, data_time: 0.060s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.452e-03, size: 480, ETA: 1:41:14
2025-09-01 08:44:14.511 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 252/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.126s, data_time: 0.033s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.447e-03, size: 320, ETA: 1:41:11
2025-09-01 08:44:17.404 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 252/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.128s, data_time: 0.028s, total_loss: 8.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.5, lr: 3.441e-03, size: 256, ETA: 1:41:08
2025-09-01 08:44:20.280 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 252/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.130s, data_time: 0.004s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 3.436e-03, size: 352, ETA: 1:41:05
2025-09-01 08:44:23.160 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 252/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 3.430e-03, size: 480, ETA: 1:41:02
2025-09-01 08:44:24.369 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:44:24.495 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch253
2025-09-01 08:44:27.331 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 253/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.422e-03, size: 384, ETA: 1:40:58
2025-09-01 08:44:30.116 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 253/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.122s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 3.417e-03, size: 384, ETA: 1:40:55
2025-09-01 08:44:32.984 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 253/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.125s, data_time: 0.001s, total_loss: 8.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 3.412e-03, size: 320, ETA: 1:40:52
2025-09-01 08:44:35.942 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 253/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.128s, data_time: 0.006s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 3.406e-03, size: 576, ETA: 1:40:49
2025-09-01 08:44:38.648 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 253/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.121s, data_time: 0.012s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 3.401e-03, size: 576, ETA: 1:40:46
2025-09-01 08:44:41.619 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 253/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.129s, data_time: 0.008s, total_loss: 7.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 3.395e-03, size: 288, ETA: 1:40:43
2025-09-01 08:44:42.921 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:44:42.962 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch254
2025-09-01 08:44:45.779 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 254/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 3.388e-03, size: 544, ETA: 1:40:39
2025-09-01 08:44:48.709 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 254/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 3.382e-03, size: 416, ETA: 1:40:36
2025-09-01 08:44:51.603 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 254/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.134s, data_time: 0.011s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.377e-03, size: 512, ETA: 1:40:34
2025-09-01 08:44:54.399 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 254/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.125s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 3.372e-03, size: 416, ETA: 1:40:31
2025-09-01 08:44:57.212 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 254/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.128s, data_time: 0.001s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 3.366e-03, size: 352, ETA: 1:40:28
2025-09-01 08:45:00.045 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 254/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, data_time: 0.034s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.0, lr: 3.361e-03, size: 448, ETA: 1:40:25
2025-09-01 08:45:01.316 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:45:01.378 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch255
2025-09-01 08:45:04.223 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 255/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.120s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 3.353e-03, size: 384, ETA: 1:40:21
2025-09-01 08:45:07.120 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 255/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.124s, 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: 3.348e-03, size: 576, ETA: 1:40:18
2025-09-01 08:45:09.894 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 255/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.124s, data_time: 0.017s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.342e-03, size: 320, ETA: 1:40:15
2025-09-01 08:45:12.782 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 255/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.131s, data_time: 0.052s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 3.337e-03, size: 512, ETA: 1:40:12
2025-09-01 08:45:15.724 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 255/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.133s, data_time: 0.045s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 3.332e-03, size: 448, ETA: 1:40:09
2025-09-01 08:45:18.463 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 255/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.122s, data_time: 0.022s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 3.326e-03, size: 352, ETA: 1:40:06
2025-09-01 08:45:19.649 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:45:25.570 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:45:27.757 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:45:29.241 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5899
2025-09-01 08:45:29.511 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5450
2025-09-01 08:45:29.582 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3335
2025-09-01 08:45:29.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4895
2025-09-01 08:45:29.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:45:29.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:45:29.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.590
2025-09-01 08:45:29.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.545
2025-09-01 08:45:29.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.333
2025-09-01 08:45:29.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.489
2025-09-01 08:45:29.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:45:29.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:45:29.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:45:29.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:45:29.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:45:29.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:45:29.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:45:29.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:45:29.584 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:45:31.421 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:45:33.230 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:45:35.051 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:45:36.927 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:45:38.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:45:40.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:45:42.516 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:45:44.319 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:45:46.220 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:45:46.220 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-09-01 08:45:46.220 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-09-01 08:45:46.220 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:45:46.245 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.40 ms, Average NMS time: 0.96 ms, Average inference time: 2.36 ms

2025-09-01 08:45:46.246 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:45:46.275 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:45:46.314 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch256
2025-09-01 08:45:48.709 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 256/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.113s, data_time: 0.036s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 3.318e-03, size: 384, ETA: 1:40:01
2025-09-01 08:45:51.636 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 256/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.144s, data_time: 0.062s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.313e-03, size: 512, ETA: 1:39:59
2025-09-01 08:45:54.515 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 256/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, data_time: 0.051s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 3.308e-03, size: 544, ETA: 1:39:56
2025-09-01 08:45:57.350 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 256/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 3.302e-03, size: 320, ETA: 1:39:54
2025-09-01 08:46:00.100 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 256/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.136s, data_time: 0.059s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.297e-03, size: 320, ETA: 1:39:51
2025-09-01 08:46:03.000 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 256/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.133s, data_time: 0.046s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 3.292e-03, size: 576, ETA: 1:39:48
2025-09-01 08:46:04.160 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:46:04.384 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch257
2025-09-01 08:46:07.130 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 257/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.115s, data_time: 0.005s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 3.284e-03, size: 352, ETA: 1:39:44
2025-09-01 08:46:10.063 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 257/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.129s, data_time: 0.012s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 3.279e-03, size: 320, ETA: 1:39:41
2025-09-01 08:46:12.885 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 257/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.037s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 3.273e-03, size: 384, ETA: 1:39:38
2025-09-01 08:46:15.578 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 257/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.116s, data_time: 0.016s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 3.268e-03, size: 544, ETA: 1:39:35
2025-09-01 08:46:18.405 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 257/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.139s, data_time: 0.049s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.263e-03, size: 256, ETA: 1:39:32
2025-09-01 08:46:21.276 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 257/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.135s, data_time: 0.038s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 3.257e-03, size: 576, ETA: 1:39:30
2025-09-01 08:46:22.469 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:46:22.538 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch258
2025-09-01 08:46:25.280 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 258/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.128s, data_time: 0.027s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.250e-03, size: 480, ETA: 1:39:25
2025-09-01 08:46:28.100 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 258/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.244e-03, size: 544, ETA: 1:39:23
2025-09-01 08:46:30.922 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 258/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.130s, data_time: 0.028s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.239e-03, size: 544, ETA: 1:39:20
2025-09-01 08:46:33.832 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 258/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 3.234e-03, size: 416, ETA: 1:39:17
2025-09-01 08:46:36.692 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 258/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 3.228e-03, size: 384, ETA: 1:39:15
2025-09-01 08:46:39.532 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 258/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.223e-03, size: 320, ETA: 1:39:12
2025-09-01 08:46:40.762 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:46:40.799 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch259
2025-09-01 08:46:43.638 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 259/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.129s, data_time: 0.027s, total_loss: 4.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 3.215e-03, size: 416, ETA: 1:39:08
2025-09-01 08:46:46.394 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 259/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.129s, data_time: 0.015s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 3.210e-03, size: 416, ETA: 1:39:05
2025-09-01 08:46:49.228 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 259/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.127s, data_time: 0.009s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 3.205e-03, size: 448, ETA: 1:39:02
2025-09-01 08:46:52.022 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 259/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 3.200e-03, size: 384, ETA: 1:38:59
2025-09-01 08:46:54.908 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 259/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 3.194e-03, size: 480, ETA: 1:38:56
2025-09-01 08:46:57.686 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 259/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.123s, data_time: 0.006s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 3.189e-03, size: 320, ETA: 1:38:53
2025-09-01 08:46:58.954 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:46:59.021 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch260
2025-09-01 08:47:01.757 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 260/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.126s, data_time: 0.016s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.181e-03, size: 480, ETA: 1:38:49
2025-09-01 08:47:04.765 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 260/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.130s, 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: 3.176e-03, size: 288, ETA: 1:38:46
2025-09-01 08:47:07.486 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 260/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.122s, data_time: 0.010s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.171e-03, size: 416, ETA: 1:38:43
2025-09-01 08:47:10.273 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 260/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.127s, data_time: 0.049s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 3.166e-03, size: 288, ETA: 1:38:40
2025-09-01 08:47:13.160 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 260/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.056s, total_loss: 5.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 3.160e-03, size: 352, ETA: 1:38:38
2025-09-01 08:47:15.968 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 260/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.155e-03, size: 480, ETA: 1:38:35
2025-09-01 08:47:17.185 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:47:23.039 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:47:24.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:47:24.705 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5199
2025-09-01 08:47:24.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4960
2025-09-01 08:47:24.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.2719
2025-09-01 08:47:24.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4292
2025-09-01 08:47:24.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:47:24.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:47:24.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.520
2025-09-01 08:47:24.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.496
2025-09-01 08:47:24.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.272
2025-09-01 08:47:24.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.429
2025-09-01 08:47:24.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:47:24.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:47:24.946 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:47:24.946 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:47:24.946 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:47:24.946 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:47:24.946 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:47:24.946 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:47:24.946 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:47:25.716 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:47:26.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:47:27.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:47:28.091 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:47:28.910 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:47:29.672 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:47:30.465 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:47:31.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:47:32.160 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:47:32.160 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.21
2025-09-01 08:47:32.161 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.43
2025-09-01 08:47:32.161 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:47:32.175 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.94 ms, Average inference time: 2.29 ms

2025-09-01 08:47:32.176 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:47:32.209 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:47:32.253 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch261
2025-09-01 08:47:34.781 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 261/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.120s, data_time: 0.029s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 3.147e-03, size: 256, ETA: 1:38:31
2025-09-01 08:47:37.600 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 261/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.136s, data_time: 0.042s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.142e-03, size: 448, ETA: 1:38:28
2025-09-01 08:47:40.455 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 261/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.140s, data_time: 0.034s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 3.137e-03, size: 416, ETA: 1:38:26
2025-09-01 08:47:43.215 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 261/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 3.132e-03, size: 576, ETA: 1:38:23
2025-09-01 08:47:46.109 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 261/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.142s, data_time: 0.003s, total_loss: 8.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.4, cls_loss: 0.9, lr: 3.126e-03, size: 576, ETA: 1:38:20
2025-09-01 08:47:48.852 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 261/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.009s, total_loss: 7.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 3.121e-03, size: 480, ETA: 1:38:18
2025-09-01 08:47:50.148 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:47:50.264 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch262
2025-09-01 08:47:53.183 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 262/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.144s, data_time: 0.054s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 3.114e-03, size: 480, ETA: 1:38:14
2025-09-01 08:47:56.076 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 262/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.138s, data_time: 0.041s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 3.108e-03, size: 480, ETA: 1:38:12
2025-09-01 08:47:58.971 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 262/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.040s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 3.103e-03, size: 512, ETA: 1:38:09
2025-09-01 08:48:01.725 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 262/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.131s, data_time: 0.048s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 3.098e-03, size: 320, ETA: 1:38:06
2025-09-01 08:48:04.571 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 262/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.142s, data_time: 0.062s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 3.093e-03, size: 576, ETA: 1:38:04
2025-09-01 08:48:07.419 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 262/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.132s, data_time: 0.038s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 3.087e-03, size: 288, ETA: 1:38:01
2025-09-01 08:48:08.713 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:48:08.771 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch263
2025-09-01 08:48:11.504 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 263/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.018s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.080e-03, size: 384, ETA: 1:37:57
2025-09-01 08:48:14.482 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 263/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.144s, data_time: 0.016s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.075e-03, size: 384, ETA: 1:37:55
2025-09-01 08:48:17.453 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 263/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.144s, 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: 3.070e-03, size: 544, ETA: 1:37:52
2025-09-01 08:48:20.242 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 263/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.135s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 3.064e-03, size: 576, ETA: 1:37:49
2025-09-01 08:48:23.087 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 263/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, 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: 3.059e-03, size: 416, ETA: 1:37:47
2025-09-01 08:48:25.913 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 263/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.140s, data_time: 0.004s, total_loss: 5.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 3.054e-03, size: 288, ETA: 1:37:44
2025-09-01 08:48:27.182 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:48:27.336 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch264
2025-09-01 08:48:30.167 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 264/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.015s, total_loss: 7.7, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 3.046e-03, size: 416, ETA: 1:37:40
2025-09-01 08:48:33.008 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 264/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.047s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 3.041e-03, size: 256, ETA: 1:37:38
2025-09-01 08:48:35.888 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 264/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.142s, data_time: 0.063s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 3.036e-03, size: 576, ETA: 1:37:35
2025-09-01 08:48:38.693 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 264/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 3.031e-03, size: 384, ETA: 1:37:33
2025-09-01 08:48:41.618 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 264/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.051s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 3.026e-03, size: 256, ETA: 1:37:30
2025-09-01 08:48:44.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 264/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.130s, data_time: 0.011s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 3.020e-03, size: 576, ETA: 1:37:27
2025-09-01 08:48:45.521 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:48:45.572 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch265
2025-09-01 08:48:48.470 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 265/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.143s, data_time: 0.006s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 3.013e-03, size: 288, ETA: 1:37:23
2025-09-01 08:48:51.212 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 265/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.001s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 3.008e-03, size: 544, ETA: 1:37:21
2025-09-01 08:48:54.092 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 265/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 3.003e-03, size: 576, ETA: 1:37:18
2025-09-01 08:48:56.849 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 265/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.049s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 2.998e-03, size: 544, ETA: 1:37:15
2025-09-01 08:48:59.720 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 265/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.050s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 2.992e-03, size: 416, ETA: 1:37:13
2025-09-01 08:49:02.672 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 265/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.145s, data_time: 0.033s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.987e-03, size: 480, ETA: 1:37:10
2025-09-01 08:49:03.851 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:49:09.781 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:49:11.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:49:12.855 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5730
2025-09-01 08:49:13.167 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5365
2025-09-01 08:49:13.248 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3196
2025-09-01 08:49:13.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4764
2025-09-01 08:49:13.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:49:13.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:49:13.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.573
2025-09-01 08:49:13.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.537
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.320
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.476
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:49:13.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:49:14.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:49:16.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:49:17.530 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:49:18.957 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:49:20.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:49:21.785 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:49:23.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:49:24.526 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:49:25.952 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:49:25.953 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-09-01 08:49:25.953 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-09-01 08:49:25.953 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:49:25.964 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.92 ms, Average inference time: 2.30 ms

2025-09-01 08:49:25.964 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:49:25.991 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:49:26.021 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch266
2025-09-01 08:49:28.441 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 266/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.110s, data_time: 0.011s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 2.980e-03, size: 320, ETA: 1:37:06
2025-09-01 08:49:31.212 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 266/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.124s, data_time: 0.024s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.975e-03, size: 384, ETA: 1:37:03
2025-09-01 08:49:34.125 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 266/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.029s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.969e-03, size: 256, ETA: 1:37:00
2025-09-01 08:49:36.936 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 266/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.043s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 2.964e-03, size: 352, ETA: 1:36:57
2025-09-01 08:49:39.869 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 266/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.137s, data_time: 0.019s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.959e-03, size: 352, ETA: 1:36:54
2025-09-01 08:49:42.632 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 266/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.954e-03, size: 512, ETA: 1:36:52
2025-09-01 08:49:43.799 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:49:43.857 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch267
2025-09-01 08:49:46.629 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 267/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.008s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 2.947e-03, size: 288, ETA: 1:36:48
2025-09-01 08:49:49.456 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 267/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.138s, data_time: 0.040s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 2.942e-03, size: 480, ETA: 1:36:45
2025-09-01 08:49:52.321 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 267/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.142s, data_time: 0.038s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.936e-03, size: 448, ETA: 1:36:42
2025-09-01 08:49:55.177 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 267/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, data_time: 0.048s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.931e-03, size: 320, ETA: 1:36:40
2025-09-01 08:49:57.994 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 267/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.138s, data_time: 0.056s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.926e-03, size: 512, ETA: 1:36:37
2025-09-01 08:50:00.795 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 267/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 2.921e-03, size: 352, ETA: 1:36:35
2025-09-01 08:50:01.940 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:50:01.998 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch268
2025-09-01 08:50:04.807 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 268/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.138s, data_time: 0.055s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 2.914e-03, size: 320, ETA: 1:36:31
2025-09-01 08:50:07.641 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 268/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.135s, data_time: 0.036s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 2.909e-03, size: 416, ETA: 1:36:28
2025-09-01 08:50:10.518 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 268/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.138s, data_time: 0.018s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 2.903e-03, size: 544, ETA: 1:36:25
2025-09-01 08:50:13.403 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 268/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.137s, data_time: 0.018s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.898e-03, size: 512, ETA: 1:36:23
2025-09-01 08:50:16.174 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 268/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.132s, data_time: 0.050s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 2.893e-03, size: 288, ETA: 1:36:20
2025-09-01 08:50:18.998 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 268/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.888e-03, size: 448, ETA: 1:36:17
2025-09-01 08:50:20.323 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:50:20.379 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch269
2025-09-01 08:50:23.147 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 269/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 2.881e-03, size: 480, ETA: 1:36:14
2025-09-01 08:50:26.050 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 269/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.142s, data_time: 0.041s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 2.876e-03, size: 288, ETA: 1:36:11
2025-09-01 08:50:28.931 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 269/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, data_time: 0.006s, total_loss: 7.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.7, lr: 2.871e-03, size: 576, ETA: 1:36:08
2025-09-01 08:50:31.814 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 269/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.866e-03, size: 320, ETA: 1:36:06
2025-09-01 08:50:34.556 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 269/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.861e-03, size: 480, ETA: 1:36:03
2025-09-01 08:50:37.520 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 269/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.145s, data_time: 0.013s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 2.855e-03, size: 416, ETA: 1:36:01
2025-09-01 08:50:38.721 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:50:38.907 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch270
2025-09-01 08:50:41.710 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 270/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.014s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.848e-03, size: 480, ETA: 1:35:57
2025-09-01 08:50:44.514 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 270/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.132s, 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: 2.843e-03, size: 512, ETA: 1:35:54
2025-09-01 08:50:47.510 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 270/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.144s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.838e-03, size: 416, ETA: 1:35:52
2025-09-01 08:50:50.541 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 270/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.143s, data_time: 0.001s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.833e-03, size: 512, ETA: 1:35:49
2025-09-01 08:50:53.208 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 270/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.128s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 2.828e-03, size: 352, ETA: 1:35:46
2025-09-01 08:50:56.071 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 270/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.131s, data_time: 0.035s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 2.823e-03, size: 384, ETA: 1:35:43
2025-09-01 08:50:57.316 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:51:03.249 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:51:06.707 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:51:09.038 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5963
2025-09-01 08:51:09.479 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5566
2025-09-01 08:51:09.600 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3653
2025-09-01 08:51:09.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5061
2025-09-01 08:51:09.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:51:09.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:51:09.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.596
2025-09-01 08:51:09.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.557
2025-09-01 08:51:09.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.365
2025-09-01 08:51:09.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.506
2025-09-01 08:51:09.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:51:09.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:51:09.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:51:09.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:51:09.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:51:09.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:51:09.605 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:51:09.605 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:51:09.605 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:51:12.330 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:51:15.012 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:51:17.700 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:51:20.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:51:23.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:51:25.753 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:51:28.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:51:31.086 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:51:33.786 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:51:33.787 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-09-01 08:51:33.787 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 08:51:33.787 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:51:33.814 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.98 ms, Average inference time: 2.35 ms

2025-09-01 08:51:33.815 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:51:33.841 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:51:33.873 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch271
2025-09-01 08:51:36.314 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 271/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.121s, data_time: 0.025s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.816e-03, size: 288, ETA: 1:35:39
2025-09-01 08:51:39.270 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 271/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.145s, data_time: 0.004s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.811e-03, size: 480, ETA: 1:35:37
2025-09-01 08:51:42.005 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 271/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.004s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.806e-03, size: 576, ETA: 1:35:34
2025-09-01 08:51:44.954 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 271/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.145s, data_time: 0.013s, total_loss: 7.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 2.801e-03, size: 448, ETA: 1:35:32
2025-09-01 08:51:47.747 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 271/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.137s, data_time: 0.017s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.796e-03, size: 480, ETA: 1:35:29
2025-09-01 08:51:50.635 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 271/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 2.791e-03, size: 384, ETA: 1:35:26
2025-09-01 08:51:51.858 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:51:51.975 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch272
2025-09-01 08:51:54.809 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 272/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 2.783e-03, size: 416, ETA: 1:35:22
2025-09-01 08:51:57.754 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 272/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 2.778e-03, size: 512, ETA: 1:35:20
2025-09-01 08:52:00.433 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 272/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.130s, data_time: 0.014s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 2.773e-03, size: 416, ETA: 1:35:17
2025-09-01 08:52:03.284 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 272/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.138s, data_time: 0.060s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.768e-03, size: 416, ETA: 1:35:14
2025-09-01 08:52:06.195 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 272/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.135s, data_time: 0.025s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.763e-03, size: 256, ETA: 1:35:12
2025-09-01 08:52:09.090 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 272/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.136s, data_time: 0.019s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 2.758e-03, size: 544, ETA: 1:35:09
2025-09-01 08:52:10.209 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:52:10.275 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch273
2025-09-01 08:52:13.055 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 273/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.135s, data_time: 0.012s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.751e-03, size: 544, ETA: 1:35:05
2025-09-01 08:52:15.872 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 273/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.137s, data_time: 0.005s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 2.746e-03, size: 544, ETA: 1:35:02
2025-09-01 08:52:18.636 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 273/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.030s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.741e-03, size: 512, ETA: 1:35:00
2025-09-01 08:52:21.518 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 273/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, data_time: 0.035s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.736e-03, size: 544, ETA: 1:34:57
2025-09-01 08:52:24.345 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 273/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.731e-03, size: 256, ETA: 1:34:54
2025-09-01 08:52:27.189 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 273/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, data_time: 0.057s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.726e-03, size: 256, ETA: 1:34:52
2025-09-01 08:52:28.608 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:52:28.644 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch274
2025-09-01 08:52:31.374 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 274/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.130s, data_time: 0.037s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.719e-03, size: 416, ETA: 1:34:48
2025-09-01 08:52:34.315 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 274/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.138s, data_time: 0.005s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 2.714e-03, size: 480, ETA: 1:34:45
2025-09-01 08:52:37.146 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 274/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 2.709e-03, size: 544, ETA: 1:34:43
2025-09-01 08:52:39.785 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 274/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.123s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.704e-03, size: 416, ETA: 1:34:40
2025-09-01 08:52:42.550 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 274/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.136s, data_time: 0.051s, total_loss: 7.3, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.699e-03, size: 256, ETA: 1:34:37
2025-09-01 08:52:45.559 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 274/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.150s, data_time: 0.065s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 2.694e-03, size: 384, ETA: 1:34:35
2025-09-01 08:52:46.936 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:52:46.983 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch275
2025-09-01 08:52:49.663 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 275/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.056s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.687e-03, size: 480, ETA: 1:34:31
2025-09-01 08:52:52.390 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 275/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.136s, data_time: 0.057s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.682e-03, size: 416, ETA: 1:34:28
2025-09-01 08:52:55.200 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 275/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 2.677e-03, size: 544, ETA: 1:34:26
2025-09-01 08:52:58.029 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 275/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 2.672e-03, size: 480, ETA: 1:34:23
2025-09-01 08:53:00.926 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 275/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.144s, data_time: 0.059s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 2.667e-03, size: 256, ETA: 1:34:21
2025-09-01 08:53:03.750 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 275/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 7.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.2, lr: 2.663e-03, size: 256, ETA: 1:34:18
2025-09-01 08:53:05.097 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:53:11.061 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:53:14.093 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:53:16.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5712
2025-09-01 08:53:16.613 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5290
2025-09-01 08:53:16.660 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3460
2025-09-01 08:53:16.661 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4821
2025-09-01 08:53:16.661 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:53:16.661 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.571
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.529
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.346
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.482
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:53:16.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:53:16.663 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:53:19.213 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:53:21.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:53:24.351 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:53:26.914 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:53:29.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:53:31.992 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:53:34.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:53:37.012 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:53:39.538 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:53:39.538 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-09-01 08:53:39.539 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-09-01 08:53:39.539 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:53:39.563 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.95 ms, Average inference time: 2.32 ms

2025-09-01 08:53:39.565 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:53:39.596 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:53:39.628 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch276
2025-09-01 08:53:41.992 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 276/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.111s, data_time: 0.011s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.655e-03, size: 384, ETA: 1:34:14
2025-09-01 08:53:44.893 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 276/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 6.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.651e-03, size: 288, ETA: 1:34:11
2025-09-01 08:53:47.822 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 276/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.011s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.2, lr: 2.646e-03, size: 576, ETA: 1:34:08
2025-09-01 08:53:50.571 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 276/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.126s, data_time: 0.013s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 2.641e-03, size: 352, ETA: 1:34:05
2025-09-01 08:53:53.422 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 276/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 2.636e-03, size: 448, ETA: 1:34:03
2025-09-01 08:53:56.291 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 276/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.142s, data_time: 0.064s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 2.631e-03, size: 288, ETA: 1:34:00
2025-09-01 08:53:57.627 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:53:57.656 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch277
2025-09-01 08:54:00.300 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 277/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.128s, data_time: 0.040s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.624e-03, size: 256, ETA: 1:33:56
2025-09-01 08:54:03.138 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 277/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 2.619e-03, size: 480, ETA: 1:33:54
2025-09-01 08:54:05.937 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 277/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.062s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 2.614e-03, size: 480, ETA: 1:33:51
2025-09-01 08:54:08.762 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 277/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.056s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.609e-03, size: 320, ETA: 1:33:48
2025-09-01 08:54:11.600 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 277/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.135s, data_time: 0.032s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.604e-03, size: 576, ETA: 1:33:46
2025-09-01 08:54:14.367 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 277/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.132s, data_time: 0.032s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 2.600e-03, size: 576, ETA: 1:33:43
2025-09-01 08:54:15.604 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:54:15.648 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch278
2025-09-01 08:54:18.461 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 278/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.128s, data_time: 0.013s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.592e-03, size: 576, ETA: 1:33:39
2025-09-01 08:54:21.313 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 278/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.043s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.588e-03, size: 352, ETA: 1:33:36
2025-09-01 08:54:24.162 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 278/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.134s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.583e-03, size: 288, ETA: 1:33:33
2025-09-01 08:54:26.986 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 278/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.009s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.578e-03, size: 544, ETA: 1:33:31
2025-09-01 08:54:29.767 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 278/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.006s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.573e-03, size: 576, ETA: 1:33:28
2025-09-01 08:54:32.548 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 278/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.131s, 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: 2.568e-03, size: 320, ETA: 1:33:25
2025-09-01 08:54:33.782 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:54:33.834 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch279
2025-09-01 08:54:36.606 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 279/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.020s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.561e-03, size: 512, ETA: 1:33:21
2025-09-01 08:54:39.344 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 279/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.034s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 2.556e-03, size: 480, ETA: 1:33:18
2025-09-01 08:54:42.318 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 279/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.145s, data_time: 0.032s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.552e-03, size: 256, ETA: 1:33:16
2025-09-01 08:54:45.156 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 279/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.002s, total_loss: 7.3, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 2.547e-03, size: 384, ETA: 1:33:13
2025-09-01 08:54:47.895 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 279/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.024s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.542e-03, size: 384, ETA: 1:33:10
2025-09-01 08:54:50.788 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 279/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.140s, data_time: 0.038s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.537e-03, size: 512, ETA: 1:33:08
2025-09-01 08:54:52.077 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:54:52.180 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch280
2025-09-01 08:54:54.973 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 280/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.042s, total_loss: 4.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.8, lr: 2.530e-03, size: 320, ETA: 1:33:04
2025-09-01 08:54:57.774 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 280/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.6Gb, iter_time: 0.128s, data_time: 0.031s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.525e-03, size: 416, ETA: 1:33:01
2025-09-01 08:55:00.636 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 280/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.521e-03, size: 352, ETA: 1:32:59
2025-09-01 08:55:03.517 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 280/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 8.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 1.0, lr: 2.516e-03, size: 512, ETA: 1:32:56
2025-09-01 08:55:06.379 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 280/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.061s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 2.511e-03, size: 320, ETA: 1:32:53
2025-09-01 08:55:09.201 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 280/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.135s, data_time: 0.050s, total_loss: 6.7, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.506e-03, size: 288, ETA: 1:32:51
2025-09-01 08:55:10.526 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:55:16.377 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:55:19.360 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:55:21.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5666
2025-09-01 08:55:22.032 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5463
2025-09-01 08:55:22.086 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3067
2025-09-01 08:55:22.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4732
2025-09-01 08:55:22.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:55:22.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:55:22.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.567
2025-09-01 08:55:22.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.546
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.307
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.473
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:55:22.088 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:55:22.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:55:24.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:55:27.306 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:55:29.975 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:55:32.568 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:55:35.160 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:55:37.792 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:55:40.419 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:55:43.005 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:55:45.604 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:55:45.604 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.24
2025-09-01 08:55:45.604 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-09-01 08:55:45.604 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:55:45.630 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.98 ms, Average inference time: 2.37 ms

2025-09-01 08:55:45.631 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:55:45.664 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:55:45.695 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch281
2025-09-01 08:55:48.206 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 281/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.125s, data_time: 0.024s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.499e-03, size: 416, ETA: 1:32:47
2025-09-01 08:55:51.062 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 281/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.495e-03, size: 384, ETA: 1:32:44
2025-09-01 08:55:54.015 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 281/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.147s, data_time: 0.066s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 2.490e-03, size: 576, ETA: 1:32:42
2025-09-01 08:55:56.914 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 281/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.144s, data_time: 0.064s, total_loss: 7.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.9, lr: 2.485e-03, size: 544, ETA: 1:32:39
2025-09-01 08:55:59.803 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 281/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.144s, data_time: 0.065s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 2.480e-03, size: 480, ETA: 1:32:37
2025-09-01 08:56:02.477 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 281/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.054s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 2.475e-03, size: 512, ETA: 1:32:34
2025-09-01 08:56:03.673 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:56:03.856 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch282
2025-09-01 08:56:06.805 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 282/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.140s, data_time: 0.009s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.469e-03, size: 416, ETA: 1:32:30
2025-09-01 08:56:09.699 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 282/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.006s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 2.464e-03, size: 288, ETA: 1:32:27
2025-09-01 08:56:12.752 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 282/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.146s, 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: 2.459e-03, size: 448, ETA: 1:32:25
2025-09-01 08:56:15.634 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 282/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.137s, 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: 2.454e-03, size: 512, ETA: 1:32:22
2025-09-01 08:56:18.472 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 282/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 2.450e-03, size: 320, ETA: 1:32:19
2025-09-01 08:56:21.332 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 282/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, data_time: 0.043s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 2.445e-03, size: 352, ETA: 1:32:17
2025-09-01 08:56:22.575 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:56:22.630 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch283
2025-09-01 08:56:25.479 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 283/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.141s, data_time: 0.053s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 2.438e-03, size: 288, ETA: 1:32:13
2025-09-01 08:56:28.291 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 283/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.061s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.433e-03, size: 544, ETA: 1:32:10
2025-09-01 08:56:31.167 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 283/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.429e-03, size: 352, ETA: 1:32:08
2025-09-01 08:56:33.959 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 283/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.136s, data_time: 0.047s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 2.424e-03, size: 384, ETA: 1:32:05
2025-09-01 08:56:36.812 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 283/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 2.419e-03, size: 384, ETA: 1:32:03
2025-09-01 08:56:39.624 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 283/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.047s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 2.414e-03, size: 544, ETA: 1:32:00
2025-09-01 08:56:40.890 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:56:41.083 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch284
2025-09-01 08:56:43.878 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 284/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.408e-03, size: 480, ETA: 1:31:56
2025-09-01 08:56:46.733 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 284/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.134s, data_time: 0.022s, total_loss: 6.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.403e-03, size: 448, ETA: 1:31:53
2025-09-01 08:56:49.530 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 284/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.045s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.398e-03, size: 576, ETA: 1:31:51
2025-09-01 08:56:52.301 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 284/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.135s, data_time: 0.059s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.394e-03, size: 544, ETA: 1:31:48
2025-09-01 08:56:55.180 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 284/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.137s, data_time: 0.032s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.389e-03, size: 320, ETA: 1:31:45
2025-09-01 08:56:58.113 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 284/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.137s, data_time: 0.006s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.384e-03, size: 320, ETA: 1:31:43
2025-09-01 08:56:59.366 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:56:59.467 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch285
2025-09-01 08:57:02.352 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 285/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.142s, 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: 2.378e-03, size: 544, ETA: 1:31:39
2025-09-01 08:57:05.244 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 285/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, 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: 2.373e-03, size: 384, ETA: 1:31:36
2025-09-01 08:57:08.009 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 285/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.134s, data_time: 0.011s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 2.368e-03, size: 416, ETA: 1:31:34
2025-09-01 08:57:10.831 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 285/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.137s, data_time: 0.043s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.364e-03, size: 384, ETA: 1:31:31
2025-09-01 08:57:13.658 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 285/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.137s, data_time: 0.044s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 2.359e-03, size: 384, ETA: 1:31:28
2025-09-01 08:57:16.478 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 285/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.053s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 2.354e-03, size: 384, ETA: 1:31:26
2025-09-01 08:57:17.705 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:57:23.537 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:57:25.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:57:26.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5948
2025-09-01 08:57:26.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5470
2025-09-01 08:57:26.617 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3614
2025-09-01 08:57:26.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5010
2025-09-01 08:57:26.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:57:26.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:57:26.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.595
2025-09-01 08:57:26.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.547
2025-09-01 08:57:26.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.361
2025-09-01 08:57:26.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.501
2025-09-01 08:57:26.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:57:26.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:57:26.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:57:26.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:57:26.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:57:26.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:57:26.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:57:26.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:57:26.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:57:28.100 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:57:29.591 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:57:31.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:57:32.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:57:34.031 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:57:35.394 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:57:36.791 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:57:38.268 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:57:39.652 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:57:39.652 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 08:57:39.652 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-09-01 08:57:39.652 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:57:39.662 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.94 ms, Average inference time: 2.29 ms

2025-09-01 08:57:39.665 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:57:39.688 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:57:39.722 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch286
2025-09-01 08:57:42.187 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 286/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.119s, data_time: 0.033s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 2.348e-03, size: 576, ETA: 1:31:22
2025-09-01 08:57:45.213 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 286/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.143s, data_time: 0.031s, total_loss: 5.6, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.343e-03, size: 480, ETA: 1:31:19
2025-09-01 08:57:47.928 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 286/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.130s, data_time: 0.039s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 2.338e-03, size: 288, ETA: 1:31:16
2025-09-01 08:57:50.775 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 286/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.134s, data_time: 0.034s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 2.334e-03, size: 416, ETA: 1:31:13
2025-09-01 08:57:53.597 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 286/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.135s, data_time: 0.048s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 2.329e-03, size: 256, ETA: 1:31:11
2025-09-01 08:57:56.331 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 286/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.032s, total_loss: 8.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.3, lr: 2.324e-03, size: 352, ETA: 1:31:08
2025-09-01 08:57:57.561 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:57:57.617 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch287
2025-09-01 08:58:00.385 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 287/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.128s, data_time: 0.039s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 2.318e-03, size: 320, ETA: 1:31:04
2025-09-01 08:58:03.174 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 287/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.136s, data_time: 0.031s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 2.313e-03, size: 576, ETA: 1:31:01
2025-09-01 08:58:05.988 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 287/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.135s, data_time: 0.041s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 2.308e-03, size: 448, ETA: 1:30:59
2025-09-01 08:58:08.922 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 287/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.049s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.304e-03, size: 256, ETA: 1:30:56
2025-09-01 08:58:11.563 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 287/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.128s, data_time: 0.035s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 2.299e-03, size: 480, ETA: 1:30:53
2025-09-01 08:58:14.406 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 287/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.053s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.295e-03, size: 384, ETA: 1:30:51
2025-09-01 08:58:15.695 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:58:15.732 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch288
2025-09-01 08:58:18.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 288/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.139s, data_time: 0.058s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.288e-03, size: 480, ETA: 1:30:47
2025-09-01 08:58:21.577 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 288/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.138s, data_time: 0.041s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 2.283e-03, size: 576, ETA: 1:30:44
2025-09-01 08:58:24.466 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 288/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.137s, data_time: 0.034s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.279e-03, size: 416, ETA: 1:30:41
2025-09-01 08:58:27.360 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 288/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, 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: 2.274e-03, size: 352, ETA: 1:30:39
2025-09-01 08:58:30.118 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 288/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.270e-03, size: 384, ETA: 1:30:36
2025-09-01 08:58:32.955 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 288/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.136s, 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: 2.265e-03, size: 416, ETA: 1:30:33
2025-09-01 08:58:34.134 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:58:34.204 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch289
2025-09-01 08:58:36.910 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 289/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.023s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 2.259e-03, size: 320, ETA: 1:30:29
2025-09-01 08:58:39.793 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 289/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.141s, data_time: 0.014s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 2.254e-03, size: 416, ETA: 1:30:27
2025-09-01 08:58:42.649 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 289/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.030s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.250e-03, size: 384, ETA: 1:30:24
2025-09-01 08:58:45.515 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 289/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.137s, data_time: 0.025s, total_loss: 5.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 2.245e-03, size: 544, ETA: 1:30:21
2025-09-01 08:58:48.238 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 289/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.019s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.2, lr: 2.240e-03, size: 288, ETA: 1:30:19
2025-09-01 08:58:51.074 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 289/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.141s, data_time: 0.057s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.236e-03, size: 352, ETA: 1:30:16
2025-09-01 08:58:52.334 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:58:52.375 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch290
2025-09-01 08:58:55.235 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 290/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.142s, data_time: 0.062s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 2.229e-03, size: 352, ETA: 1:30:12
2025-09-01 08:58:58.057 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 290/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.225e-03, size: 288, ETA: 1:30:10
2025-09-01 08:59:00.896 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 290/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 2.220e-03, size: 416, ETA: 1:30:07
2025-09-01 08:59:03.745 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 290/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.7, lr: 2.216e-03, size: 544, ETA: 1:30:05
2025-09-01 08:59:06.706 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 290/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.141s, data_time: 0.056s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 2.211e-03, size: 416, ETA: 1:30:02
2025-09-01 08:59:09.505 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 290/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.040s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.6, lr: 2.207e-03, size: 384, ETA: 1:29:59
2025-09-01 08:59:10.888 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:59:16.776 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 08:59:19.415 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 08:59:21.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5998
2025-09-01 08:59:21.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5587
2025-09-01 08:59:21.806 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3332
2025-09-01 08:59:21.808 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4973
2025-09-01 08:59:21.808 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 08:59:21.809 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 08:59:21.809 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.600
2025-09-01 08:59:21.810 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.559
2025-09-01 08:59:21.810 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.333
2025-09-01 08:59:21.811 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.497
2025-09-01 08:59:21.811 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 08:59:21.811 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 08:59:21.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 08:59:21.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 08:59:21.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 08:59:21.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 08:59:21.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 08:59:21.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 08:59:21.814 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 08:59:24.171 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 08:59:26.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 08:59:28.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 08:59:31.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 08:59:33.333 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 08:59:35.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 08:59:37.939 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 08:59:40.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 08:59:42.560 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 08:59:42.561 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-09-01 08:59:42.561 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-09-01 08:59:42.561 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 08:59:42.587 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.34 ms, Average NMS time: 0.96 ms, Average inference time: 2.30 ms

2025-09-01 08:59:42.588 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:59:42.615 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 08:59:42.646 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch291
2025-09-01 08:59:45.160 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 291/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.119s, data_time: 0.037s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 2.200e-03, size: 416, ETA: 1:29:55
2025-09-01 08:59:48.060 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 291/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.010s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 2.196e-03, size: 544, ETA: 1:29:52
2025-09-01 08:59:50.993 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 291/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 2.191e-03, size: 480, ETA: 1:29:49
2025-09-01 08:59:53.676 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 291/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.125s, data_time: 0.027s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 2.187e-03, size: 320, ETA: 1:29:47
2025-09-01 08:59:56.771 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 291/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.141s, data_time: 0.007s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.182e-03, size: 320, ETA: 1:29:44
2025-09-01 08:59:59.640 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 291/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, 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: 2.178e-03, size: 480, ETA: 1:29:41
2025-09-01 09:00:00.899 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:00:00.934 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch292
2025-09-01 09:00:03.825 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 292/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.007s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 2.171e-03, size: 448, ETA: 1:29:37
2025-09-01 09:00:06.571 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 292/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.124s, data_time: 0.032s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 2.167e-03, size: 448, ETA: 1:29:34
2025-09-01 09:00:09.364 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 292/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.124s, data_time: 0.026s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 2.163e-03, size: 544, ETA: 1:29:31
2025-09-01 09:00:12.359 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 292/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.038s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.9, lr: 2.158e-03, size: 288, ETA: 1:29:29
2025-09-01 09:00:15.341 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 292/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.136s, 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: 2.154e-03, size: 512, ETA: 1:29:26
2025-09-01 09:00:18.224 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 292/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.130s, 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: 2.149e-03, size: 544, ETA: 1:29:23
2025-09-01 09:00:19.344 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:00:19.470 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch293
2025-09-01 09:00:22.428 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 293/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.141s, data_time: 0.040s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 2.143e-03, size: 416, ETA: 1:29:19
2025-09-01 09:00:25.255 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 293/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.127s, data_time: 0.012s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 2.138e-03, size: 384, ETA: 1:29:16
2025-09-01 09:00:28.065 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 293/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.131s, data_time: 0.044s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 2.134e-03, size: 416, ETA: 1:29:14
2025-09-01 09:00:31.008 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 293/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.139s, data_time: 0.040s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.9, lr: 2.130e-03, size: 288, ETA: 1:29:11
2025-09-01 09:00:33.800 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 293/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.119s, 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: 2.125e-03, size: 448, ETA: 1:29:08
2025-09-01 09:00:36.812 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 293/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.7Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 2.121e-03, size: 288, ETA: 1:29:05
2025-09-01 09:00:38.055 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:00:38.091 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch294
2025-09-01 09:00:41.023 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 294/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, 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: 2.114e-03, size: 352, ETA: 1:29:01
2025-09-01 09:00:44.080 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 294/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.139s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 2.110e-03, size: 448, ETA: 1:28:58
2025-09-01 09:00:47.054 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 294/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, 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: 2.106e-03, size: 480, ETA: 1:28:56
2025-09-01 09:00:49.946 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 294/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.129s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 2.101e-03, size: 512, ETA: 1:28:53
2025-09-01 09:00:52.868 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 294/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 2.097e-03, size: 384, ETA: 1:28:50
2025-09-01 09:00:55.632 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 294/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 2.092e-03, size: 544, ETA: 1:28:47
2025-09-01 09:00:57.007 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:00:57.179 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch295
2025-09-01 09:00:59.922 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 295/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.125s, data_time: 0.028s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.086e-03, size: 512, ETA: 1:28:43
2025-09-01 09:01:02.736 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 295/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.053s, total_loss: 8.2, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 4.0, cls_loss: 0.8, lr: 2.082e-03, size: 320, ETA: 1:28:40
2025-09-01 09:01:05.591 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 295/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.126s, data_time: 0.029s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 2.077e-03, size: 544, ETA: 1:28:37
2025-09-01 09:01:08.534 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 295/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 2.073e-03, size: 448, ETA: 1:28:35
2025-09-01 09:01:11.356 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 295/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.122s, data_time: 0.005s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 2.069e-03, size: 352, ETA: 1:28:32
2025-09-01 09:01:14.244 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 295/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.124s, 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: 2.064e-03, size: 480, ETA: 1:28:29
2025-09-01 09:01:15.384 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:01:21.394 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:01:23.839 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:01:25.342 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5885
2025-09-01 09:01:25.531 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5671
2025-09-01 09:01:25.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3587
2025-09-01 09:01:25.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5048
2025-09-01 09:01:25.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:01:25.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:01:25.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.588
2025-09-01 09:01:25.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.567
2025-09-01 09:01:25.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.359
2025-09-01 09:01:25.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.505
2025-09-01 09:01:25.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:01:25.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:01:25.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:01:25.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:01:25.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:01:25.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:01:25.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:01:25.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:01:25.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:01:27.304 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:01:29.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:01:30.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:01:32.421 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:01:34.131 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:01:35.889 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:01:37.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:01:39.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:01:41.005 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:01:41.006 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 09:01:41.006 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-09-01 09:01:41.006 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:01:41.034 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.93 ms, Average inference time: 2.30 ms

2025-09-01 09:01:41.035 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:01:41.060 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:01:41.093 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch296
2025-09-01 09:01:43.444 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 296/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.113s, data_time: 0.032s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.058e-03, size: 256, ETA: 1:28:24
2025-09-01 09:01:46.270 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 296/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 2.054e-03, size: 544, ETA: 1:28:22
2025-09-01 09:01:49.064 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 296/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.051s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.0, lr: 2.049e-03, size: 576, ETA: 1:28:19
2025-09-01 09:01:51.896 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 296/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 2.045e-03, size: 352, ETA: 1:28:16
2025-09-01 09:01:54.807 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 296/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.145s, data_time: 0.066s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 2.041e-03, size: 288, ETA: 1:28:14
2025-09-01 09:01:57.591 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 296/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.051s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.3, lr: 2.036e-03, size: 256, ETA: 1:28:11
2025-09-01 09:01:58.886 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:01:59.047 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch297
2025-09-01 09:02:01.846 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 297/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.131s, data_time: 0.023s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 2.030e-03, size: 448, ETA: 1:28:07
2025-09-01 09:02:04.709 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 297/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.058s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 2.026e-03, size: 256, ETA: 1:28:04
2025-09-01 09:02:07.538 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 297/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.126s, data_time: 0.008s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.8, lr: 2.021e-03, size: 416, ETA: 1:28:02
2025-09-01 09:02:10.444 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 297/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.125s, data_time: 0.010s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 2.017e-03, size: 416, ETA: 1:27:59
2025-09-01 09:02:13.351 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 297/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.006s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 2.013e-03, size: 320, ETA: 1:27:56
2025-09-01 09:02:16.212 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 297/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.128s, data_time: 0.006s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 2.009e-03, size: 352, ETA: 1:27:53
2025-09-01 09:02:17.478 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:02:17.514 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch298
2025-09-01 09:02:20.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 298/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 2.002e-03, size: 448, ETA: 1:27:49
2025-09-01 09:02:23.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 298/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.125s, data_time: 0.011s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.998e-03, size: 288, ETA: 1:27:46
2025-09-01 09:02:25.890 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 298/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.135s, data_time: 0.037s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 1.994e-03, size: 384, ETA: 1:27:43
2025-09-01 09:02:28.750 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 298/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.025s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.990e-03, size: 448, ETA: 1:27:41
2025-09-01 09:02:31.514 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 298/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.985e-03, size: 576, ETA: 1:27:38
2025-09-01 09:02:34.357 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 298/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.009s, total_loss: 8.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 1.0, lr: 1.981e-03, size: 416, ETA: 1:27:35
2025-09-01 09:02:35.548 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:02:35.609 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch299
2025-09-01 09:02:38.485 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 299/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.130s, data_time: 0.047s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 1.975e-03, size: 416, ETA: 1:27:31
2025-09-01 09:02:41.385 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 299/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.971e-03, size: 480, ETA: 1:27:28
2025-09-01 09:02:44.169 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 299/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.128s, data_time: 0.031s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.6, lr: 1.966e-03, size: 448, ETA: 1:27:25
2025-09-01 09:02:47.037 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 299/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.127s, data_time: 0.004s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 1.0, lr: 1.962e-03, size: 320, ETA: 1:27:22
2025-09-01 09:02:50.010 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 299/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.124s, data_time: 0.012s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 1.958e-03, size: 416, ETA: 1:27:19
2025-09-01 09:02:52.851 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 299/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.123s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.954e-03, size: 288, ETA: 1:27:16
2025-09-01 09:02:54.067 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:02:54.104 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch300
2025-09-01 09:02:56.825 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 300/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.123s, data_time: 0.009s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 1.948e-03, size: 544, ETA: 1:27:12
2025-09-01 09:02:59.675 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 300/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.142s, data_time: 0.054s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 1.943e-03, size: 256, ETA: 1:27:09
2025-09-01 09:03:02.412 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 300/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.131s, data_time: 0.047s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.939e-03, size: 384, ETA: 1:27:07
2025-09-01 09:03:05.260 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 300/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.935e-03, size: 512, ETA: 1:27:04
2025-09-01 09:03:07.970 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 300/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 7.0, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.931e-03, size: 576, ETA: 1:27:01
2025-09-01 09:03:10.719 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 300/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.029s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.927e-03, size: 320, ETA: 1:26:58
2025-09-01 09:03:12.069 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:03:17.954 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:03:21.069 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:03:23.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5938
2025-09-01 09:03:23.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5547
2025-09-01 09:03:23.671 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3528
2025-09-01 09:03:23.672 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5004
2025-09-01 09:03:23.672 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.594
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.555
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.353
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.500
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:03:23.673 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:03:23.674 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:03:23.674 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:03:23.674 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:03:26.192 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:03:28.748 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:03:31.336 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:03:33.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:03:36.473 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:03:39.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:03:41.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:03:44.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:03:46.697 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:03:46.697 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 09:03:46.697 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-09-01 09:03:46.698 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:03:46.724 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.97 ms, Average inference time: 2.34 ms

2025-09-01 09:03:46.725 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:03:46.751 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:03:46.784 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch301
2025-09-01 09:03:49.317 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 301/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.126s, data_time: 0.049s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.921e-03, size: 320, ETA: 1:26:54
2025-09-01 09:03:52.128 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 301/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.139s, data_time: 0.047s, total_loss: 5.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 1.916e-03, size: 544, ETA: 1:26:51
2025-09-01 09:03:54.958 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 301/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.139s, data_time: 0.011s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.912e-03, size: 416, ETA: 1:26:49
2025-09-01 09:03:57.707 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 301/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.135s, data_time: 0.010s, total_loss: 6.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.908e-03, size: 288, ETA: 1:26:46
2025-09-01 09:04:00.498 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 301/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.137s, data_time: 0.041s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.904e-03, size: 544, ETA: 1:26:44
2025-09-01 09:04:03.409 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 301/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.145s, data_time: 0.064s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.900e-03, size: 352, ETA: 1:26:41
2025-09-01 09:04:04.612 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:04:04.654 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch302
2025-09-01 09:04:07.471 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 302/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 1.894e-03, size: 544, ETA: 1:26:37
2025-09-01 09:04:10.307 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 302/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.134s, data_time: 0.021s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.890e-03, size: 448, ETA: 1:26:34
2025-09-01 09:04:13.046 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 302/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.886e-03, size: 320, ETA: 1:26:32
2025-09-01 09:04:15.929 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 302/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.041s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.881e-03, size: 288, ETA: 1:26:29
2025-09-01 09:04:18.869 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 302/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.139s, data_time: 0.039s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.877e-03, size: 544, ETA: 1:26:26
2025-09-01 09:04:21.685 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 302/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.135s, data_time: 0.011s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.873e-03, size: 288, ETA: 1:26:24
2025-09-01 09:04:22.910 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:04:22.948 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch303
2025-09-01 09:04:25.690 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 303/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.022s, total_loss: 7.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.4, lr: 1.867e-03, size: 544, ETA: 1:26:20
2025-09-01 09:04:28.617 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 303/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.144s, data_time: 0.005s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.863e-03, size: 544, ETA: 1:26:17
2025-09-01 09:04:31.400 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 303/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.134s, data_time: 0.011s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.859e-03, size: 384, ETA: 1:26:14
2025-09-01 09:04:34.268 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 303/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 4.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.6, lr: 1.855e-03, size: 320, ETA: 1:26:12
2025-09-01 09:04:37.100 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 303/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 1.851e-03, size: 416, ETA: 1:26:09
2025-09-01 09:04:39.980 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 303/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.049s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.847e-03, size: 544, ETA: 1:26:07
2025-09-01 09:04:41.190 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:04:41.299 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch304
2025-09-01 09:04:44.020 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 304/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.132s, data_time: 0.038s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.841e-03, size: 384, ETA: 1:26:03
2025-09-01 09:04:46.819 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 304/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.052s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 1.837e-03, size: 384, ETA: 1:26:00
2025-09-01 09:04:49.631 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 304/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.061s, total_loss: 7.3, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 1.833e-03, size: 256, ETA: 1:25:57
2025-09-01 09:04:52.520 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 304/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.137s, data_time: 0.053s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.829e-03, size: 416, ETA: 1:25:55
2025-09-01 09:04:55.423 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 304/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.136s, data_time: 0.010s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.824e-03, size: 320, ETA: 1:25:52
2025-09-01 09:04:58.208 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 304/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.130s, data_time: 0.009s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.9, lr: 1.820e-03, size: 512, ETA: 1:25:49
2025-09-01 09:04:59.393 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:04:59.453 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch305
2025-09-01 09:05:02.161 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 305/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.134s, data_time: 0.046s, total_loss: 4.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.6, lr: 1.815e-03, size: 416, ETA: 1:25:45
2025-09-01 09:05:04.989 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 305/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, data_time: 0.054s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.811e-03, size: 352, ETA: 1:25:43
2025-09-01 09:05:07.670 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 305/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.045s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.806e-03, size: 480, ETA: 1:25:40
2025-09-01 09:05:10.589 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 305/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.143s, data_time: 0.025s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.802e-03, size: 320, ETA: 1:25:37
2025-09-01 09:05:13.396 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 305/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.136s, data_time: 0.026s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.798e-03, size: 480, ETA: 1:25:35
2025-09-01 09:05:16.274 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 305/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.143s, data_time: 0.061s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.794e-03, size: 512, ETA: 1:25:32
2025-09-01 09:05:17.497 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:05:23.358 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:05:25.113 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:05:26.188 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5761
2025-09-01 09:05:26.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5314
2025-09-01 09:05:26.498 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3440
2025-09-01 09:05:26.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4838
2025-09-01 09:05:26.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:05:26.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:05:26.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.576
2025-09-01 09:05:26.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.531
2025-09-01 09:05:26.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.344
2025-09-01 09:05:26.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.484
2025-09-01 09:05:26.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:05:26.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:05:26.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:05:26.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:05:26.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:05:26.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:05:26.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:05:26.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:05:26.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:05:27.864 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:05:29.347 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:05:30.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:05:32.110 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:05:33.527 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:05:34.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:05:36.317 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:05:37.745 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:05:39.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:05:39.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-09-01 09:05:39.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-09-01 09:05:39.130 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:05:39.141 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.41 ms, Average NMS time: 0.95 ms, Average inference time: 2.36 ms

2025-09-01 09:05:39.142 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:05:39.172 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:05:39.204 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch306
2025-09-01 09:05:41.682 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 306/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.123s, data_time: 0.042s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.789e-03, size: 480, ETA: 1:25:28
2025-09-01 09:05:44.543 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 306/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.785e-03, size: 320, ETA: 1:25:25
2025-09-01 09:05:47.365 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 306/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.130s, data_time: 0.050s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.781e-03, size: 512, ETA: 1:25:22
2025-09-01 09:05:50.240 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 306/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.132s, data_time: 0.012s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.777e-03, size: 288, ETA: 1:25:20
2025-09-01 09:05:53.121 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 306/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.129s, data_time: 0.009s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.9, lr: 1.773e-03, size: 320, ETA: 1:25:17
2025-09-01 09:05:55.926 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 306/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.127s, data_time: 0.008s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.0, lr: 1.769e-03, size: 512, ETA: 1:25:14
2025-09-01 09:05:57.187 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:05:57.260 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch307
2025-09-01 09:06:00.043 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 307/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.134s, data_time: 0.058s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.1, lr: 1.763e-03, size: 256, ETA: 1:25:10
2025-09-01 09:06:02.925 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 307/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.142s, data_time: 0.056s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.759e-03, size: 480, ETA: 1:25:08
2025-09-01 09:06:05.805 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 307/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.045s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.755e-03, size: 512, ETA: 1:25:05
2025-09-01 09:06:08.595 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 307/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.123s, data_time: 0.016s, total_loss: 6.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 1.751e-03, size: 320, ETA: 1:25:02
2025-09-01 09:06:11.428 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 307/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.122s, data_time: 0.011s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.747e-03, size: 352, ETA: 1:24:59
2025-09-01 09:06:14.382 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 307/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.127s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.743e-03, size: 352, ETA: 1:24:56
2025-09-01 09:06:15.605 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:06:15.660 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch308
2025-09-01 09:06:18.438 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 308/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.132s, data_time: 0.023s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.737e-03, size: 480, ETA: 1:24:52
2025-09-01 09:06:21.310 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 308/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.733e-03, size: 576, ETA: 1:24:49
2025-09-01 09:06:24.168 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 308/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.062s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.729e-03, size: 288, ETA: 1:24:47
2025-09-01 09:06:27.055 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 308/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.025s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.725e-03, size: 352, ETA: 1:24:44
2025-09-01 09:06:29.987 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 308/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.005s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.722e-03, size: 448, ETA: 1:24:42
2025-09-01 09:06:32.790 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 308/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.124s, data_time: 0.013s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.718e-03, size: 384, ETA: 1:24:39
2025-09-01 09:06:34.067 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:06:34.287 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch309
2025-09-01 09:06:37.056 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 309/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.124s, data_time: 0.044s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 1.712e-03, size: 352, ETA: 1:24:34
2025-09-01 09:06:39.857 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 309/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.126s, data_time: 0.047s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 1.708e-03, size: 384, ETA: 1:24:32
2025-09-01 09:06:42.696 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 309/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.128s, data_time: 0.015s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.704e-03, size: 352, ETA: 1:24:29
2025-09-01 09:06:45.471 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 309/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.031s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 1.700e-03, size: 288, ETA: 1:24:26
2025-09-01 09:06:48.292 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 309/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.058s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.696e-03, size: 320, ETA: 1:24:23
2025-09-01 09:06:51.180 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 309/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.142s, data_time: 0.045s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.692e-03, size: 384, ETA: 1:24:21
2025-09-01 09:06:52.318 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:06:52.496 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch310
2025-09-01 09:06:55.323 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 310/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.051s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 1.687e-03, size: 352, ETA: 1:24:17
2025-09-01 09:06:58.295 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 310/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.139s, data_time: 0.019s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.683e-03, size: 416, ETA: 1:24:14
2025-09-01 09:07:01.073 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 310/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.135s, data_time: 0.007s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.679e-03, size: 544, ETA: 1:24:11
2025-09-01 09:07:03.877 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 310/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.1, lr: 1.675e-03, size: 352, ETA: 1:24:09
2025-09-01 09:07:06.746 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 310/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.142s, data_time: 0.058s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 1.671e-03, size: 288, ETA: 1:24:06
2025-09-01 09:07:09.490 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 310/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.133s, data_time: 0.050s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 1.1, lr: 1.668e-03, size: 512, ETA: 1:24:04
2025-09-01 09:07:10.721 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:07:16.598 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:07:17.955 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:07:18.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5888
2025-09-01 09:07:19.057 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5534
2025-09-01 09:07:19.107 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3420
2025-09-01 09:07:19.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4947
2025-09-01 09:07:19.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:07:19.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:07:19.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.589
2025-09-01 09:07:19.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.553
2025-09-01 09:07:19.108 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.342
2025-09-01 09:07:19.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.495
2025-09-01 09:07:19.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:07:19.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:07:19.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:07:19.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:07:19.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:07:19.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:07:19.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:07:19.109 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:07:19.110 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:07:20.234 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:07:21.504 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:07:22.597 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:07:23.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:07:24.795 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:07:25.915 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:07:27.003 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:07:28.102 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:07:29.192 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:07:29.193 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-09-01 09:07:29.193 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-09-01 09:07:29.193 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:07:29.201 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.93 ms, Average inference time: 2.28 ms

2025-09-01 09:07:29.202 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:07:29.227 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:07:29.258 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch311
2025-09-01 09:07:31.662 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 311/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.117s, data_time: 0.032s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.662e-03, size: 288, ETA: 1:23:59
2025-09-01 09:07:34.538 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 311/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.658e-03, size: 480, ETA: 1:23:57
2025-09-01 09:07:37.329 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 311/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.134s, data_time: 0.046s, total_loss: 7.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 1.654e-03, size: 512, ETA: 1:23:54
2025-09-01 09:07:40.172 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 311/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.650e-03, size: 448, ETA: 1:23:51
2025-09-01 09:07:42.989 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 311/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 1.647e-03, size: 288, ETA: 1:23:49
2025-09-01 09:07:45.842 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 311/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.643e-03, size: 320, ETA: 1:23:46
2025-09-01 09:07:47.008 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:07:47.171 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch312
2025-09-01 09:07:50.088 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 312/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.067s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.637e-03, size: 288, ETA: 1:23:42
2025-09-01 09:07:52.836 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 312/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.055s, total_loss: 5.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 1.634e-03, size: 352, ETA: 1:23:40
2025-09-01 09:07:55.829 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 312/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.148s, data_time: 0.067s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 1.630e-03, size: 320, ETA: 1:23:37
2025-09-01 09:07:58.704 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 312/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.143s, data_time: 0.062s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.626e-03, size: 256, ETA: 1:23:35
2025-09-01 09:08:01.523 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 312/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.138s, data_time: 0.058s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.622e-03, size: 256, ETA: 1:23:32
2025-09-01 09:08:04.395 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 312/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.139s, data_time: 0.054s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.618e-03, size: 384, ETA: 1:23:29
2025-09-01 09:08:05.695 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:08:05.737 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch313
2025-09-01 09:08:08.708 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 313/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.148s, data_time: 0.065s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.613e-03, size: 480, ETA: 1:23:26
2025-09-01 09:08:11.590 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 313/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.143s, data_time: 0.062s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.2, lr: 1.609e-03, size: 384, ETA: 1:23:23
2025-09-01 09:08:14.397 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 313/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.605e-03, size: 512, ETA: 1:23:21
2025-09-01 09:08:17.177 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 313/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.132s, data_time: 0.047s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 1.602e-03, size: 448, ETA: 1:23:18
2025-09-01 09:08:20.097 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 313/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.145s, data_time: 0.063s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.598e-03, size: 352, ETA: 1:23:15
2025-09-01 09:08:23.003 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 313/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.145s, data_time: 0.064s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 1.594e-03, size: 416, ETA: 1:23:13
2025-09-01 09:08:24.247 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:08:24.343 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch314
2025-09-01 09:08:27.225 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 314/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.139s, data_time: 0.041s, total_loss: 5.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 1.589e-03, size: 448, ETA: 1:23:09
2025-09-01 09:08:30.051 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 314/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.131s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.585e-03, size: 576, ETA: 1:23:06
2025-09-01 09:08:32.929 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 314/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, 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: 1.581e-03, size: 480, ETA: 1:23:04
2025-09-01 09:08:35.713 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 314/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.136s, data_time: 0.048s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.578e-03, size: 384, ETA: 1:23:01
2025-09-01 09:08:38.491 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 314/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.574e-03, size: 288, ETA: 1:22:58
2025-09-01 09:08:41.286 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 314/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.060s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 1.1, lr: 1.570e-03, size: 352, ETA: 1:22:56
2025-09-01 09:08:42.573 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:08:42.610 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch315
2025-09-01 09:08:45.359 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 315/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.131s, data_time: 0.049s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 1.565e-03, size: 320, ETA: 1:22:52
2025-09-01 09:08:48.272 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 315/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.011s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.561e-03, size: 256, ETA: 1:22:49
2025-09-01 09:08:51.026 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 315/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.131s, data_time: 0.014s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.557e-03, size: 256, ETA: 1:22:46
2025-09-01 09:08:53.974 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 315/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.146s, data_time: 0.022s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.554e-03, size: 352, ETA: 1:22:44
2025-09-01 09:08:56.916 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 315/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.8Gb, iter_time: 0.144s, data_time: 0.026s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.550e-03, size: 384, ETA: 1:22:41
2025-09-01 09:08:59.784 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 315/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.546e-03, size: 448, ETA: 1:22:38
2025-09-01 09:09:01.080 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:09:07.088 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:09:09.634 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:09:11.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5823
2025-09-01 09:09:11.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5484
2025-09-01 09:09:11.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3218
2025-09-01 09:09:11.964 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4842
2025-09-01 09:09:11.964 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:09:11.964 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.582
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.548
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.322
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.484
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:09:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:09:11.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:09:14.096 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:09:16.191 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:09:18.293 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:09:20.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:09:22.486 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:09:24.568 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:09:26.634 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:09:28.738 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:09:30.843 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:09:30.844 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-09-01 09:09:30.844 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-09-01 09:09:30.844 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:09:30.869 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.96 ms, Average inference time: 2.34 ms

2025-09-01 09:09:30.871 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:09:30.901 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:09:30.931 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch316
2025-09-01 09:09:33.311 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 316/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.114s, data_time: 0.033s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.541e-03, size: 384, ETA: 1:22:34
2025-09-01 09:09:36.240 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 316/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.133s, data_time: 0.040s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 1.537e-03, size: 480, ETA: 1:22:31
2025-09-01 09:09:39.023 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 316/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.123s, data_time: 0.017s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.534e-03, size: 256, ETA: 1:22:29
2025-09-01 09:09:42.094 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 316/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.010s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.530e-03, size: 384, ETA: 1:22:26
2025-09-01 09:09:44.870 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 316/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.125s, data_time: 0.005s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.526e-03, size: 480, ETA: 1:22:23
2025-09-01 09:09:47.775 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 316/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.133s, data_time: 0.005s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 1.523e-03, size: 288, ETA: 1:22:20
2025-09-01 09:09:49.032 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:09:49.169 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch317
2025-09-01 09:09:51.890 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 317/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.131s, data_time: 0.044s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.518e-03, size: 544, ETA: 1:22:16
2025-09-01 09:09:54.682 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 317/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.139s, data_time: 0.052s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.514e-03, size: 288, ETA: 1:22:14
2025-09-01 09:09:57.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 317/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.148s, data_time: 0.068s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 1.510e-03, size: 352, ETA: 1:22:11
2025-09-01 09:10:00.419 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 317/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.507e-03, size: 416, ETA: 1:22:09
2025-09-01 09:10:03.263 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 317/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.503e-03, size: 256, ETA: 1:22:06
2025-09-01 09:10:05.956 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 317/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.133s, data_time: 0.050s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 1.500e-03, size: 352, ETA: 1:22:03
2025-09-01 09:10:07.252 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:10:07.307 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch318
2025-09-01 09:10:10.157 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 318/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.139s, data_time: 0.052s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 1.494e-03, size: 416, ETA: 1:21:59
2025-09-01 09:10:12.993 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 318/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.029s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.491e-03, size: 384, ETA: 1:21:57
2025-09-01 09:10:15.960 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 318/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.487e-03, size: 384, ETA: 1:21:54
2025-09-01 09:10:18.829 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 318/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.044s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.484e-03, size: 384, ETA: 1:21:51
2025-09-01 09:10:21.600 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 318/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.134s, data_time: 0.047s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.480e-03, size: 320, ETA: 1:21:49
2025-09-01 09:10:24.512 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 318/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.139s, data_time: 0.032s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.6, lr: 1.476e-03, size: 416, ETA: 1:21:46
2025-09-01 09:10:25.678 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:10:25.715 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch319
2025-09-01 09:10:28.612 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 319/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.144s, data_time: 0.001s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 1.471e-03, size: 320, ETA: 1:21:42
2025-09-01 09:10:31.582 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 319/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.145s, data_time: 0.010s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.468e-03, size: 384, ETA: 1:21:40
2025-09-01 09:10:34.476 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 319/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.464e-03, size: 320, ETA: 1:21:37
2025-09-01 09:10:37.414 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 319/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.130s, data_time: 0.034s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.461e-03, size: 416, ETA: 1:21:34
2025-09-01 09:10:40.281 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 319/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, data_time: 0.020s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.457e-03, size: 288, ETA: 1:21:32
2025-09-01 09:10:43.182 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 319/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.143s, 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: 1.454e-03, size: 448, ETA: 1:21:29
2025-09-01 09:10:44.353 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:10:44.487 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch320
2025-09-01 09:10:47.246 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 320/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.045s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 1.449e-03, size: 352, ETA: 1:21:25
2025-09-01 09:10:50.083 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 320/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.032s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.445e-03, size: 256, ETA: 1:21:23
2025-09-01 09:10:53.011 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 320/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.139s, 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: 1.442e-03, size: 352, ETA: 1:21:20
2025-09-01 09:10:55.868 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 320/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.438e-03, size: 448, ETA: 1:21:17
2025-09-01 09:10:58.669 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 320/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.132s, data_time: 0.011s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.435e-03, size: 576, ETA: 1:21:15
2025-09-01 09:11:01.550 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 320/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.015s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.431e-03, size: 320, ETA: 1:21:12
2025-09-01 09:11:02.722 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:11:08.546 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:11:11.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:11:14.492 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6047
2025-09-01 09:11:14.908 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5705
2025-09-01 09:11:14.957 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3519
2025-09-01 09:11:14.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5090
2025-09-01 09:11:14.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:11:14.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:11:14.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.605
2025-09-01 09:11:14.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.570
2025-09-01 09:11:14.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.352
2025-09-01 09:11:14.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.509
2025-09-01 09:11:14.958 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:11:14.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:11:14.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:11:14.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:11:14.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:11:14.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:11:14.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:11:14.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:11:14.959 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:11:17.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:11:21.072 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:11:24.227 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:11:27.153 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:11:30.074 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:11:32.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:11:36.193 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:11:39.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:11:42.175 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:11:42.175 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:11:42.175 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 09:11:42.175 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:11:42.200 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.96 ms, Average inference time: 2.33 ms

2025-09-01 09:11:42.205 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:11:42.233 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:11:42.263 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch321
2025-09-01 09:11:44.737 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 321/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.123s, data_time: 0.039s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.426e-03, size: 448, ETA: 1:21:08
2025-09-01 09:11:47.595 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 321/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.142s, data_time: 0.071s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.423e-03, size: 320, ETA: 1:21:05
2025-09-01 09:11:50.428 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 321/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, data_time: 0.042s, total_loss: 7.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.419e-03, size: 256, ETA: 1:21:03
2025-09-01 09:11:53.318 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 321/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.143s, data_time: 0.059s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.416e-03, size: 512, ETA: 1:21:00
2025-09-01 09:11:56.038 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 321/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.049s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.412e-03, size: 352, ETA: 1:20:57
2025-09-01 09:11:58.897 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 321/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.139s, data_time: 0.024s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.409e-03, size: 416, ETA: 1:20:55
2025-09-01 09:12:00.188 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:12:00.225 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch322
2025-09-01 09:12:03.114 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 322/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.131s, data_time: 0.030s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.404e-03, size: 288, ETA: 1:20:51
2025-09-01 09:12:05.853 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 322/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.124s, data_time: 0.014s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.3, lr: 1.400e-03, size: 544, ETA: 1:20:48
2025-09-01 09:12:08.759 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 322/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.051s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.397e-03, size: 384, ETA: 1:20:45
2025-09-01 09:12:11.594 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 322/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.141s, data_time: 0.062s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 1.0, lr: 1.393e-03, size: 288, ETA: 1:20:43
2025-09-01 09:12:14.484 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 322/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.144s, data_time: 0.065s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.390e-03, size: 384, ETA: 1:20:40
2025-09-01 09:12:17.342 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 322/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.387e-03, size: 544, ETA: 1:20:38
2025-09-01 09:12:18.505 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:12:18.542 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch323
2025-09-01 09:12:21.410 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 323/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.143s, data_time: 0.062s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.6, lr: 1.382e-03, size: 448, ETA: 1:20:34
2025-09-01 09:12:24.189 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 323/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, data_time: 0.060s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.378e-03, size: 352, ETA: 1:20:31
2025-09-01 09:12:27.193 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 323/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.375e-03, size: 448, ETA: 1:20:28
2025-09-01 09:12:29.966 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 323/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.052s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.372e-03, size: 512, ETA: 1:20:26
2025-09-01 09:12:32.769 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 323/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.368e-03, size: 384, ETA: 1:20:23
2025-09-01 09:12:35.491 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 323/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.134s, data_time: 0.055s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.365e-03, size: 576, ETA: 1:20:20
2025-09-01 09:12:36.865 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:12:36.902 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch324
2025-09-01 09:12:39.538 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 324/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.130s, data_time: 0.048s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.360e-03, size: 320, ETA: 1:20:16
2025-09-01 09:12:42.436 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 324/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.143s, data_time: 0.066s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.357e-03, size: 416, ETA: 1:20:14
2025-09-01 09:12:45.345 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 324/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.145s, data_time: 0.066s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.1, lr: 1.353e-03, size: 544, ETA: 1:20:11
2025-09-01 09:12:48.043 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 324/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.035s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.350e-03, size: 544, ETA: 1:20:09
2025-09-01 09:12:50.922 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 324/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.346e-03, size: 416, ETA: 1:20:06
2025-09-01 09:12:53.650 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 324/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.130s, data_time: 0.046s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 1.343e-03, size: 544, ETA: 1:20:03
2025-09-01 09:12:54.939 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:12:54.978 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch325
2025-09-01 09:12:57.812 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 325/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.338e-03, size: 416, ETA: 1:19:59
2025-09-01 09:13:00.749 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 325/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.141s, data_time: 0.014s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.335e-03, size: 480, ETA: 1:19:57
2025-09-01 09:13:03.571 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 325/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.022s, total_loss: 5.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.332e-03, size: 512, ETA: 1:19:54
2025-09-01 09:13:06.432 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 325/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.135s, data_time: 0.057s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.328e-03, size: 544, ETA: 1:19:51
2025-09-01 09:13:09.362 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 325/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.006s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 1.325e-03, size: 480, ETA: 1:19:48
2025-09-01 09:13:12.246 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 325/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 1.322e-03, size: 352, ETA: 1:19:46
2025-09-01 09:13:13.308 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:13:19.121 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:13:21.158 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:13:22.536 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5964
2025-09-01 09:13:22.772 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5637
2025-09-01 09:13:22.830 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3824
2025-09-01 09:13:22.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5142
2025-09-01 09:13:22.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:13:22.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:13:22.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.596
2025-09-01 09:13:22.831 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.382
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.514
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:13:22.832 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:13:24.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:13:26.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:13:28.094 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:13:29.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:13:31.462 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:13:33.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:13:34.818 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:13:36.483 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:13:38.169 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:13:38.170 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 09:13:38.170 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 09:13:38.170 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:13:38.197 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.95 ms, Average inference time: 2.30 ms

2025-09-01 09:13:38.199 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:13:38.229 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:13:38.261 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch326
2025-09-01 09:13:40.832 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 326/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.126s, data_time: 0.046s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.1, lr: 1.317e-03, size: 576, ETA: 1:19:41
2025-09-01 09:13:43.599 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 326/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.136s, data_time: 0.055s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 1.314e-03, size: 416, ETA: 1:19:39
2025-09-01 09:13:46.477 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 326/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.143s, data_time: 0.065s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.5, lr: 1.310e-03, size: 352, ETA: 1:19:36
2025-09-01 09:13:49.299 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 326/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.063s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 1.307e-03, size: 352, ETA: 1:19:33
2025-09-01 09:13:52.115 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 326/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 1.304e-03, size: 288, ETA: 1:19:31
2025-09-01 09:13:55.073 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 326/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.142s, data_time: 0.069s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.301e-03, size: 384, ETA: 1:19:28
2025-09-01 09:13:56.227 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:13:56.272 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch327
2025-09-01 09:13:59.110 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 327/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.139s, data_time: 0.048s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.296e-03, size: 256, ETA: 1:19:24
2025-09-01 09:14:01.887 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 327/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.136s, data_time: 0.013s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.293e-03, size: 448, ETA: 1:19:22
2025-09-01 09:14:04.852 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 327/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.013s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.289e-03, size: 576, ETA: 1:19:19
2025-09-01 09:14:07.702 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 327/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.119s, data_time: 0.026s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.286e-03, size: 416, ETA: 1:19:16
2025-09-01 09:14:10.633 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 327/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.126s, data_time: 0.018s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.283e-03, size: 256, ETA: 1:19:13
2025-09-01 09:14:13.352 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 327/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.030s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.280e-03, size: 416, ETA: 1:19:10
2025-09-01 09:14:14.658 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:14:14.693 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch328
2025-09-01 09:14:17.494 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 328/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.133s, data_time: 0.037s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 1.275e-03, size: 480, ETA: 1:19:07
2025-09-01 09:14:20.371 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 328/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.272e-03, size: 512, ETA: 1:19:04
2025-09-01 09:14:23.237 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 328/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.269e-03, size: 352, ETA: 1:19:01
2025-09-01 09:14:26.064 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 328/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.127s, data_time: 0.020s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 1.266e-03, size: 416, ETA: 1:18:58
2025-09-01 09:14:28.965 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 328/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.142s, data_time: 0.045s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 1.262e-03, size: 576, ETA: 1:18:55
2025-09-01 09:14:31.882 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 328/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.145s, data_time: 0.060s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.259e-03, size: 544, ETA: 1:18:53
2025-09-01 09:14:33.187 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:14:33.216 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch329
2025-09-01 09:14:35.988 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 329/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.049s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.255e-03, size: 448, ETA: 1:18:49
2025-09-01 09:14:38.799 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 329/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 1.251e-03, size: 416, ETA: 1:18:46
2025-09-01 09:14:41.617 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 329/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.059s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.248e-03, size: 576, ETA: 1:18:44
2025-09-01 09:14:44.436 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 329/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.062s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.245e-03, size: 576, ETA: 1:18:41
2025-09-01 09:14:47.263 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 329/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.242e-03, size: 384, ETA: 1:18:39
2025-09-01 09:14:49.990 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 329/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.128s, data_time: 0.033s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.239e-03, size: 416, ETA: 1:18:36
2025-09-01 09:14:51.152 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:14:51.192 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch330
2025-09-01 09:14:54.062 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 330/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.129s, data_time: 0.045s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.5, lr: 1.234e-03, size: 512, ETA: 1:18:32
2025-09-01 09:14:56.908 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 330/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.136s, 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: 1.231e-03, size: 448, ETA: 1:18:29
2025-09-01 09:14:59.650 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 330/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.132s, data_time: 0.015s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.228e-03, size: 384, ETA: 1:18:26
2025-09-01 09:15:02.482 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 330/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.134s, data_time: 0.023s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.225e-03, size: 416, ETA: 1:18:24
2025-09-01 09:15:05.373 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 330/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, 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: 1.222e-03, size: 512, ETA: 1:18:21
2025-09-01 09:15:08.152 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 330/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.133s, data_time: 0.035s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.219e-03, size: 576, ETA: 1:18:18
2025-09-01 09:15:09.415 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:15:15.237 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:15:16.862 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:15:18.006 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5884
2025-09-01 09:15:18.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5729
2025-09-01 09:15:18.384 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3585
2025-09-01 09:15:18.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5066
2025-09-01 09:15:18.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:15:18.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:15:18.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.588
2025-09-01 09:15:18.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.573
2025-09-01 09:15:18.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.359
2025-09-01 09:15:18.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.507
2025-09-01 09:15:18.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:15:18.385 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:15:18.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:15:18.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:15:18.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:15:18.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:15:18.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:15:18.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:15:18.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:15:19.717 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:15:21.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:15:22.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:15:24.012 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:15:25.317 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:15:26.643 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:15:28.018 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:15:29.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:15:30.654 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:15:30.654 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-09-01 09:15:30.655 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 09:15:30.655 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:15:30.662 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.93 ms, Average inference time: 2.30 ms

2025-09-01 09:15:30.664 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:15:30.685 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:15:30.716 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch331
2025-09-01 09:15:33.197 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 331/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.120s, data_time: 0.029s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.214e-03, size: 448, ETA: 1:18:14
2025-09-01 09:15:36.069 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 331/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.211e-03, size: 384, ETA: 1:18:12
2025-09-01 09:15:38.851 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 331/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.208e-03, size: 352, ETA: 1:18:09
2025-09-01 09:15:41.713 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 331/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.205e-03, size: 256, ETA: 1:18:06
2025-09-01 09:15:44.483 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 331/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.132s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.202e-03, size: 544, ETA: 1:18:04
2025-09-01 09:15:47.189 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 331/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.132s, data_time: 0.026s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.199e-03, size: 256, ETA: 1:18:01
2025-09-01 09:15:48.429 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:15:48.568 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch332
2025-09-01 09:15:51.433 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 332/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 1.194e-03, size: 544, ETA: 1:17:57
2025-09-01 09:15:54.174 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 332/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.129s, data_time: 0.017s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.191e-03, size: 544, ETA: 1:17:54
2025-09-01 09:15:56.984 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 332/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.033s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 1.188e-03, size: 448, ETA: 1:17:51
2025-09-01 09:15:59.842 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 332/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.136s, data_time: 0.048s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.185e-03, size: 256, ETA: 1:17:49
2025-09-01 09:16:02.755 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 332/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.136s, data_time: 0.013s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.182e-03, size: 416, ETA: 1:17:46
2025-09-01 09:16:05.402 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 332/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.125s, data_time: 0.010s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.179e-03, size: 512, ETA: 1:17:43
2025-09-01 09:16:06.588 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:16:06.628 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch333
2025-09-01 09:16:09.572 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 333/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.142s, data_time: 0.021s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.175e-03, size: 512, ETA: 1:17:39
2025-09-01 09:16:12.446 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 333/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.025s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 1.172e-03, size: 256, ETA: 1:17:37
2025-09-01 09:16:15.233 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 333/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.131s, data_time: 0.024s, total_loss: 4.6, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.7, lr: 1.169e-03, size: 512, ETA: 1:17:34
2025-09-01 09:16:18.022 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 333/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.023s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.166e-03, size: 544, ETA: 1:17:31
2025-09-01 09:16:20.854 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 333/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.132s, data_time: 0.030s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.163e-03, size: 480, ETA: 1:17:28
2025-09-01 09:16:23.793 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 333/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.160e-03, size: 512, ETA: 1:17:25
2025-09-01 09:16:24.984 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:16:25.031 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch334
2025-09-01 09:16:27.938 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 334/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.022s, total_loss: 7.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 1.156e-03, size: 448, ETA: 1:17:22
2025-09-01 09:16:30.720 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 334/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, data_time: 0.045s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.153e-03, size: 256, ETA: 1:17:19
2025-09-01 09:16:33.478 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 334/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.132s, data_time: 0.032s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.8, lr: 1.150e-03, size: 544, ETA: 1:17:16
2025-09-01 09:16:36.235 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 334/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.130s, data_time: 0.046s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 1.147e-03, size: 576, ETA: 1:17:13
2025-09-01 09:16:39.160 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 334/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.063s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 1.144e-03, size: 576, ETA: 1:17:11
2025-09-01 09:16:42.006 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 334/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.141e-03, size: 544, ETA: 1:17:08
2025-09-01 09:16:43.308 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:16:43.372 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch335
2025-09-01 09:16:46.214 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 335/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.137e-03, size: 416, ETA: 1:17:04
2025-09-01 09:16:49.050 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 335/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.141s, data_time: 0.063s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.134e-03, size: 512, ETA: 1:17:02
2025-09-01 09:16:51.868 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 335/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.131e-03, size: 544, ETA: 1:16:59
2025-09-01 09:16:54.699 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 335/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.138s, data_time: 0.062s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.128e-03, size: 576, ETA: 1:16:57
2025-09-01 09:16:57.531 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 335/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.125e-03, size: 384, ETA: 1:16:54
2025-09-01 09:17:00.391 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 335/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.122e-03, size: 288, ETA: 1:16:51
2025-09-01 09:17:01.706 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:17:07.665 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:17:10.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:17:12.352 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6086
2025-09-01 09:17:12.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5605
2025-09-01 09:17:12.762 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3594
2025-09-01 09:17:12.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5095
2025-09-01 09:17:12.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:17:12.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:17:12.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.609
2025-09-01 09:17:12.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.561
2025-09-01 09:17:12.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.359
2025-09-01 09:17:12.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.510
2025-09-01 09:17:12.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:17:12.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:17:12.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:17:12.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:17:12.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:17:12.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:17:12.764 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:17:12.765 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:17:12.765 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:17:15.097 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:17:17.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:17:19.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:17:21.873 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:17:24.134 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:17:26.351 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:17:28.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:17:30.905 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:17:33.250 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:17:33.251 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:17:33.251 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 09:17:33.251 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:17:33.277 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.93 ms, Average inference time: 2.31 ms

2025-09-01 09:17:33.278 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:17:33.357 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:17:33.390 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch336
2025-09-01 09:17:35.868 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 336/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.120s, data_time: 0.033s, total_loss: 7.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 1.118e-03, size: 480, ETA: 1:16:47
2025-09-01 09:17:38.907 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 336/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.139s, data_time: 0.014s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 1.115e-03, size: 384, ETA: 1:16:45
2025-09-01 09:17:41.858 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 336/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 6.5, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 1.112e-03, size: 288, ETA: 1:16:42
2025-09-01 09:17:44.638 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 336/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.126s, data_time: 0.023s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 1.109e-03, size: 384, ETA: 1:16:39
2025-09-01 09:17:47.624 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 336/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.132s, data_time: 0.011s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.106e-03, size: 512, ETA: 1:16:36
2025-09-01 09:17:50.345 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 336/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.126s, data_time: 0.014s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.9, lr: 1.103e-03, size: 576, ETA: 1:16:33
2025-09-01 09:17:51.619 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:17:51.754 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch337
2025-09-01 09:17:54.712 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 337/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.127s, data_time: 0.044s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 1.099e-03, size: 384, ETA: 1:16:29
2025-09-01 09:17:57.431 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 337/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.119s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.096e-03, size: 416, ETA: 1:16:26
2025-09-01 09:18:00.347 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 337/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.126s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 1.094e-03, size: 288, ETA: 1:16:24
2025-09-01 09:18:03.224 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 337/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.123s, data_time: 0.003s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 1.091e-03, size: 288, ETA: 1:16:21
2025-09-01 09:18:06.225 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 337/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.124s, 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: 1.088e-03, size: 576, ETA: 1:16:18
2025-09-01 09:18:09.197 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 337/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.085e-03, size: 480, ETA: 1:16:15
2025-09-01 09:18:10.477 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:18:10.513 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch338
2025-09-01 09:18:13.139 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 338/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.122s, 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: 1.081e-03, size: 448, ETA: 1:16:11
2025-09-01 09:18:15.905 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 338/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.136s, data_time: 0.055s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 1.078e-03, size: 416, ETA: 1:16:08
2025-09-01 09:18:18.761 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 338/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.142s, data_time: 0.059s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 1.075e-03, size: 320, ETA: 1:16:06
2025-09-01 09:18:21.578 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 338/600, iter: 80/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.140s, data_time: 0.062s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 1.073e-03, size: 576, ETA: 1:16:03
2025-09-01 09:18:24.488 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 338/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.145s, data_time: 0.067s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 1.070e-03, size: 256, ETA: 1:16:00
2025-09-01 09:18:27.448 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 338/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.147s, data_time: 0.068s, total_loss: 6.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 1.067e-03, size: 288, ETA: 1:15:58
2025-09-01 09:18:28.866 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:18:28.905 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch339
2025-09-01 09:18:31.686 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 339/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.063e-03, size: 512, ETA: 1:15:54
2025-09-01 09:18:34.448 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 339/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.054s, total_loss: 7.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 1.060e-03, size: 544, ETA: 1:15:52
2025-09-01 09:18:37.323 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 339/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.133s, data_time: 0.050s, total_loss: 5.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 1.058e-03, size: 320, ETA: 1:15:49
2025-09-01 09:18:40.258 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 339/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.136s, data_time: 0.038s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.055e-03, size: 512, ETA: 1:15:46
2025-09-01 09:18:43.079 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 339/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.124s, data_time: 0.033s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.052e-03, size: 352, ETA: 1:15:43
2025-09-01 09:18:45.919 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 339/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.122s, data_time: 0.037s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 1.049e-03, size: 352, ETA: 1:15:40
2025-09-01 09:18:47.036 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:18:47.072 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch340
2025-09-01 09:18:49.931 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 340/600, iter: 20/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.142s, data_time: 0.060s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.9, lr: 1.045e-03, size: 416, ETA: 1:15:36
2025-09-01 09:18:52.834 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 340/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.144s, data_time: 0.061s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 1.043e-03, size: 544, ETA: 1:15:34
2025-09-01 09:18:55.630 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 340/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 1.040e-03, size: 544, ETA: 1:15:31
2025-09-01 09:18:58.571 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 340/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.146s, data_time: 0.063s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 1.037e-03, size: 320, ETA: 1:15:29
2025-09-01 09:19:01.366 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 340/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.051s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 1.035e-03, size: 512, ETA: 1:15:26
2025-09-01 09:19:04.183 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 340/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.136s, data_time: 0.047s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.032e-03, size: 576, ETA: 1:15:23
2025-09-01 09:19:05.362 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:19:11.225 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:19:12.979 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:19:14.231 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6117
2025-09-01 09:19:14.498 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5828
2025-09-01 09:19:14.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3456
2025-09-01 09:19:14.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5133
2025-09-01 09:19:14.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.612
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.583
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.346
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.513
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:19:14.550 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:19:14.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:19:14.551 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:19:16.005 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:19:17.446 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:19:18.848 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:19:20.226 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:19:21.674 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:19:23.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:19:24.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:19:25.896 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:19:27.289 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:19:27.290 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 09:19:27.290 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 09:19:27.290 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:19:27.299 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.95 ms, Average inference time: 2.31 ms

2025-09-01 09:19:27.301 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:19:27.332 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:19:27.365 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch341
2025-09-01 09:19:29.879 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 341/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.124s, data_time: 0.043s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 1.028e-03, size: 480, ETA: 1:15:19
2025-09-01 09:19:32.667 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 341/600, iter: 40/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.052s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 1.025e-03, size: 576, ETA: 1:15:17
2025-09-01 09:19:35.537 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 341/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.142s, data_time: 0.056s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 1.023e-03, size: 544, ETA: 1:15:14
2025-09-01 09:19:38.379 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 341/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 1.020e-03, size: 512, ETA: 1:15:11
2025-09-01 09:19:41.109 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 341/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.056s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 1.017e-03, size: 288, ETA: 1:15:09
2025-09-01 09:19:43.926 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 341/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.137s, data_time: 0.049s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.015e-03, size: 416, ETA: 1:15:06
2025-09-01 09:19:45.144 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:19:45.251 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch342
2025-09-01 09:19:47.972 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 342/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.134s, data_time: 0.053s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 1.011e-03, size: 320, ETA: 1:15:02
2025-09-01 09:19:50.888 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 342/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.050s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 1.008e-03, size: 416, ETA: 1:15:00
2025-09-01 09:19:53.746 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 342/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.141s, data_time: 0.061s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 1.006e-03, size: 416, ETA: 1:14:57
2025-09-01 09:19:56.597 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 342/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 1.003e-03, size: 288, ETA: 1:14:54
2025-09-01 09:19:59.400 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 342/600, iter: 100/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.139s, data_time: 0.055s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 1.000e-03, size: 352, ETA: 1:14:52
2025-09-01 09:20:02.289 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 342/600, iter: 120/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.144s, data_time: 0.064s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.6, lr: 9.977e-04, size: 576, ETA: 1:14:49
2025-09-01 09:20:03.550 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:20:03.598 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch343
2025-09-01 09:20:06.415 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 343/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.140s, data_time: 0.062s, total_loss: 7.0, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 9.939e-04, size: 320, ETA: 1:14:45
2025-09-01 09:20:09.103 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 343/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.132s, data_time: 0.034s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.913e-04, size: 384, ETA: 1:14:43
2025-09-01 09:20:11.918 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 343/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.139s, data_time: 0.005s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.887e-04, size: 384, ETA: 1:14:40
2025-09-01 09:20:14.738 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 343/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.861e-04, size: 320, ETA: 1:14:37
2025-09-01 09:20:17.700 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 343/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.146s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.835e-04, size: 576, ETA: 1:14:35
2025-09-01 09:20:20.474 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 343/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.028s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.810e-04, size: 384, ETA: 1:14:32
2025-09-01 09:20:21.832 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:20:21.972 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch344
2025-09-01 09:20:24.672 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 344/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 9.772e-04, size: 576, ETA: 1:14:28
2025-09-01 09:20:27.578 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 344/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.137s, data_time: 0.004s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 9.747e-04, size: 448, ETA: 1:14:25
2025-09-01 09:20:30.492 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 344/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.133s, data_time: 0.015s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 9.721e-04, size: 480, ETA: 1:14:23
2025-09-01 09:20:33.259 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 344/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, 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: 9.696e-04, size: 384, ETA: 1:14:20
2025-09-01 09:20:36.053 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 344/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.126s, data_time: 0.007s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.671e-04, size: 448, ETA: 1:14:17
2025-09-01 09:20:38.858 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 344/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.129s, data_time: 0.039s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 9.645e-04, size: 256, ETA: 1:14:14
2025-09-01 09:20:40.125 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:20:40.168 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch345
2025-09-01 09:20:42.984 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 345/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.129s, data_time: 0.025s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 9.609e-04, size: 416, ETA: 1:14:10
2025-09-01 09:20:45.895 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 345/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 9.584e-04, size: 544, ETA: 1:14:08
2025-09-01 09:20:48.766 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 345/600, iter: 60/129, gpu mem: 1663Mb, mem: 46.9Gb, iter_time: 0.130s, data_time: 0.024s, total_loss: 4.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.7, cls_loss: 0.7, lr: 9.559e-04, size: 416, ETA: 1:14:05
2025-09-01 09:20:51.516 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 345/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.122s, data_time: 0.026s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 9.534e-04, size: 416, ETA: 1:14:02
2025-09-01 09:20:54.266 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 345/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.131s, data_time: 0.035s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 9.509e-04, size: 320, ETA: 1:13:59
2025-09-01 09:20:57.051 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 345/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.133s, data_time: 0.040s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.484e-04, size: 512, ETA: 1:13:56
2025-09-01 09:20:58.270 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:21:04.104 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:21:05.922 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:21:07.166 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6140
2025-09-01 09:21:07.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5846
2025-09-01 09:21:07.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3755
2025-09-01 09:21:07.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5247
2025-09-01 09:21:07.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:21:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:21:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.614
2025-09-01 09:21:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.585
2025-09-01 09:21:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.375
2025-09-01 09:21:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.525
2025-09-01 09:21:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:21:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:21:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:21:07.417 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:21:07.418 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:21:07.418 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:21:07.418 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:21:07.418 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:21:07.418 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:21:08.924 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:21:10.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:21:11.867 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:21:13.318 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:21:14.983 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:21:16.542 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:21:17.970 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:21:19.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:21:21.024 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:21:21.025 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:21:21.025 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:21:21.025 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:21:21.051 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.97 ms, Average inference time: 2.36 ms

2025-09-01 09:21:21.054 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:21:21.078 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:21:21.111 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch346
2025-09-01 09:21:23.582 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 346/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.121s, data_time: 0.045s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 9.448e-04, size: 512, ETA: 1:13:52
2025-09-01 09:21:26.437 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 346/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.128s, data_time: 0.040s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 9.423e-04, size: 288, ETA: 1:13:49
2025-09-01 09:21:29.350 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 346/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.015s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.0, lr: 9.398e-04, size: 384, ETA: 1:13:47
2025-09-01 09:21:32.188 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 346/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.127s, 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: 9.374e-04, size: 320, ETA: 1:13:44
2025-09-01 09:21:35.011 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 346/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 9.349e-04, size: 352, ETA: 1:13:41
2025-09-01 09:21:37.940 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 346/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.134s, 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: 9.325e-04, size: 288, ETA: 1:13:38
2025-09-01 09:21:39.140 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:21:39.300 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch347
2025-09-01 09:21:42.044 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 347/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.120s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 9.290e-04, size: 576, ETA: 1:13:34
2025-09-01 09:21:44.701 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 347/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.127s, data_time: 0.016s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 9.265e-04, size: 256, ETA: 1:13:31
2025-09-01 09:21:47.562 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 347/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.128s, data_time: 0.009s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 9.241e-04, size: 384, ETA: 1:13:29
2025-09-01 09:21:50.341 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 347/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.130s, data_time: 0.017s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 9.217e-04, size: 320, ETA: 1:13:26
2025-09-01 09:21:53.244 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 347/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.136s, data_time: 0.045s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 9.193e-04, size: 448, ETA: 1:13:23
2025-09-01 09:21:56.070 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 347/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.128s, data_time: 0.026s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 9.169e-04, size: 576, ETA: 1:13:20
2025-09-01 09:21:57.309 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:21:57.382 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch348
2025-09-01 09:22:00.190 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 348/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.126s, data_time: 0.018s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.134e-04, size: 384, ETA: 1:13:16
2025-09-01 09:22:03.006 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 348/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.131s, data_time: 0.017s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 9.110e-04, size: 576, ETA: 1:13:14
2025-09-01 09:22:05.821 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 348/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.132s, data_time: 0.008s, total_loss: 6.9, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 9.086e-04, size: 256, ETA: 1:13:11
2025-09-01 09:22:08.562 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 348/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.124s, data_time: 0.012s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 9.063e-04, size: 544, ETA: 1:13:08
2025-09-01 09:22:11.385 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 348/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.038s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 9.039e-04, size: 416, ETA: 1:13:05
2025-09-01 09:22:14.273 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 348/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.131s, data_time: 0.025s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 9.015e-04, size: 448, ETA: 1:13:03
2025-09-01 09:22:15.557 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:22:15.719 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch349
2025-09-01 09:22:18.351 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 349/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.121s, data_time: 0.023s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.981e-04, size: 544, ETA: 1:12:58
2025-09-01 09:22:21.304 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 349/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.132s, data_time: 0.049s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.9, lr: 8.958e-04, size: 480, ETA: 1:12:56
2025-09-01 09:22:24.220 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 349/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.8, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.934e-04, size: 288, ETA: 1:12:53
2025-09-01 09:22:26.898 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 349/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.129s, data_time: 0.046s, total_loss: 5.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 8.911e-04, size: 288, ETA: 1:12:50
2025-09-01 09:22:29.759 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 349/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.141s, data_time: 0.064s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.888e-04, size: 288, ETA: 1:12:48
2025-09-01 09:22:32.511 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 349/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.126s, data_time: 0.042s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 8.865e-04, size: 512, ETA: 1:12:45
2025-09-01 09:22:33.808 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:22:33.846 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch350
2025-09-01 09:22:36.616 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 350/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 8.831e-04, size: 480, ETA: 1:12:41
2025-09-01 09:22:39.477 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 350/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.141s, data_time: 0.057s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 8.808e-04, size: 416, ETA: 1:12:38
2025-09-01 09:22:42.323 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 350/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.048s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 8.785e-04, size: 352, ETA: 1:12:36
2025-09-01 09:22:45.105 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 350/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.134s, data_time: 0.034s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 8.762e-04, size: 544, ETA: 1:12:33
2025-09-01 09:22:47.933 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 350/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.133s, data_time: 0.054s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 8.740e-04, size: 480, ETA: 1:12:30
2025-09-01 09:22:50.641 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 350/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.135s, data_time: 0.048s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 8.717e-04, size: 288, ETA: 1:12:28
2025-09-01 09:22:51.940 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:22:57.777 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:23:00.987 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:23:03.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6083
2025-09-01 09:23:03.661 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5924
2025-09-01 09:23:03.720 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3653
2025-09-01 09:23:03.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5220
2025-09-01 09:23:03.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:23:03.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.608
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.592
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.365
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.522
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:23:03.722 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:23:03.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:23:03.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:23:03.723 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:23:06.442 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:23:09.237 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:23:11.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:23:14.749 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:23:17.487 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:23:20.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:23:22.891 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:23:25.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:23:28.306 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:23:28.306 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:23:28.307 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:23:28.308 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:23:28.337 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.94 ms, Average inference time: 2.31 ms

2025-09-01 09:23:28.338 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:23:28.371 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:23:28.413 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch351
2025-09-01 09:23:30.879 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 351/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.122s, data_time: 0.042s, total_loss: 7.3, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.684e-04, size: 320, ETA: 1:12:24
2025-09-01 09:23:33.654 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 351/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.137s, data_time: 0.045s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 8.661e-04, size: 512, ETA: 1:12:21
2025-09-01 09:23:36.482 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 351/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.031s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.639e-04, size: 288, ETA: 1:12:18
2025-09-01 09:23:39.421 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 351/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.133s, data_time: 0.022s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 8.616e-04, size: 320, ETA: 1:12:16
2025-09-01 09:23:42.249 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 351/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.136s, data_time: 0.010s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 8.594e-04, size: 544, ETA: 1:12:13
2025-09-01 09:23:45.160 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 351/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.142s, data_time: 0.035s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 8.572e-04, size: 384, ETA: 1:12:10
2025-09-01 09:23:46.433 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:23:46.475 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch352
2025-09-01 09:23:49.223 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 352/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.134s, data_time: 0.033s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 8.539e-04, size: 544, ETA: 1:12:06
2025-09-01 09:23:52.024 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 352/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.131s, data_time: 0.025s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 8.517e-04, size: 320, ETA: 1:12:04
2025-09-01 09:23:54.791 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 352/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.132s, data_time: 0.020s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 1.0, lr: 8.495e-04, size: 320, ETA: 1:12:01
2025-09-01 09:23:57.560 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 352/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.126s, data_time: 0.016s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 8.473e-04, size: 512, ETA: 1:11:58
2025-09-01 09:24:00.349 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 352/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.133s, data_time: 0.004s, total_loss: 6.2, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.6, lr: 8.451e-04, size: 256, ETA: 1:11:55
2025-09-01 09:24:03.240 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 352/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.130s, 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: 8.429e-04, size: 416, ETA: 1:11:53
2025-09-01 09:24:04.540 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:24:04.599 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch353
2025-09-01 09:24:07.392 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 353/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.136s, data_time: 0.010s, total_loss: 8.0, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 8.398e-04, size: 544, ETA: 1:11:49
2025-09-01 09:24:10.267 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 353/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.141s, data_time: 0.009s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 8.376e-04, size: 416, ETA: 1:11:46
2025-09-01 09:24:13.109 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 353/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.004s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 8.354e-04, size: 512, ETA: 1:11:43
2025-09-01 09:24:15.953 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 353/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.139s, data_time: 0.010s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 8.333e-04, size: 352, ETA: 1:11:41
2025-09-01 09:24:18.821 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 353/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.032s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.311e-04, size: 480, ETA: 1:11:38
2025-09-01 09:24:21.703 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 353/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.142s, data_time: 0.005s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.290e-04, size: 320, ETA: 1:11:36
2025-09-01 09:24:22.889 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:24:23.038 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch354
2025-09-01 09:24:25.875 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 354/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.130s, data_time: 0.007s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 8.259e-04, size: 352, ETA: 1:11:32
2025-09-01 09:24:28.786 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 354/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.009s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.238e-04, size: 480, ETA: 1:11:29
2025-09-01 09:24:31.547 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 354/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.134s, data_time: 0.048s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.216e-04, size: 512, ETA: 1:11:26
2025-09-01 09:24:34.346 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 354/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.061s, total_loss: 7.6, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.9, lr: 8.195e-04, size: 416, ETA: 1:11:24
2025-09-01 09:24:37.240 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 354/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.144s, data_time: 0.060s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.9, lr: 8.174e-04, size: 256, ETA: 1:11:21
2025-09-01 09:24:40.000 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 354/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 8.153e-04, size: 288, ETA: 1:11:18
2025-09-01 09:24:41.295 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:24:41.346 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch355
2025-09-01 09:24:44.180 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 355/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.140s, data_time: 0.051s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 0.9, lr: 8.123e-04, size: 448, ETA: 1:11:15
2025-09-01 09:24:47.077 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 355/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.141s, data_time: 0.027s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 8.102e-04, size: 288, ETA: 1:11:12
2025-09-01 09:24:49.977 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 355/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 8.081e-04, size: 384, ETA: 1:11:09
2025-09-01 09:24:52.808 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 355/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 6.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 8.060e-04, size: 320, ETA: 1:11:07
2025-09-01 09:24:55.709 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 355/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.142s, 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: 8.040e-04, size: 480, ETA: 1:11:04
2025-09-01 09:24:58.492 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 355/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.135s, data_time: 0.010s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.0, lr: 8.019e-04, size: 384, ETA: 1:11:01
2025-09-01 09:24:59.709 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:25:05.883 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:25:08.537 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:25:10.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6122
2025-09-01 09:25:10.677 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5867
2025-09-01 09:25:10.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3571
2025-09-01 09:25:10.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5187
2025-09-01 09:25:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:25:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:25:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.612
2025-09-01 09:25:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.587
2025-09-01 09:25:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.357
2025-09-01 09:25:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.519
2025-09-01 09:25:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:25:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:25:10.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:25:10.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:25:10.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:25:10.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:25:10.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:25:10.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:25:10.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:25:12.949 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:25:15.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:25:17.354 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:25:19.494 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:25:21.739 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:25:23.909 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:25:26.192 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:25:28.477 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:25:30.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:25:30.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 09:25:30.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:25:30.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:25:30.717 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.96 ms, Average inference time: 2.33 ms

2025-09-01 09:25:30.718 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:25:30.748 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:25:30.779 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch356
2025-09-01 09:25:33.177 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 356/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.118s, data_time: 0.035s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 7.989e-04, size: 544, ETA: 1:10:57
2025-09-01 09:25:35.884 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 356/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.134s, data_time: 0.053s, total_loss: 6.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.969e-04, size: 416, ETA: 1:10:54
2025-09-01 09:25:38.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 356/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.129s, data_time: 0.033s, total_loss: 7.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.9, cls_loss: 0.9, lr: 7.949e-04, size: 384, ETA: 1:10:52
2025-09-01 09:25:41.465 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 356/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.126s, data_time: 0.009s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 7.928e-04, size: 480, ETA: 1:10:49
2025-09-01 09:25:44.171 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 356/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.128s, data_time: 0.028s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.1, lr: 7.908e-04, size: 288, ETA: 1:10:46
2025-09-01 09:25:46.977 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 356/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.133s, data_time: 0.040s, total_loss: 6.5, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.888e-04, size: 288, ETA: 1:10:43
2025-09-01 09:25:48.355 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:25:48.394 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch357
2025-09-01 09:25:51.191 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 357/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.056s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 7.859e-04, size: 544, ETA: 1:10:40
2025-09-01 09:25:53.978 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 357/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.056s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.839e-04, size: 384, ETA: 1:10:37
2025-09-01 09:25:56.796 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 357/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.126s, data_time: 0.031s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 7.819e-04, size: 512, ETA: 1:10:34
2025-09-01 09:25:59.578 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 357/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.124s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.799e-04, size: 352, ETA: 1:10:31
2025-09-01 09:26:02.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 357/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.128s, data_time: 0.010s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 7.779e-04, size: 256, ETA: 1:10:29
2025-09-01 09:26:05.117 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 357/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.129s, data_time: 0.045s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.760e-04, size: 320, ETA: 1:10:26
2025-09-01 09:26:06.395 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:26:06.447 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch358
2025-09-01 09:26:09.241 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 358/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.062s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 7.731e-04, size: 448, ETA: 1:10:22
2025-09-01 09:26:12.027 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 358/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.136s, data_time: 0.050s, total_loss: 6.8, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 7.712e-04, size: 480, ETA: 1:10:19
2025-09-01 09:26:14.882 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 358/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 7.692e-04, size: 352, ETA: 1:10:17
2025-09-01 09:26:17.777 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 358/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.144s, data_time: 0.061s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 7.673e-04, size: 480, ETA: 1:10:14
2025-09-01 09:26:20.588 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 358/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.140s, data_time: 0.055s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.6, lr: 7.653e-04, size: 576, ETA: 1:10:11
2025-09-01 09:26:23.408 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 358/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.135s, data_time: 0.051s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 7.634e-04, size: 544, ETA: 1:10:09
2025-09-01 09:26:24.659 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:26:24.708 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch359
2025-09-01 09:26:27.456 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 359/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 7.606e-04, size: 448, ETA: 1:10:05
2025-09-01 09:26:30.369 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 359/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.145s, data_time: 0.066s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.3, cls_loss: 1.1, lr: 7.587e-04, size: 288, ETA: 1:10:02
2025-09-01 09:26:33.133 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 359/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.0, lr: 7.568e-04, size: 512, ETA: 1:10:00
2025-09-01 09:26:36.060 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 359/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.144s, data_time: 0.036s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.549e-04, size: 544, ETA: 1:09:57
2025-09-01 09:26:38.859 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 359/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.137s, data_time: 0.057s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 7.530e-04, size: 352, ETA: 1:09:54
2025-09-01 09:26:41.650 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 359/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.138s, data_time: 0.060s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 7.512e-04, size: 512, ETA: 1:09:52
2025-09-01 09:26:43.012 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:26:43.049 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch360
2025-09-01 09:26:45.901 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 360/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.140s, data_time: 0.064s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.484e-04, size: 480, ETA: 1:09:48
2025-09-01 09:26:48.708 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 360/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 4.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 7.466e-04, size: 416, ETA: 1:09:45
2025-09-01 09:26:51.505 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 360/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.132s, data_time: 0.022s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 1.0, lr: 7.447e-04, size: 448, ETA: 1:09:43
2025-09-01 09:26:54.384 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 360/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.137s, data_time: 0.042s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 7.429e-04, size: 352, ETA: 1:09:40
2025-09-01 09:26:57.120 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 360/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.130s, data_time: 0.013s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.410e-04, size: 512, ETA: 1:09:37
2025-09-01 09:27:00.002 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 360/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.130s, data_time: 0.017s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 7.392e-04, size: 384, ETA: 1:09:34
2025-09-01 09:27:01.297 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:27:07.127 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:27:09.586 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:27:11.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6121
2025-09-01 09:27:11.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5800
2025-09-01 09:27:11.796 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3791
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5237
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.612
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.580
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.379
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.524
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:27:11.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:27:11.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:27:11.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:27:11.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:27:11.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:27:11.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:27:11.798 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:27:13.850 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:27:15.877 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:27:17.986 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:27:20.071 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:27:22.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:27:24.271 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:27:26.350 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:27:28.423 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:27:30.486 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:27:30.487 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:27:30.487 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:27:30.487 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:27:30.512 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.96 ms, Average inference time: 2.35 ms

2025-09-01 09:27:30.517 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:27:30.540 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:27:30.629 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch361
2025-09-01 09:27:33.117 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 361/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.122s, data_time: 0.045s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 7.365e-04, size: 416, ETA: 1:09:30
2025-09-01 09:27:35.936 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 361/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.140s, data_time: 0.064s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 7.347e-04, size: 256, ETA: 1:09:28
2025-09-01 09:27:38.677 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 361/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.135s, data_time: 0.055s, total_loss: 6.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 7.329e-04, size: 576, ETA: 1:09:25
2025-09-01 09:27:41.674 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 361/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.149s, data_time: 0.070s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.7, lr: 7.311e-04, size: 352, ETA: 1:09:22
2025-09-01 09:27:44.462 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 361/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 7.293e-04, size: 352, ETA: 1:09:20
2025-09-01 09:27:47.379 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 361/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.144s, data_time: 0.055s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 7.275e-04, size: 448, ETA: 1:09:17
2025-09-01 09:27:48.660 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:27:48.697 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch362
2025-09-01 09:27:51.420 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 362/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.135s, data_time: 0.054s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 7.249e-04, size: 512, ETA: 1:09:13
2025-09-01 09:27:54.211 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 362/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.231e-04, size: 512, ETA: 1:09:11
2025-09-01 09:27:57.191 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 362/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.148s, data_time: 0.064s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 7.213e-04, size: 576, ETA: 1:09:08
2025-09-01 09:28:00.000 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 362/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 7.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.8, cls_loss: 0.8, lr: 7.196e-04, size: 480, ETA: 1:09:06
2025-09-01 09:28:02.869 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 362/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.143s, data_time: 0.058s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 7.178e-04, size: 480, ETA: 1:09:03
2025-09-01 09:28:05.729 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 362/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.142s, data_time: 0.063s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 7.161e-04, size: 352, ETA: 1:09:00
2025-09-01 09:28:07.068 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:28:07.111 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch363
2025-09-01 09:28:09.992 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 363/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 7.136e-04, size: 576, ETA: 1:08:57
2025-09-01 09:28:12.766 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 363/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.060s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 7.118e-04, size: 544, ETA: 1:08:54
2025-09-01 09:28:15.586 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 363/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.140s, data_time: 0.063s, total_loss: 6.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.101e-04, size: 288, ETA: 1:08:51
2025-09-01 09:28:18.540 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 363/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.144s, data_time: 0.064s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 7.084e-04, size: 576, ETA: 1:08:49
2025-09-01 09:28:21.377 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 363/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.0Gb, iter_time: 0.140s, data_time: 0.060s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 7.067e-04, size: 544, ETA: 1:08:46
2025-09-01 09:28:24.151 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 363/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.055s, total_loss: 6.0, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 7.050e-04, size: 448, ETA: 1:08:44
2025-09-01 09:28:25.410 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:28:25.544 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch364
2025-09-01 09:28:28.285 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 364/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.136s, data_time: 0.055s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 7.025e-04, size: 448, ETA: 1:08:40
2025-09-01 09:28:31.130 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 364/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.141s, data_time: 0.063s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 7.008e-04, size: 448, ETA: 1:08:37
2025-09-01 09:28:33.887 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 364/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.991e-04, size: 288, ETA: 1:08:34
2025-09-01 09:28:36.690 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 364/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 6.975e-04, size: 416, ETA: 1:08:32
2025-09-01 09:28:39.576 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 364/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.142s, data_time: 0.062s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.958e-04, size: 512, ETA: 1:08:29
2025-09-01 09:28:42.475 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 364/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.941e-04, size: 480, ETA: 1:08:26
2025-09-01 09:28:43.707 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:28:43.747 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch365
2025-09-01 09:28:46.590 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 365/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.132s, data_time: 0.050s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.917e-04, size: 576, ETA: 1:08:22
2025-09-01 09:28:49.343 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 365/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.128s, data_time: 0.035s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 6.901e-04, size: 384, ETA: 1:08:20
2025-09-01 09:28:52.284 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 365/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.146s, data_time: 0.065s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.884e-04, size: 512, ETA: 1:08:17
2025-09-01 09:28:55.027 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 365/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.136s, data_time: 0.054s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.6, lr: 6.868e-04, size: 544, ETA: 1:08:14
2025-09-01 09:28:57.942 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 365/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.145s, data_time: 0.065s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.852e-04, size: 352, ETA: 1:08:12
2025-09-01 09:29:00.893 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 365/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.147s, data_time: 0.064s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 6.836e-04, size: 448, ETA: 1:08:09
2025-09-01 09:29:02.073 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:29:08.001 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:29:10.227 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:29:11.765 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6109
2025-09-01 09:29:12.080 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5920
2025-09-01 09:29:12.133 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3563
2025-09-01 09:29:12.134 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5197
2025-09-01 09:29:12.134 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:29:12.134 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:29:12.134 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.611
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.592
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.356
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.520
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:29:12.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:29:12.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:29:14.110 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:29:16.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:29:17.929 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:29:19.816 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:29:21.663 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:29:23.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:29:25.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:29:27.315 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:29:29.172 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:29:29.172 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 09:29:29.172 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:29:29.172 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:29:29.197 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.41 ms, Average NMS time: 0.95 ms, Average inference time: 2.35 ms

2025-09-01 09:29:29.198 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:29:29.225 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:29:29.256 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch366
2025-09-01 09:29:31.727 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 366/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.121s, data_time: 0.041s, total_loss: 6.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 6.812e-04, size: 512, ETA: 1:08:05
2025-09-01 09:29:34.532 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 366/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.061s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.796e-04, size: 320, ETA: 1:08:03
2025-09-01 09:29:37.435 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 366/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.144s, data_time: 0.061s, total_loss: 5.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 6.781e-04, size: 320, ETA: 1:08:00
2025-09-01 09:29:40.272 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 366/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.765e-04, size: 352, ETA: 1:07:57
2025-09-01 09:29:43.059 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 366/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.130s, data_time: 0.030s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.2, lr: 6.749e-04, size: 480, ETA: 1:07:55
2025-09-01 09:29:46.013 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 366/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.134s, data_time: 0.005s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 0.8, lr: 6.733e-04, size: 576, ETA: 1:07:52
2025-09-01 09:29:47.283 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:29:47.402 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch367
2025-09-01 09:29:50.216 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 367/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.050s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 6.711e-04, size: 256, ETA: 1:07:48
2025-09-01 09:29:53.055 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 367/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.141s, data_time: 0.060s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.695e-04, size: 320, ETA: 1:07:45
2025-09-01 09:29:55.884 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 367/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.141s, data_time: 0.054s, total_loss: 6.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.6, lr: 6.680e-04, size: 480, ETA: 1:07:43
2025-09-01 09:29:58.572 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 367/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.132s, data_time: 0.053s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.664e-04, size: 320, ETA: 1:07:40
2025-09-01 09:30:01.281 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 367/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.129s, data_time: 0.035s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 6.649e-04, size: 320, ETA: 1:07:37
2025-09-01 09:30:04.130 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 367/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.031s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.634e-04, size: 512, ETA: 1:07:35
2025-09-01 09:30:05.367 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:30:05.436 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch368
2025-09-01 09:30:08.235 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 368/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.131s, data_time: 0.044s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 6.612e-04, size: 320, ETA: 1:07:31
2025-09-01 09:30:11.114 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 368/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.143s, data_time: 0.068s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 6.596e-04, size: 256, ETA: 1:07:28
2025-09-01 09:30:13.863 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 368/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.136s, data_time: 0.058s, total_loss: 6.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.6, lr: 6.581e-04, size: 512, ETA: 1:07:25
2025-09-01 09:30:16.736 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 368/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.1, lr: 6.566e-04, size: 256, ETA: 1:07:23
2025-09-01 09:30:19.563 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 368/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.061s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.552e-04, size: 576, ETA: 1:07:20
2025-09-01 09:30:22.454 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 368/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.143s, data_time: 0.063s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.537e-04, size: 320, ETA: 1:07:18
2025-09-01 09:30:23.656 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:30:23.693 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch369
2025-09-01 09:30:26.471 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 369/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.131s, data_time: 0.051s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.6, lr: 6.515e-04, size: 256, ETA: 1:07:14
2025-09-01 09:30:29.421 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 369/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.142s, data_time: 0.053s, total_loss: 7.3, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 6.501e-04, size: 320, ETA: 1:07:11
2025-09-01 09:30:32.292 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 369/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.143s, data_time: 0.065s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 6.486e-04, size: 544, ETA: 1:07:08
2025-09-01 09:30:35.254 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 369/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.147s, data_time: 0.065s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 6.472e-04, size: 448, ETA: 1:07:06
2025-09-01 09:30:37.949 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 369/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.126s, data_time: 0.030s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.457e-04, size: 544, ETA: 1:07:03
2025-09-01 09:30:40.632 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 369/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.132s, data_time: 0.044s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.443e-04, size: 576, ETA: 1:07:00
2025-09-01 09:30:41.954 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:30:41.990 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch370
2025-09-01 09:30:44.926 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 370/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.020s, total_loss: 6.2, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 6.422e-04, size: 288, ETA: 1:06:56
2025-09-01 09:30:47.745 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 370/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.020s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 6.408e-04, size: 448, ETA: 1:06:54
2025-09-01 09:30:50.580 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 370/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.1, lr: 6.394e-04, size: 256, ETA: 1:06:51
2025-09-01 09:30:53.397 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 370/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.140s, data_time: 0.054s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.380e-04, size: 576, ETA: 1:06:48
2025-09-01 09:30:56.175 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 370/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.366e-04, size: 288, ETA: 1:06:46
2025-09-01 09:30:59.029 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 370/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.059s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.352e-04, size: 544, ETA: 1:06:43
2025-09-01 09:31:00.332 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:31:06.339 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:31:08.026 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:31:09.164 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6065
2025-09-01 09:31:09.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5779
2025-09-01 09:31:09.451 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3612
2025-09-01 09:31:09.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5152
2025-09-01 09:31:09.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:31:09.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:31:09.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.607
2025-09-01 09:31:09.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.578
2025-09-01 09:31:09.452 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.361
2025-09-01 09:31:09.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.515
2025-09-01 09:31:09.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:31:09.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:31:09.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:31:09.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:31:09.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:31:09.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:31:09.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:31:09.453 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:31:09.454 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:31:11.051 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:31:12.468 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:31:13.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:31:15.422 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:31:16.805 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:31:18.216 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:31:19.606 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:31:20.987 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:31:22.423 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:31:22.423 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 09:31:22.423 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:31:22.423 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:31:22.432 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.33 ms, Average NMS time: 0.93 ms, Average inference time: 2.27 ms

2025-09-01 09:31:22.434 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:31:22.466 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:31:22.498 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch371
2025-09-01 09:31:25.022 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 371/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.125s, data_time: 0.045s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.8, lr: 6.332e-04, size: 320, ETA: 1:06:39
2025-09-01 09:31:27.897 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 371/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.143s, data_time: 0.065s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 6.318e-04, size: 544, ETA: 1:06:37
2025-09-01 09:31:30.624 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 371/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.136s, data_time: 0.052s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.6, lr: 6.304e-04, size: 544, ETA: 1:06:34
2025-09-01 09:31:33.505 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 371/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.143s, data_time: 0.064s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 6.291e-04, size: 320, ETA: 1:06:31
2025-09-01 09:31:36.349 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 371/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.141s, data_time: 0.055s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 6.277e-04, size: 512, ETA: 1:06:29
2025-09-01 09:31:39.164 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 371/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.140s, data_time: 0.062s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 1.0, lr: 6.264e-04, size: 352, ETA: 1:06:26
2025-09-01 09:31:40.392 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:31:40.447 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch372
2025-09-01 09:31:43.309 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 372/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.132s, data_time: 0.020s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 6.245e-04, size: 320, ETA: 1:06:22
2025-09-01 09:31:46.188 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 372/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.130s, data_time: 0.021s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 6.231e-04, size: 416, ETA: 1:06:19
2025-09-01 09:31:49.013 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 372/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.135s, data_time: 0.030s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 6.218e-04, size: 384, ETA: 1:06:17
2025-09-01 09:31:51.945 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 372/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.053s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.205e-04, size: 384, ETA: 1:06:14
2025-09-01 09:31:54.787 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 372/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.052s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 6.192e-04, size: 512, ETA: 1:06:11
2025-09-01 09:31:57.661 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 372/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.059s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 6.179e-04, size: 480, ETA: 1:06:09
2025-09-01 09:31:58.978 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:31:59.015 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch373
2025-09-01 09:32:01.794 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 373/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.135s, data_time: 0.045s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 6.160e-04, size: 416, ETA: 1:06:05
2025-09-01 09:32:04.744 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 373/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.128s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 1.9, cls_loss: 0.7, lr: 6.147e-04, size: 256, ETA: 1:06:02
2025-09-01 09:32:07.689 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 373/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.126s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.6, lr: 6.134e-04, size: 512, ETA: 1:05:59
2025-09-01 09:32:10.497 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 373/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.126s, data_time: 0.005s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 6.122e-04, size: 384, ETA: 1:05:56
2025-09-01 09:32:13.307 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 373/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.123s, data_time: 0.016s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 6.109e-04, size: 256, ETA: 1:05:54
2025-09-01 09:32:16.105 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 373/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.130s, data_time: 0.042s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 6.097e-04, size: 416, ETA: 1:05:51
2025-09-01 09:32:17.310 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:32:17.373 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch374
2025-09-01 09:32:20.201 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 374/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.136s, data_time: 0.053s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 6.079e-04, size: 320, ETA: 1:05:47
2025-09-01 09:32:23.000 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 374/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.057s, total_loss: 6.3, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 6.066e-04, size: 288, ETA: 1:05:44
2025-09-01 09:32:25.796 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 374/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.136s, data_time: 0.057s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 6.054e-04, size: 512, ETA: 1:05:42
2025-09-01 09:32:28.687 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 374/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.144s, data_time: 0.060s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 6.042e-04, size: 576, ETA: 1:05:39
2025-09-01 09:32:31.536 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 374/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.141s, data_time: 0.056s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 6.029e-04, size: 576, ETA: 1:05:36
2025-09-01 09:32:34.372 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 374/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.141s, data_time: 0.058s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 6.017e-04, size: 448, ETA: 1:05:34
2025-09-01 09:32:35.686 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:32:35.722 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch375
2025-09-01 09:32:38.570 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 375/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.132s, data_time: 0.020s, total_loss: 7.1, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.8, lr: 6.000e-04, size: 416, ETA: 1:05:30
2025-09-01 09:32:41.356 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 375/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.130s, data_time: 0.024s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.988e-04, size: 320, ETA: 1:05:27
2025-09-01 09:32:44.215 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 375/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.131s, data_time: 0.028s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 1.1, lr: 5.976e-04, size: 352, ETA: 1:05:24
2025-09-01 09:32:46.954 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 375/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.132s, data_time: 0.031s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.0, lr: 5.964e-04, size: 576, ETA: 1:05:22
2025-09-01 09:32:49.675 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 375/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.130s, data_time: 0.027s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.953e-04, size: 512, ETA: 1:05:19
2025-09-01 09:32:52.417 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 375/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.134s, data_time: 0.041s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.941e-04, size: 512, ETA: 1:05:16
2025-09-01 09:32:53.668 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:32:59.549 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:33:01.188 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:33:02.298 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6127
2025-09-01 09:33:02.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5865
2025-09-01 09:33:02.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3778
2025-09-01 09:33:02.562 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5256
2025-09-01 09:33:02.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:33:02.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:33:02.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.613
2025-09-01 09:33:02.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.586
2025-09-01 09:33:02.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.378
2025-09-01 09:33:02.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.526
2025-09-01 09:33:02.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:33:02.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:33:02.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:33:02.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:33:02.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:33:02.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:33:02.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:33:02.565 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:33:02.565 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:33:03.975 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:33:05.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:33:06.757 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:33:08.098 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:33:09.520 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:33:10.920 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:33:12.309 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:33:13.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:33:15.071 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:33:15.071 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:33:15.071 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 09:33:15.071 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:33:15.081 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.94 ms, Average inference time: 2.29 ms

2025-09-01 09:33:15.082 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:33:15.153 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:33:15.186 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch376
2025-09-01 09:33:17.713 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 376/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.125s, data_time: 0.048s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.924e-04, size: 384, ETA: 1:05:12
2025-09-01 09:33:20.537 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 376/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.137s, data_time: 0.050s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.913e-04, size: 544, ETA: 1:05:09
2025-09-01 09:33:23.315 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 376/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.128s, data_time: 0.032s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.901e-04, size: 320, ETA: 1:05:07
2025-09-01 09:33:26.204 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 376/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.137s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.890e-04, size: 544, ETA: 1:05:04
2025-09-01 09:33:29.093 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 376/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.134s, 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: 5.879e-04, size: 384, ETA: 1:05:01
2025-09-01 09:33:32.026 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 376/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.135s, data_time: 0.011s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.9, lr: 5.868e-04, size: 288, ETA: 1:04:59
2025-09-01 09:33:33.197 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:33:33.318 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch377
2025-09-01 09:33:36.248 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 377/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.128s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.852e-04, size: 544, ETA: 1:04:54
2025-09-01 09:33:39.103 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 377/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.037s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.841e-04, size: 256, ETA: 1:04:52
2025-09-01 09:33:41.877 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 377/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.133s, data_time: 0.051s, total_loss: 5.8, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.830e-04, size: 352, ETA: 1:04:49
2025-09-01 09:33:44.536 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 377/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.128s, data_time: 0.041s, total_loss: 6.5, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.819e-04, size: 544, ETA: 1:04:46
2025-09-01 09:33:47.388 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 377/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.135s, data_time: 0.026s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.2, lr: 5.808e-04, size: 512, ETA: 1:04:44
2025-09-01 09:33:50.226 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 377/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.138s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.797e-04, size: 544, ETA: 1:04:41
2025-09-01 09:33:51.468 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:33:51.650 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch378
2025-09-01 09:33:54.555 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 378/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, 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: 5.782e-04, size: 448, ETA: 1:04:37
2025-09-01 09:33:57.321 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 378/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.131s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.771e-04, size: 544, ETA: 1:04:34
2025-09-01 09:34:00.117 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 378/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.132s, data_time: 0.005s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 5.761e-04, size: 320, ETA: 1:04:32
2025-09-01 09:34:03.104 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 378/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.141s, 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: 5.750e-04, size: 448, ETA: 1:04:29
2025-09-01 09:34:05.979 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 378/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.134s, 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: 5.740e-04, size: 512, ETA: 1:04:26
2025-09-01 09:34:08.807 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 378/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.136s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.730e-04, size: 448, ETA: 1:04:24
2025-09-01 09:34:10.127 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:34:10.164 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch379
2025-09-01 09:34:13.004 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 379/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.140s, data_time: 0.002s, total_loss: 7.1, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.7, lr: 5.715e-04, size: 352, ETA: 1:04:20
2025-09-01 09:34:15.852 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 379/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, 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: 5.705e-04, size: 544, ETA: 1:04:17
2025-09-01 09:34:18.616 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 379/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.134s, data_time: 0.007s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.695e-04, size: 480, ETA: 1:04:14
2025-09-01 09:34:21.582 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 379/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.145s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.8, lr: 5.685e-04, size: 480, ETA: 1:04:12
2025-09-01 09:34:24.428 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 379/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.137s, data_time: 0.007s, total_loss: 8.9, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 4.5, cls_loss: 1.1, lr: 5.675e-04, size: 576, ETA: 1:04:09
2025-09-01 09:34:27.276 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 379/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.138s, data_time: 0.016s, total_loss: 6.0, iou_loss: 3.2, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.8, lr: 5.665e-04, size: 352, ETA: 1:04:06
2025-09-01 09:34:28.560 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:34:28.731 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch380
2025-09-01 09:34:31.507 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 380/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.131s, 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: 5.651e-04, size: 384, ETA: 1:04:03
2025-09-01 09:34:34.289 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 380/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.124s, data_time: 0.029s, total_loss: 4.6, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.6, lr: 5.642e-04, size: 512, ETA: 1:04:00
2025-09-01 09:34:37.218 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 380/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.143s, data_time: 0.066s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.632e-04, size: 256, ETA: 1:03:57
2025-09-01 09:34:40.025 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 380/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.133s, data_time: 0.049s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.623e-04, size: 384, ETA: 1:03:54
2025-09-01 09:34:42.839 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 380/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.131s, data_time: 0.045s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.613e-04, size: 320, ETA: 1:03:52
2025-09-01 09:34:45.674 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 380/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.135s, data_time: 0.060s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.604e-04, size: 320, ETA: 1:03:49
2025-09-01 09:34:46.935 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:34:53.042 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:34:55.544 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:34:57.125 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6054
2025-09-01 09:34:57.396 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5763
2025-09-01 09:34:57.491 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3452
2025-09-01 09:34:57.492 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5090
2025-09-01 09:34:57.492 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:34:57.492 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:34:57.492 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.605
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.576
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.345
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.509
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:34:57.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:34:57.494 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:34:57.494 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:34:59.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:35:01.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:35:03.504 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:35:05.422 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:35:07.473 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:35:09.435 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:35:11.350 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:35:13.295 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:35:15.231 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:35:15.231 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:35:15.232 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 09:35:15.232 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:35:15.261 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.95 ms, Average inference time: 2.34 ms

2025-09-01 09:35:15.262 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:35:15.293 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:35:15.326 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch381
2025-09-01 09:35:17.766 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 381/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.121s, data_time: 0.040s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.590e-04, size: 352, ETA: 1:03:45
2025-09-01 09:35:20.650 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 381/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.142s, data_time: 0.058s, total_loss: 5.5, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.581e-04, size: 448, ETA: 1:03:42
2025-09-01 09:35:23.680 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 381/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.151s, data_time: 0.071s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 1.2, lr: 5.572e-04, size: 320, ETA: 1:03:40
2025-09-01 09:35:26.443 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 381/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, data_time: 0.055s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.563e-04, size: 576, ETA: 1:03:37
2025-09-01 09:35:29.139 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 381/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.129s, data_time: 0.033s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.554e-04, size: 416, ETA: 1:03:34
2025-09-01 09:35:32.005 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 381/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.142s, data_time: 0.067s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.545e-04, size: 576, ETA: 1:03:32
2025-09-01 09:35:33.254 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:35:33.343 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch382
2025-09-01 09:35:36.126 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 382/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.135s, data_time: 0.051s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.533e-04, size: 576, ETA: 1:03:28
2025-09-01 09:35:39.052 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 382/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.138s, data_time: 0.015s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.524e-04, size: 416, ETA: 1:03:25
2025-09-01 09:35:41.796 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 382/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.127s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.9, lr: 5.515e-04, size: 256, ETA: 1:03:22
2025-09-01 09:35:44.672 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 382/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.135s, data_time: 0.037s, total_loss: 7.6, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.7, cls_loss: 0.8, lr: 5.507e-04, size: 352, ETA: 1:03:20
2025-09-01 09:35:47.497 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 382/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.140s, data_time: 0.057s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.498e-04, size: 384, ETA: 1:03:17
2025-09-01 09:35:50.321 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 382/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.140s, data_time: 0.061s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.490e-04, size: 352, ETA: 1:03:14
2025-09-01 09:35:51.677 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:35:51.730 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch383
2025-09-01 09:35:54.575 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 383/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.4, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.478e-04, size: 256, ETA: 1:03:11
2025-09-01 09:35:57.391 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 383/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.140s, data_time: 0.059s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.1, lr: 5.469e-04, size: 256, ETA: 1:03:08
2025-09-01 09:36:00.298 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 383/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.144s, data_time: 0.062s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.461e-04, size: 352, ETA: 1:03:05
2025-09-01 09:36:03.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 383/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.135s, data_time: 0.021s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.9, lr: 5.453e-04, size: 320, ETA: 1:03:03
2025-09-01 09:36:06.165 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 383/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.139s, data_time: 0.029s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 1.1, lr: 5.445e-04, size: 288, ETA: 1:03:00
2025-09-01 09:36:08.968 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 383/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.124s, data_time: 0.002s, total_loss: 6.7, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 5.437e-04, size: 288, ETA: 1:02:57
2025-09-01 09:36:10.270 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:36:10.325 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch384
2025-09-01 09:36:13.117 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 384/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.127s, data_time: 0.001s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.426e-04, size: 416, ETA: 1:02:53
2025-09-01 09:36:16.010 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 384/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.133s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.418e-04, size: 352, ETA: 1:02:50
2025-09-01 09:36:18.869 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 384/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.129s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.410e-04, size: 544, ETA: 1:02:48
2025-09-01 09:36:21.686 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 384/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.134s, data_time: 0.032s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.403e-04, size: 448, ETA: 1:02:45
2025-09-01 09:36:24.652 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 384/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, 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: 5.395e-04, size: 544, ETA: 1:02:42
2025-09-01 09:36:27.506 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 384/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.130s, data_time: 0.017s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.387e-04, size: 416, ETA: 1:02:39
2025-09-01 09:36:28.741 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:36:28.902 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch385
2025-09-01 09:36:31.700 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 385/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.129s, data_time: 0.050s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.377e-04, size: 576, ETA: 1:02:35
2025-09-01 09:36:34.565 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 385/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.131s, data_time: 0.039s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.369e-04, size: 544, ETA: 1:02:33
2025-09-01 09:36:37.250 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 385/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.127s, data_time: 0.049s, total_loss: 5.2, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.8, lr: 5.362e-04, size: 288, ETA: 1:02:30
2025-09-01 09:36:40.163 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 385/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.143s, data_time: 0.060s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.355e-04, size: 416, ETA: 1:02:27
2025-09-01 09:36:43.118 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 385/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.147s, data_time: 0.069s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.4, cls_loss: 0.7, lr: 5.348e-04, size: 512, ETA: 1:02:25
2025-09-01 09:36:46.023 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 385/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.145s, data_time: 0.061s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.2, lr: 5.341e-04, size: 256, ETA: 1:02:22
2025-09-01 09:36:47.237 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:36:53.184 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:36:55.383 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:36:56.947 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6135
2025-09-01 09:36:57.220 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5784
2025-09-01 09:36:57.277 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3524
2025-09-01 09:36:57.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5148
2025-09-01 09:36:57.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:36:57.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:36:57.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.614
2025-09-01 09:36:57.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.578
2025-09-01 09:36:57.278 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.352
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.515
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:36:57.279 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:36:59.155 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:37:01.010 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:37:02.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:37:04.727 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:37:06.596 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:37:08.508 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:37:10.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:37:12.146 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:37:13.993 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:37:13.994 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 09:37:13.994 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 09:37:13.994 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:37:14.021 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.94 ms, Average inference time: 2.32 ms

2025-09-01 09:37:14.022 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:37:14.048 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:37:14.078 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch386
2025-09-01 09:37:16.559 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 386/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.121s, data_time: 0.039s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.6, lr: 5.331e-04, size: 320, ETA: 1:02:18
2025-09-01 09:37:19.457 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 386/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.137s, data_time: 0.035s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.324e-04, size: 448, ETA: 1:02:15
2025-09-01 09:37:22.239 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 386/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.133s, data_time: 0.049s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.317e-04, size: 416, ETA: 1:02:13
2025-09-01 09:37:25.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 386/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.135s, data_time: 0.059s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.310e-04, size: 384, ETA: 1:02:10
2025-09-01 09:37:27.946 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 386/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.142s, data_time: 0.064s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.304e-04, size: 544, ETA: 1:02:07
2025-09-01 09:37:30.802 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 386/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.141s, data_time: 0.060s, total_loss: 6.8, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.3, lr: 5.297e-04, size: 256, ETA: 1:02:05
2025-09-01 09:37:32.035 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:37:32.074 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch387
2025-09-01 09:37:34.854 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 387/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, data_time: 0.057s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.288e-04, size: 512, ETA: 1:02:01
2025-09-01 09:37:37.693 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 387/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.137s, data_time: 0.056s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.281e-04, size: 288, ETA: 1:01:58
2025-09-01 09:37:40.552 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 387/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.142s, data_time: 0.061s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.275e-04, size: 320, ETA: 1:01:56
2025-09-01 09:37:43.356 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 387/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, data_time: 0.046s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.269e-04, size: 544, ETA: 1:01:53
2025-09-01 09:37:46.298 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 387/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.144s, data_time: 0.050s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.263e-04, size: 576, ETA: 1:01:50
2025-09-01 09:37:49.135 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 387/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.140s, data_time: 0.058s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.256e-04, size: 320, ETA: 1:01:48
2025-09-01 09:37:50.312 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:37:50.481 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch388
2025-09-01 09:37:53.290 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 388/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.133s, data_time: 0.049s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.248e-04, size: 416, ETA: 1:01:44
2025-09-01 09:37:56.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 388/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.131s, data_time: 0.045s, total_loss: 7.0, iou_loss: 3.3, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.242e-04, size: 384, ETA: 1:01:41
2025-09-01 09:37:59.013 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 388/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.140s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.236e-04, size: 544, ETA: 1:01:38
2025-09-01 09:38:01.732 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 388/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.130s, 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: 5.230e-04, size: 544, ETA: 1:01:36
2025-09-01 09:38:04.577 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 388/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.133s, data_time: 0.003s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.224e-04, size: 576, ETA: 1:01:33
2025-09-01 09:38:07.436 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 388/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.137s, data_time: 0.004s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.219e-04, size: 384, ETA: 1:01:30
2025-09-01 09:38:08.657 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:38:08.709 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch389
2025-09-01 09:38:11.595 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 389/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.142s, data_time: 0.047s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.211e-04, size: 416, ETA: 1:01:26
2025-09-01 09:38:14.476 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 389/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.141s, data_time: 0.040s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.205e-04, size: 512, ETA: 1:01:24
2025-09-01 09:38:17.431 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 389/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.146s, data_time: 0.007s, total_loss: 4.6, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 1.6, cls_loss: 0.6, lr: 5.200e-04, size: 448, ETA: 1:01:21
2025-09-01 09:38:20.203 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 389/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, data_time: 0.015s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 1.8, cls_loss: 0.8, lr: 5.194e-04, size: 544, ETA: 1:01:18
2025-09-01 09:38:23.051 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 389/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.140s, data_time: 0.012s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.189e-04, size: 320, ETA: 1:01:16
2025-09-01 09:38:25.947 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 389/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.142s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.184e-04, size: 256, ETA: 1:01:13
2025-09-01 09:38:27.202 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:38:27.324 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch390
2025-09-01 09:38:30.072 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 390/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.132s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.6, lr: 5.177e-04, size: 576, ETA: 1:01:09
2025-09-01 09:38:32.902 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 390/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.139s, data_time: 0.021s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.172e-04, size: 256, ETA: 1:01:07
2025-09-01 09:38:35.686 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 390/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.138s, data_time: 0.056s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.167e-04, size: 384, ETA: 1:01:04
2025-09-01 09:38:38.672 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 390/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.148s, data_time: 0.068s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.162e-04, size: 576, ETA: 1:01:01
2025-09-01 09:38:41.593 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 390/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.145s, data_time: 0.063s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.157e-04, size: 512, ETA: 1:00:59
2025-09-01 09:38:44.427 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 390/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.141s, data_time: 0.055s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.152e-04, size: 512, ETA: 1:00:56
2025-09-01 09:38:45.545 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:38:51.525 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:38:53.677 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:38:55.159 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6113
2025-09-01 09:38:55.463 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5784
2025-09-01 09:38:55.517 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3555
2025-09-01 09:38:55.517 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5151
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.611
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.578
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.356
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.515
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:38:55.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:38:55.519 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:38:55.519 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:38:55.519 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:38:55.519 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:38:57.382 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:38:59.347 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:39:01.260 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:39:03.128 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:39:05.098 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:39:06.986 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:39:08.853 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:39:10.711 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:39:12.690 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:39:12.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:39:12.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:39:12.691 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:39:12.716 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.33 ms, Average NMS time: 0.91 ms, Average inference time: 2.24 ms

2025-09-01 09:39:12.717 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:39:12.742 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:39:12.773 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch391
2025-09-01 09:39:15.235 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 391/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.121s, data_time: 0.036s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 1.0, lr: 5.146e-04, size: 576, ETA: 1:00:52
2025-09-01 09:39:17.982 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 391/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.135s, data_time: 0.017s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.141e-04, size: 384, ETA: 1:00:49
2025-09-01 09:39:20.892 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 391/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.143s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.8, lr: 5.137e-04, size: 384, ETA: 1:00:47
2025-09-01 09:39:23.740 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 391/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.1Gb, iter_time: 0.139s, data_time: 0.004s, total_loss: 6.2, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.132e-04, size: 544, ETA: 1:00:44
2025-09-01 09:39:26.550 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 391/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.139s, data_time: 0.006s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.5, cls_loss: 0.7, lr: 5.128e-04, size: 512, ETA: 1:00:41
2025-09-01 09:39:29.374 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 391/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.138s, data_time: 0.034s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.124e-04, size: 384, ETA: 1:00:39
2025-09-01 09:39:30.728 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:39:30.773 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch392
2025-09-01 09:39:33.518 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 392/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.132s, data_time: 0.049s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 5.117e-04, size: 512, ETA: 1:00:35
2025-09-01 09:39:36.415 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 392/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.137s, data_time: 0.004s, total_loss: 4.5, iou_loss: 2.1, l1_loss: 0.0, conf_loss: 1.6, cls_loss: 0.8, lr: 5.113e-04, size: 256, ETA: 1:00:32
2025-09-01 09:39:39.075 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 392/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.125s, data_time: 0.028s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.109e-04, size: 288, ETA: 1:00:29
2025-09-01 09:39:41.873 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 392/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.132s, data_time: 0.009s, total_loss: 6.7, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.105e-04, size: 320, ETA: 1:00:27
2025-09-01 09:39:44.759 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 392/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.128s, data_time: 0.004s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.102e-04, size: 544, ETA: 1:00:24
2025-09-01 09:39:47.670 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 392/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, data_time: 0.006s, total_loss: 5.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.9, lr: 5.098e-04, size: 256, ETA: 1:00:21
2025-09-01 09:39:48.854 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:39:48.890 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch393
2025-09-01 09:39:51.816 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 393/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.141s, data_time: 0.024s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.092e-04, size: 512, ETA: 1:00:17
2025-09-01 09:39:54.570 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 393/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, data_time: 0.004s, total_loss: 7.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.6, lr: 5.089e-04, size: 448, ETA: 1:00:15
2025-09-01 09:39:57.477 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 393/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, data_time: 0.012s, total_loss: 7.1, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.085e-04, size: 544, ETA: 1:00:12
2025-09-01 09:40:00.401 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 393/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.131s, 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: 5.082e-04, size: 448, ETA: 1:00:09
2025-09-01 09:40:03.139 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 393/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.128s, data_time: 0.018s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 5.078e-04, size: 256, ETA: 1:00:06
2025-09-01 09:40:06.040 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 393/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.123s, data_time: 0.027s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.075e-04, size: 288, ETA: 1:00:04
2025-09-01 09:40:07.328 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:40:07.368 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch394
2025-09-01 09:40:10.241 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 394/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.129s, data_time: 0.004s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.070e-04, size: 544, ETA: 1:00:00
2025-09-01 09:40:12.914 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 394/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.122s, 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: 5.067e-04, size: 544, ETA: 0:59:57
2025-09-01 09:40:15.711 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 394/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.129s, data_time: 0.030s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 1.0, lr: 5.064e-04, size: 576, ETA: 0:59:54
2025-09-01 09:40:18.632 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 394/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.139s, data_time: 0.042s, total_loss: 6.1, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.7, cls_loss: 0.9, lr: 5.061e-04, size: 512, ETA: 0:59:51
2025-09-01 09:40:21.535 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 394/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.132s, data_time: 0.041s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 1.0, lr: 5.058e-04, size: 256, ETA: 0:59:49
2025-09-01 09:40:24.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 394/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.139s, data_time: 0.028s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.055e-04, size: 384, ETA: 0:59:46
2025-09-01 09:40:25.552 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:40:25.605 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch395
2025-09-01 09:40:28.452 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 395/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.139s, data_time: 0.003s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.051e-04, size: 576, ETA: 0:59:42
2025-09-01 09:40:31.429 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 395/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.144s, data_time: 0.010s, total_loss: 6.6, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.049e-04, size: 256, ETA: 0:59:39
2025-09-01 09:40:34.213 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 395/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, data_time: 0.055s, total_loss: 6.3, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 1.1, lr: 5.046e-04, size: 256, ETA: 0:59:37
2025-09-01 09:40:37.169 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 395/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.146s, data_time: 0.065s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.043e-04, size: 320, ETA: 0:59:34
2025-09-01 09:40:39.902 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 395/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.135s, data_time: 0.060s, total_loss: 7.6, iou_loss: 3.0, l1_loss: 0.0, conf_loss: 3.6, cls_loss: 1.1, lr: 5.041e-04, size: 320, ETA: 0:59:31
2025-09-01 09:40:42.730 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 395/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.136s, data_time: 0.028s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.039e-04, size: 448, ETA: 0:59:29
2025-09-01 09:40:43.967 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:40:49.891 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:40:51.883 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:40:53.124 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6142
2025-09-01 09:40:53.441 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5854
2025-09-01 09:40:53.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3484
2025-09-01 09:40:53.532 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5160
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.614
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.585
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.348
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.516
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:40:53.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:40:53.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:40:53.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:40:53.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:40:53.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:40:53.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:40:55.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:40:56.884 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:40:58.514 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:41:00.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:41:01.848 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:41:03.614 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:41:05.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:41:07.221 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:41:08.824 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:41:08.824 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:41:08.824 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:41:08.824 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:41:08.853 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.93 ms, Average inference time: 2.28 ms

2025-09-01 09:41:08.859 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:41:08.881 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:41:08.915 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch396
2025-09-01 09:41:11.315 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 396/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.114s, data_time: 0.022s, total_loss: 6.2, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.035e-04, size: 288, ETA: 0:59:25
2025-09-01 09:41:14.192 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 396/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.127s, data_time: 0.037s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 5.033e-04, size: 320, ETA: 0:59:22
2025-09-01 09:41:16.980 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 396/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.127s, data_time: 0.024s, total_loss: 6.4, iou_loss: 3.4, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.6, lr: 5.031e-04, size: 384, ETA: 0:59:19
2025-09-01 09:41:19.895 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 396/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.125s, data_time: 0.010s, total_loss: 5.7, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.029e-04, size: 352, ETA: 0:59:16
2025-09-01 09:41:22.729 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 396/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.139s, data_time: 0.052s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.027e-04, size: 416, ETA: 0:59:14
2025-09-01 09:41:25.600 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 396/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.131s, data_time: 0.020s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.025e-04, size: 448, ETA: 0:59:11
2025-09-01 09:41:26.906 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:41:27.022 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch397
2025-09-01 09:41:29.778 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 397/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.131s, data_time: 0.004s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.9, lr: 5.022e-04, size: 544, ETA: 0:59:07
2025-09-01 09:41:32.523 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 397/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.132s, data_time: 0.033s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.020e-04, size: 448, ETA: 0:59:04
2025-09-01 09:41:35.264 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 397/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.133s, data_time: 0.053s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.019e-04, size: 416, ETA: 0:59:01
2025-09-01 09:41:38.126 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 397/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 5.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.017e-04, size: 384, ETA: 0:58:59
2025-09-01 09:41:40.927 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 397/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.138s, data_time: 0.057s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 2.8, cls_loss: 0.9, lr: 5.016e-04, size: 480, ETA: 0:58:56
2025-09-01 09:41:43.763 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 397/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.138s, data_time: 0.037s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.014e-04, size: 352, ETA: 0:58:53
2025-09-01 09:41:44.928 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:41:45.085 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch398
2025-09-01 09:41:47.799 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 398/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.132s, data_time: 0.049s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 0.8, lr: 5.012e-04, size: 384, ETA: 0:58:49
2025-09-01 09:41:50.641 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 398/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.137s, data_time: 0.055s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.011e-04, size: 448, ETA: 0:58:47
2025-09-01 09:41:53.376 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 398/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.135s, data_time: 0.053s, total_loss: 6.9, iou_loss: 3.1, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.010e-04, size: 288, ETA: 0:58:44
2025-09-01 09:41:56.345 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 398/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.148s, data_time: 0.074s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.1, cls_loss: 0.8, lr: 5.009e-04, size: 480, ETA: 0:58:41
2025-09-01 09:41:59.181 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 398/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.141s, data_time: 0.059s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 0.9, lr: 5.007e-04, size: 512, ETA: 0:58:39
2025-09-01 09:42:01.938 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 398/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.137s, data_time: 0.058s, total_loss: 6.9, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 3.0, cls_loss: 1.1, lr: 5.006e-04, size: 288, ETA: 0:58:36
2025-09-01 09:42:03.187 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:42:03.238 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch399
2025-09-01 09:42:06.197 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 399/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.129s, data_time: 0.044s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.005e-04, size: 352, ETA: 0:58:32
2025-09-01 09:42:08.940 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 399/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.127s, data_time: 0.025s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.0, conf_loss: 2.3, cls_loss: 0.9, lr: 5.004e-04, size: 320, ETA: 0:58:29
2025-09-01 09:42:11.798 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 399/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.135s, data_time: 0.040s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.6, cls_loss: 1.0, lr: 5.004e-04, size: 480, ETA: 0:58:27
2025-09-01 09:42:14.756 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 399/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.146s, data_time: 0.047s, total_loss: 6.6, iou_loss: 2.8, l1_loss: 0.0, conf_loss: 2.9, cls_loss: 0.9, lr: 5.003e-04, size: 480, ETA: 0:58:24
2025-09-01 09:42:17.665 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 399/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.144s, data_time: 0.060s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.0, conf_loss: 2.4, cls_loss: 0.8, lr: 5.002e-04, size: 576, ETA: 0:58:22
2025-09-01 09:42:20.384 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 399/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.128s, data_time: 0.048s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.002e-04, size: 416, ETA: 0:58:19
2025-09-01 09:42:21.625 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:42:21.672 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch400
2025-09-01 09:42:21.673 | INFO     | yolox_microbt.core.trainer:before_epoch:208 - --->No mosaic aug now!
2025-09-01 09:42:21.673 | INFO     | yolox_microbt.core.trainer:before_epoch:210 - --->Add additional L1 loss now!
2025-09-01 09:42:21.674 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:42:23.601 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 400/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.006s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.8, lr: 5.001e-04, size: 256, ETA: 0:58:14
2025-09-01 09:42:25.389 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 400/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.7, lr: 5.001e-04, size: 448, ETA: 0:58:11
2025-09-01 09:42:27.180 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 400/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, 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: 384, ETA: 0:58:08
2025-09-01 09:42:28.899 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 400/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:58:05
2025-09-01 09:42:30.600 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 400/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, 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: 384, ETA: 0:58:02
2025-09-01 09:42:32.405 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 400/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.8, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 3.7, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:57:58
2025-09-01 09:42:33.190 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:42:39.014 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:42:39.932 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:42:40.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6198
2025-09-01 09:42:40.649 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5851
2025-09-01 09:42:40.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3590
2025-09-01 09:42:40.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5213
2025-09-01 09:42:40.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:42:40.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:42:40.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.620
2025-09-01 09:42:40.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.585
2025-09-01 09:42:40.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.359
2025-09-01 09:42:40.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.521
2025-09-01 09:42:40.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:42:40.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:42:40.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:42:40.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:42:40.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:42:40.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:42:40.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:42:40.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:42:40.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:42:41.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:42:42.150 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:42:42.849 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:42:43.595 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:42:44.302 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:42:45.004 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:42:45.736 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:42:46.440 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:42:47.178 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:42:47.178 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 09:42:47.178 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:42:47.178 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:42:47.185 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.89 ms, Average inference time: 2.24 ms

2025-09-01 09:42:47.186 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:42:47.210 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:42:47.243 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch401
2025-09-01 09:42:48.957 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 401/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:57:54
2025-09-01 09:42:50.622 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 401/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:57:50
2025-09-01 09:42:52.385 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 401/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:57:47
2025-09-01 09:42:54.072 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 401/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, 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: 288, ETA: 0:57:44
2025-09-01 09:42:55.863 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 401/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, 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: 0:57:41
2025-09-01 09:42:57.601 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 401/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, 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: 512, ETA: 0:57:38
2025-09-01 09:42:58.398 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:42:58.444 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch402
2025-09-01 09:43:00.222 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 402/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:57:33
2025-09-01 09:43:02.022 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 402/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, 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: 0:57:30
2025-09-01 09:43:03.748 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 402/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.5, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:57:27
2025-09-01 09:43:05.530 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 402/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 3.9, iou_loss: 1.4, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:57:24
2025-09-01 09:43:07.240 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 402/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.7, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:57:20
2025-09-01 09:43:09.024 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 402/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 9.4, iou_loss: 2.8, l1_loss: 1.4, conf_loss: 4.2, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:57:17
2025-09-01 09:43:09.820 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:43:09.881 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch403
2025-09-01 09:43:11.634 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 403/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:57:13
2025-09-01 09:43:13.417 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 403/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:57:09
2025-09-01 09:43:15.190 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 403/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:57:06
2025-09-01 09:43:16.946 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 403/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:57:03
2025-09-01 09:43:18.742 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 403/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 10.3, iou_loss: 2.9, l1_loss: 1.7, conf_loss: 4.8, cls_loss: 1.0, lr: 5.000e-04, size: 512, ETA: 0:57:00
2025-09-01 09:43:20.501 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 403/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:56:57
2025-09-01 09:43:21.275 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:43:21.310 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch404
2025-09-01 09:43:23.105 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 404/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:56:52
2025-09-01 09:43:24.895 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 404/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:56:49
2025-09-01 09:43:26.692 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 404/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:56:46
2025-09-01 09:43:28.402 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 404/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:56:43
2025-09-01 09:43:30.131 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 404/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 1.3, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:56:39
2025-09-01 09:43:31.816 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 404/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:56:36
2025-09-01 09:43:32.539 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:43:32.596 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch405
2025-09-01 09:43:34.359 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 405/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 1.1, lr: 5.000e-04, size: 416, ETA: 0:56:32
2025-09-01 09:43:36.150 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 405/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, 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: 352, ETA: 0:56:28
2025-09-01 09:43:37.897 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 405/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:56:25
2025-09-01 09:43:39.636 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 405/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:56:22
2025-09-01 09:43:41.407 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 405/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:56:19
2025-09-01 09:43:43.207 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 405/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:56:16
2025-09-01 09:43:43.996 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:43:50.017 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:43:50.809 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:43:51.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6157
2025-09-01 09:43:51.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5861
2025-09-01 09:43:51.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3809
2025-09-01 09:43:51.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5276
2025-09-01 09:43:51.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:43:51.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:43:51.448 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.616
2025-09-01 09:43:51.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.586
2025-09-01 09:43:51.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.381
2025-09-01 09:43:51.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.528
2025-09-01 09:43:51.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:43:51.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:43:51.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:43:51.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:43:51.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:43:51.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:43:51.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:43:51.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:43:51.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:43:52.098 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:43:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:43:53.530 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:43:54.182 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:43:54.866 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:43:55.507 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:43:56.143 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:43:56.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:43:57.452 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:43:57.452 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 09:43:57.452 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 09:43:57.452 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:43:57.459 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.91 ms, Average inference time: 2.28 ms

2025-09-01 09:43:57.461 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:43:57.488 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:43:57.520 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch406
2025-09-01 09:43:59.264 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 406/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 9.7, iou_loss: 2.9, l1_loss: 1.6, conf_loss: 4.1, cls_loss: 1.1, lr: 5.000e-04, size: 512, ETA: 0:56:11
2025-09-01 09:44:01.062 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 406/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.8, iou_loss: 1.8, l1_loss: 1.1, conf_loss: 3.3, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:56:08
2025-09-01 09:44:02.865 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 406/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:56:05
2025-09-01 09:44:04.587 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 406/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:56:02
2025-09-01 09:44:06.371 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 406/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:55:59
2025-09-01 09:44:08.086 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 406/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:55:55
2025-09-01 09:44:08.901 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:44:08.941 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch407
2025-09-01 09:44:10.792 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 407/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:55:51
2025-09-01 09:44:12.587 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 407/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:55:48
2025-09-01 09:44:14.485 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 407/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:55:45
2025-09-01 09:44:16.173 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 407/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, 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: 352, ETA: 0:55:41
2025-09-01 09:44:18.009 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 407/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:55:38
2025-09-01 09:44:19.761 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 407/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.6, iou_loss: 3.0, l1_loss: 1.1, conf_loss: 3.3, cls_loss: 1.1, lr: 5.000e-04, size: 384, ETA: 0:55:35
2025-09-01 09:44:20.553 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:44:20.595 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch408
2025-09-01 09:44:22.458 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 408/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:55:31
2025-09-01 09:44:24.215 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 408/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.5, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 6.5, cls_loss: 0.0, lr: 5.000e-04, size: 544, ETA: 0:55:27
2025-09-01 09:44:25.932 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 408/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, 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: 384, ETA: 0:55:24
2025-09-01 09:44:27.687 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 408/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 1.1, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:55:21
2025-09-01 09:44:29.443 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 408/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:55:18
2025-09-01 09:44:31.223 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 408/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:55:15
2025-09-01 09:44:31.999 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:44:32.040 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch409
2025-09-01 09:44:33.748 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 409/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 8.4, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 4.1, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:55:10
2025-09-01 09:44:35.420 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 409/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:55:07
2025-09-01 09:44:37.233 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 409/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.1, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.4, lr: 5.000e-04, size: 544, ETA: 0:55:04
2025-09-01 09:44:39.036 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 409/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:55:01
2025-09-01 09:44:40.772 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 409/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:54:58
2025-09-01 09:44:42.521 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 409/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:54:55
2025-09-01 09:44:43.295 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:44:43.356 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch410
2025-09-01 09:44:45.175 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 410/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.006s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 1.4, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:54:50
2025-09-01 09:44:47.009 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 410/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:54:47
2025-09-01 09:44:48.705 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 410/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:54:44
2025-09-01 09:44:50.457 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 410/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:54:41
2025-09-01 09:44:52.351 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 410/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.091s, 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: 448, ETA: 0:54:38
2025-09-01 09:44:54.128 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 410/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 4.9, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:54:34
2025-09-01 09:44:54.902 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:45:00.914 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:45:01.680 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:45:02.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6314
2025-09-01 09:45:02.275 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.6104
2025-09-01 09:45:02.337 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3958
2025-09-01 09:45:02.338 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5458
2025-09-01 09:45:02.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:45:02.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:45:02.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.631
2025-09-01 09:45:02.339 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.610
2025-09-01 09:45:02.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.396
2025-09-01 09:45:02.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.546
2025-09-01 09:45:02.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:45:02.340 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:45:02.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:45:02.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:45:02.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:45:02.341 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:45:02.342 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:45:02.342 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:45:02.342 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:45:03.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:45:03.639 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:45:04.233 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:45:04.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:45:05.467 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:45:06.054 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:45:06.658 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:45:07.296 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:45:07.904 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:45:07.904 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 09:45:07.904 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.55
2025-09-01 09:45:07.904 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:45:07.911 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.40 ms, Average NMS time: 0.95 ms, Average inference time: 2.36 ms

2025-09-01 09:45:07.912 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:45:07.936 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:45:07.969 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch411
2025-09-01 09:45:09.672 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 411/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:54:30
2025-09-01 09:45:11.504 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 411/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:54:27
2025-09-01 09:45:13.242 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 411/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:54:24
2025-09-01 09:45:14.987 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 411/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:54:21
2025-09-01 09:45:16.751 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 411/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, 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: 576, ETA: 0:54:17
2025-09-01 09:45:18.554 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 411/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:54:14
2025-09-01 09:45:19.343 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:45:19.398 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch412
2025-09-01 09:45:21.148 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 412/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:54:10
2025-09-01 09:45:22.904 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 412/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:54:07
2025-09-01 09:45:24.666 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 412/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:54:04
2025-09-01 09:45:26.478 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 412/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:54:01
2025-09-01 09:45:28.254 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 412/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:53:57
2025-09-01 09:45:30.083 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 412/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:53:54
2025-09-01 09:45:30.856 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:45:30.899 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch413
2025-09-01 09:45:32.674 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 413/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 7.3, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 3.9, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:53:50
2025-09-01 09:45:34.444 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 413/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.6, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 3.8, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:53:47
2025-09-01 09:45:36.187 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 413/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:53:44
2025-09-01 09:45:38.017 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 413/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 1.4, conf_loss: 3.1, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:53:41
2025-09-01 09:45:39.766 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 413/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:53:37
2025-09-01 09:45:41.544 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 413/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:53:34
2025-09-01 09:45:42.375 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:45:42.424 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch414
2025-09-01 09:45:44.207 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 414/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.1, l1_loss: 1.5, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:53:30
2025-09-01 09:45:45.976 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 414/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:53:27
2025-09-01 09:45:47.821 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 414/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:53:24
2025-09-01 09:45:49.586 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 414/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 1.2, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:53:21
2025-09-01 09:45:51.352 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 414/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:53:17
2025-09-01 09:45:53.116 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 414/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:53:14
2025-09-01 09:45:53.887 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:45:53.926 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch415
2025-09-01 09:45:55.624 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 415/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 1.8, cls_loss: 0.4, lr: 5.000e-04, size: 352, ETA: 0:53:10
2025-09-01 09:45:57.393 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 415/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.8, iou_loss: 2.9, l1_loss: 1.9, conf_loss: 3.1, cls_loss: 0.9, lr: 5.000e-04, size: 512, ETA: 0:53:07
2025-09-01 09:45:59.151 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 415/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.4, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:53:04
2025-09-01 09:46:00.812 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 415/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.0, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:53:00
2025-09-01 09:46:02.708 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 415/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 3.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:52:57
2025-09-01 09:46:04.441 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 415/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:52:54
2025-09-01 09:46:05.238 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:46:11.041 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:46:12.048 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:46:12.675 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6095
2025-09-01 09:46:12.844 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5777
2025-09-01 09:46:12.919 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3700
2025-09-01 09:46:12.920 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5191
2025-09-01 09:46:12.920 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:46:12.920 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:46:12.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.609
2025-09-01 09:46:12.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.578
2025-09-01 09:46:12.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.370
2025-09-01 09:46:12.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.519
2025-09-01 09:46:12.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:46:12.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:46:12.921 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:46:12.922 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:46:12.922 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:46:12.922 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:46:12.922 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:46:12.922 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:46:12.922 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:46:13.725 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:46:14.563 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:46:15.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:46:16.214 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:46:17.012 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:46:17.843 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:46:18.649 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:46:19.487 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:46:20.287 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:46:20.287 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:46:20.287 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:46:20.287 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:46:20.294 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.91 ms, Average inference time: 2.27 ms

2025-09-01 09:46:20.295 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:46:20.321 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:46:20.351 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch416
2025-09-01 09:46:22.052 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 416/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.005s, total_loss: 3.1, iou_loss: 1.3, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:52:50
2025-09-01 09:46:23.781 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 416/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:52:47
2025-09-01 09:46:25.568 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 416/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:52:44
2025-09-01 09:46:27.258 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 416/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, 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: 448, ETA: 0:52:41
2025-09-01 09:46:29.064 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 416/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:52:37
2025-09-01 09:46:30.804 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 416/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:52:34
2025-09-01 09:46:31.582 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:46:31.618 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch417
2025-09-01 09:46:33.316 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 417/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.003s, total_loss: 3.5, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:52:30
2025-09-01 09:46:35.140 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 417/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:52:27
2025-09-01 09:46:36.847 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 417/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:52:24
2025-09-01 09:46:38.560 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 417/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 3.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:52:21
2025-09-01 09:46:40.314 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 417/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 1.1, conf_loss: 1.6, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:52:17
2025-09-01 09:46:42.157 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 417/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:52:14
2025-09-01 09:46:42.997 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:46:43.043 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch418
2025-09-01 09:46:44.829 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 418/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.003s, 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: 448, ETA: 0:52:10
2025-09-01 09:46:46.585 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 418/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:52:07
2025-09-01 09:46:48.331 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 418/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:52:04
2025-09-01 09:46:50.124 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 418/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, 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: 0:52:01
2025-09-01 09:46:51.853 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 418/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 2.5, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:51:58
2025-09-01 09:46:53.592 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 418/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:51:55
2025-09-01 09:46:54.457 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:46:54.497 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch419
2025-09-01 09:46:56.301 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 419/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:51:50
2025-09-01 09:46:58.020 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 419/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.9, lr: 5.000e-04, size: 448, ETA: 0:51:47
2025-09-01 09:46:59.740 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 419/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.7, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:51:44
2025-09-01 09:47:01.418 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 419/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.001s, total_loss: 4.3, iou_loss: 1.4, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:51:41
2025-09-01 09:47:03.205 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 419/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 7.1, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:51:38
2025-09-01 09:47:04.931 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 419/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:51:35
2025-09-01 09:47:05.711 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:47:05.749 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch420
2025-09-01 09:47:07.593 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 420/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:51:30
2025-09-01 09:47:09.448 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 420/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:51:27
2025-09-01 09:47:11.159 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 420/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:51:24
2025-09-01 09:47:12.934 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 420/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 4.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:51:21
2025-09-01 09:47:14.760 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 420/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:51:18
2025-09-01 09:47:16.435 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 420/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.4, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.4, lr: 5.000e-04, size: 480, ETA: 0:51:15
2025-09-01 09:47:17.288 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:47:23.241 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:47:24.057 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:47:24.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6163
2025-09-01 09:47:24.727 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5683
2025-09-01 09:47:24.759 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3428
2025-09-01 09:47:24.759 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5091
2025-09-01 09:47:24.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:47:24.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:47:24.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.616
2025-09-01 09:47:24.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.568
2025-09-01 09:47:24.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.343
2025-09-01 09:47:24.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.509
2025-09-01 09:47:24.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:47:24.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:47:24.760 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:47:24.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:47:24.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:47:24.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:47:24.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:47:24.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:47:24.761 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:47:25.476 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:47:26.096 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:47:26.752 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:47:27.369 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:47:27.992 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:47:28.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:47:29.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:47:29.883 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:47:30.540 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:47:30.540 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 09:47:30.540 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 09:47:30.541 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:47:30.547 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.93 ms, Average inference time: 2.31 ms

2025-09-01 09:47:30.553 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:47:30.574 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:47:30.604 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch421
2025-09-01 09:47:32.333 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 421/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:51:11
2025-09-01 09:47:34.038 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 421/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:51:07
2025-09-01 09:47:35.793 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 421/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, 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: 416, ETA: 0:51:04
2025-09-01 09:47:37.576 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 421/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:51:01
2025-09-01 09:47:39.253 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 421/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:50:58
2025-09-01 09:47:41.095 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 421/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:50:55
2025-09-01 09:47:41.891 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:47:41.928 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch422
2025-09-01 09:47:43.682 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 422/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, 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: 0:50:51
2025-09-01 09:47:45.515 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 422/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.4, iou_loss: 2.3, l1_loss: 1.7, conf_loss: 3.4, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:50:48
2025-09-01 09:47:47.213 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 422/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:50:45
2025-09-01 09:47:49.008 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 422/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:50:42
2025-09-01 09:47:50.779 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 422/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:50:39
2025-09-01 09:47:52.516 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 422/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:50:36
2025-09-01 09:47:53.288 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:47:53.325 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch423
2025-09-01 09:47:55.080 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 423/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:50:31
2025-09-01 09:47:56.880 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 423/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:50:28
2025-09-01 09:47:58.720 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 423/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.1, l1_loss: 1.0, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:50:25
2025-09-01 09:48:00.456 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 423/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:50:22
2025-09-01 09:48:02.293 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 423/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 3.4, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:50:19
2025-09-01 09:48:04.141 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 423/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:50:16
2025-09-01 09:48:04.957 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:48:05.002 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch424
2025-09-01 09:48:06.749 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 424/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:50:12
2025-09-01 09:48:08.560 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 424/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.7, l1_loss: 1.2, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:50:09
2025-09-01 09:48:10.300 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 424/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:50:06
2025-09-01 09:48:12.112 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 424/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:50:03
2025-09-01 09:48:13.840 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 424/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:50:00
2025-09-01 09:48:15.611 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 424/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:49:57
2025-09-01 09:48:16.364 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:48:16.414 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch425
2025-09-01 09:48:18.141 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 425/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 2.8, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 0.6, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:49:52
2025-09-01 09:48:19.938 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 425/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 11.3, iou_loss: 3.6, l1_loss: 1.4, conf_loss: 5.5, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:49:49
2025-09-01 09:48:21.734 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 425/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.5, l1_loss: 1.4, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:49:46
2025-09-01 09:48:23.515 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 425/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, 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: 416, ETA: 0:49:43
2025-09-01 09:48:25.278 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 425/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:49:40
2025-09-01 09:48:27.028 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 425/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 0.8, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:49:37
2025-09-01 09:48:27.818 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:48:33.814 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:48:34.494 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:48:34.897 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6269
2025-09-01 09:48:35.025 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5816
2025-09-01 09:48:35.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3924
2025-09-01 09:48:35.063 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5336
2025-09-01 09:48:35.063 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:48:35.063 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:48:35.063 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.627
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.582
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.392
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.534
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:48:35.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:48:35.065 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:48:35.681 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:48:36.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:48:36.847 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:48:37.454 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:48:38.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:48:38.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:48:39.256 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:48:39.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:48:40.415 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:48:40.415 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 09:48:40.415 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 09:48:40.415 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:48:40.422 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.87 ms, Average inference time: 2.24 ms

2025-09-01 09:48:40.423 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:48:40.446 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:48:40.478 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch426
2025-09-01 09:48:42.168 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 426/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:49:33
2025-09-01 09:48:43.978 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 426/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:49:30
2025-09-01 09:48:45.751 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 426/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:49:27
2025-09-01 09:48:47.508 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 426/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:49:24
2025-09-01 09:48:49.200 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 426/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:49:20
2025-09-01 09:48:51.041 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 426/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, 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: 576, ETA: 0:49:18
2025-09-01 09:48:51.917 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:48:51.966 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch427
2025-09-01 09:48:53.683 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 427/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 10.9, iou_loss: 2.8, l1_loss: 1.3, conf_loss: 6.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:49:13
2025-09-01 09:48:55.524 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 427/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:49:10
2025-09-01 09:48:57.442 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 427/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.094s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:49:07
2025-09-01 09:48:59.164 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 427/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.004s, 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: 448, ETA: 0:49:04
2025-09-01 09:49:01.067 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 427/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.093s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:49:01
2025-09-01 09:49:02.918 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 427/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:48:58
2025-09-01 09:49:03.911 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:49:03.968 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch428
2025-09-01 09:49:05.844 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 428/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:48:54
2025-09-01 09:49:07.652 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 428/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.004s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:48:51
2025-09-01 09:49:09.507 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 428/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.004s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:48:48
2025-09-01 09:49:11.256 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 428/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:48:45
2025-09-01 09:49:13.023 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 428/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.004s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:48:42
2025-09-01 09:49:14.881 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 428/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.004s, 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: 448, ETA: 0:48:39
2025-09-01 09:49:15.736 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:49:15.793 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch429
2025-09-01 09:49:17.594 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 429/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:48:35
2025-09-01 09:49:19.424 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 429/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:48:32
2025-09-01 09:49:21.218 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 429/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:48:29
2025-09-01 09:49:22.964 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 429/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:48:26
2025-09-01 09:49:24.756 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 429/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 5.9, iou_loss: 1.9, l1_loss: 1.3, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:48:23
2025-09-01 09:49:26.492 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 429/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:48:20
2025-09-01 09:49:27.387 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:49:27.431 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch430
2025-09-01 09:49:29.187 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 430/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.9, cls_loss: 1.0, lr: 5.000e-04, size: 416, ETA: 0:48:15
2025-09-01 09:49:30.974 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 430/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, 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: 416, ETA: 0:48:12
2025-09-01 09:49:32.689 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 430/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:48:09
2025-09-01 09:49:34.403 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 430/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:48:06
2025-09-01 09:49:36.152 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 430/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:48:03
2025-09-01 09:49:37.917 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 430/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:48:00
2025-09-01 09:49:38.729 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:49:44.845 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:49:45.772 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:49:46.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6173
2025-09-01 09:49:46.538 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5720
2025-09-01 09:49:46.617 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3881
2025-09-01 09:49:46.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5258
2025-09-01 09:49:46.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:49:46.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:49:46.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.617
2025-09-01 09:49:46.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.572
2025-09-01 09:49:46.618 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.388
2025-09-01 09:49:46.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.526
2025-09-01 09:49:46.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:49:46.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:49:46.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:49:46.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:49:46.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:49:46.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:49:46.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:49:46.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:49:46.620 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:49:47.429 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:49:48.252 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:49:49.067 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:49:50.062 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:49:50.875 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:49:51.734 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:49:52.599 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:49:53.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:49:54.320 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:49:54.320 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 09:49:54.320 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 09:49:54.321 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:49:54.330 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.89 ms, Average inference time: 2.25 ms

2025-09-01 09:49:54.331 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:49:54.359 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:49:54.399 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch431
2025-09-01 09:49:55.987 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 431/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.076s, data_time: 0.002s, total_loss: 2.8, iou_loss: 1.1, l1_loss: 0.3, conf_loss: 1.0, cls_loss: 0.4, lr: 5.000e-04, size: 320, ETA: 0:47:56
2025-09-01 09:49:57.688 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 431/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 3.1, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:47:53
2025-09-01 09:49:59.493 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 431/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:47:50
2025-09-01 09:50:01.308 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 431/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:47:47
2025-09-01 09:50:03.131 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 431/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.3, l1_loss: 1.5, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:47:44
2025-09-01 09:50:04.920 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 431/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.9, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:47:41
2025-09-01 09:50:05.702 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:50:05.742 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch432
2025-09-01 09:50:07.413 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 432/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:47:37
2025-09-01 09:50:09.159 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 432/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:47:34
2025-09-01 09:50:10.864 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 432/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:47:31
2025-09-01 09:50:12.604 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 432/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 2.8, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:47:28
2025-09-01 09:50:14.359 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 432/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 2.5, cls_loss: 1.0, lr: 5.000e-04, size: 288, ETA: 0:47:25
2025-09-01 09:50:16.187 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 432/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:47:22
2025-09-01 09:50:17.014 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:50:17.059 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch433
2025-09-01 09:50:18.762 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 433/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:47:17
2025-09-01 09:50:20.545 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 433/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:47:14
2025-09-01 09:50:22.336 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 433/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:47:11
2025-09-01 09:50:24.162 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 433/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.3, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.4, lr: 5.000e-04, size: 480, ETA: 0:47:08
2025-09-01 09:50:25.893 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 433/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 1.1, lr: 5.000e-04, size: 256, ETA: 0:47:06
2025-09-01 09:50:27.649 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 433/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, 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: 256, ETA: 0:47:03
2025-09-01 09:50:28.403 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:50:28.471 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch434
2025-09-01 09:50:30.201 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 434/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:46:58
2025-09-01 09:50:31.978 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 434/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:46:55
2025-09-01 09:50:33.680 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 434/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.1, l1_loss: 1.6, conf_loss: 3.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:46:52
2025-09-01 09:50:35.511 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 434/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.4, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:46:49
2025-09-01 09:50:37.289 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 434/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:46:46
2025-09-01 09:50:39.062 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 434/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:46:43
2025-09-01 09:50:39.908 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:50:39.958 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch435
2025-09-01 09:50:41.697 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 435/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, 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: 352, ETA: 0:46:39
2025-09-01 09:50:43.471 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 435/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:46:36
2025-09-01 09:50:45.208 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 435/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:46:33
2025-09-01 09:50:47.016 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 435/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.5, l1_loss: 2.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:46:30
2025-09-01 09:50:48.779 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 435/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:46:27
2025-09-01 09:50:50.541 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 435/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, 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: 288, ETA: 0:46:24
2025-09-01 09:50:51.356 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:50:57.007 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:50:57.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:50:58.372 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6231
2025-09-01 09:50:58.474 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5810
2025-09-01 09:50:58.554 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4110
2025-09-01 09:50:58.555 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5384
2025-09-01 09:50:58.555 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:50:58.555 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:50:58.555 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.623
2025-09-01 09:50:58.555 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.581
2025-09-01 09:50:58.555 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.411
2025-09-01 09:50:58.556 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.538
2025-09-01 09:50:58.556 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:50:58.556 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:50:58.556 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:50:58.556 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:50:58.556 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:50:58.556 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:50:58.556 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:50:58.556 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:50:58.557 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:50:59.215 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:50:59.912 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:51:00.604 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:51:01.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:51:01.902 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:51:02.727 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:51:03.373 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:51:04.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:51:04.655 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:51:04.655 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 09:51:04.656 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-09-01 09:51:04.656 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:51:04.663 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.89 ms, Average inference time: 2.24 ms

2025-09-01 09:51:04.664 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:51:04.740 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:51:04.775 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch436
2025-09-01 09:51:06.383 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 436/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.077s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:46:20
2025-09-01 09:51:08.135 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 436/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:46:17
2025-09-01 09:51:09.860 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 436/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:46:14
2025-09-01 09:51:11.662 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 436/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:46:11
2025-09-01 09:51:13.417 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 436/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:46:08
2025-09-01 09:51:15.146 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 436/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 0.7, cls_loss: 0.4, lr: 5.000e-04, size: 320, ETA: 0:46:05
2025-09-01 09:51:16.001 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:51:16.052 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch437
2025-09-01 09:51:17.836 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 437/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, 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: 448, ETA: 0:46:01
2025-09-01 09:51:19.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 437/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, 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: 544, ETA: 0:45:58
2025-09-01 09:51:21.520 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 437/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 1.0, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:45:55
2025-09-01 09:51:23.407 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 437/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, 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: 256, ETA: 0:45:52
2025-09-01 09:51:25.114 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 437/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:45:49
2025-09-01 09:51:26.993 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 437/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:45:46
2025-09-01 09:51:27.878 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:51:27.938 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch438
2025-09-01 09:51:29.669 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 438/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.2, l1_loss: 1.2, conf_loss: 3.1, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:45:42
2025-09-01 09:51:31.443 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 438/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:45:39
2025-09-01 09:51:33.297 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 438/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:45:36
2025-09-01 09:51:34.935 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 438/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 1.2, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:45:33
2025-09-01 09:51:36.704 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 438/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.8, l1_loss: 1.4, conf_loss: 3.1, cls_loss: 1.3, lr: 5.000e-04, size: 352, ETA: 0:45:30
2025-09-01 09:51:38.388 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 438/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:45:27
2025-09-01 09:51:39.220 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:51:39.291 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch439
2025-09-01 09:51:41.080 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 439/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.001s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:45:23
2025-09-01 09:51:42.755 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 439/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:45:20
2025-09-01 09:51:44.486 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 439/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 0.8, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:45:17
2025-09-01 09:51:46.109 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 439/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:45:14
2025-09-01 09:51:47.846 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 439/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:45:11
2025-09-01 09:51:49.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 439/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:45:08
2025-09-01 09:51:50.462 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:51:50.510 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch440
2025-09-01 09:51:52.320 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 440/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:45:04
2025-09-01 09:51:53.983 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 440/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:45:01
2025-09-01 09:51:55.631 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 440/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:44:58
2025-09-01 09:51:57.386 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 440/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:44:55
2025-09-01 09:51:59.118 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 440/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, 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: 320, ETA: 0:44:52
2025-09-01 09:52:00.819 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 440/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:44:49
2025-09-01 09:52:01.588 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:52:07.502 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:52:08.314 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:52:08.769 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6249
2025-09-01 09:52:08.904 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5833
2025-09-01 09:52:08.939 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4363
2025-09-01 09:52:08.940 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5482
2025-09-01 09:52:08.940 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:52:08.940 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:52:08.940 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.625
2025-09-01 09:52:08.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.583
2025-09-01 09:52:08.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.436
2025-09-01 09:52:08.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.548
2025-09-01 09:52:08.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:52:08.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:52:08.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:52:08.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:52:08.941 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:52:08.942 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:52:08.942 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:52:08.942 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:52:08.942 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:52:09.648 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:52:10.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:52:10.957 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:52:11.566 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:52:12.187 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:52:12.924 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:52:13.535 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:52:14.140 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:52:14.746 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:52:14.746 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.31
2025-09-01 09:52:14.747 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.55
2025-09-01 09:52:14.747 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:52:14.754 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.92 ms, Average inference time: 2.30 ms

2025-09-01 09:52:14.754 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:52:14.783 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:52:14.814 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch441
2025-09-01 09:52:16.449 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 441/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:44:44
2025-09-01 09:52:18.157 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 441/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:44:41
2025-09-01 09:52:19.905 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 441/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, 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: 544, ETA: 0:44:39
2025-09-01 09:52:21.628 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 441/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 3.4, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:44:36
2025-09-01 09:52:23.427 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 441/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:44:33
2025-09-01 09:52:25.195 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 441/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:44:30
2025-09-01 09:52:25.982 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:52:26.107 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch442
2025-09-01 09:52:27.769 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 442/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:44:25
2025-09-01 09:52:29.635 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 442/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:44:23
2025-09-01 09:52:31.475 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 442/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:44:20
2025-09-01 09:52:33.222 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 442/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:44:17
2025-09-01 09:52:34.907 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 442/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, 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: 416, ETA: 0:44:14
2025-09-01 09:52:36.751 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 442/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:44:11
2025-09-01 09:52:37.581 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:52:37.622 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch443
2025-09-01 09:52:39.412 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 443/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:44:07
2025-09-01 09:52:41.294 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 443/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 8.8, iou_loss: 3.2, l1_loss: 1.6, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:44:04
2025-09-01 09:52:43.086 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 443/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 1.1, lr: 5.000e-04, size: 416, ETA: 0:44:01
2025-09-01 09:52:44.803 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 443/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:43:58
2025-09-01 09:52:46.577 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 443/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, 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: 384, ETA: 0:43:55
2025-09-01 09:52:48.371 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 443/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.5, l1_loss: 0.3, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:43:52
2025-09-01 09:52:49.130 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:52:49.208 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch444
2025-09-01 09:52:51.041 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 444/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:43:48
2025-09-01 09:52:52.881 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 444/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:43:45
2025-09-01 09:52:54.628 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 444/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, 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: 448, ETA: 0:43:42
2025-09-01 09:52:56.384 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 444/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:43:39
2025-09-01 09:52:58.211 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 444/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:43:36
2025-09-01 09:53:00.038 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 444/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.7, l1_loss: 1.4, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:43:33
2025-09-01 09:53:00.848 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:53:00.888 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch445
2025-09-01 09:53:02.624 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 445/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:43:29
2025-09-01 09:53:04.386 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 445/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:43:26
2025-09-01 09:53:06.183 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 445/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:43:23
2025-09-01 09:53:07.983 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 445/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.5, iou_loss: 3.0, l1_loss: 1.2, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:43:20
2025-09-01 09:53:09.759 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 445/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:43:17
2025-09-01 09:53:11.541 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 445/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:43:15
2025-09-01 09:53:12.286 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:53:18.303 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:53:18.944 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:53:19.386 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5759
2025-09-01 09:53:19.541 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5631
2025-09-01 09:53:19.624 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3453
2025-09-01 09:53:19.624 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4947
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.576
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.563
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.345
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.495
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:53:19.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:53:19.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:53:19.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:53:19.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:53:19.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:53:19.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:53:20.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:53:20.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:53:21.141 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:53:21.639 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:53:22.131 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:53:22.664 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:53:23.163 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:53:23.662 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:53:24.161 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:53:24.162 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 09:53:24.162 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-09-01 09:53:24.162 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:53:24.168 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.94 ms, Average inference time: 2.31 ms

2025-09-01 09:53:24.169 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:53:24.196 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:53:24.226 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch446
2025-09-01 09:53:25.959 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 446/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:43:10
2025-09-01 09:53:27.631 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 446/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:43:07
2025-09-01 09:53:29.305 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 446/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.3, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:43:04
2025-09-01 09:53:31.042 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 446/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:43:02
2025-09-01 09:53:32.800 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 446/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:42:59
2025-09-01 09:53:34.622 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 446/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:42:56
2025-09-01 09:53:35.424 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:53:35.478 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch447
2025-09-01 09:53:37.231 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 447/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:42:52
2025-09-01 09:53:39.004 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 447/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:42:49
2025-09-01 09:53:40.899 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 447/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:42:46
2025-09-01 09:53:42.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 447/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:42:43
2025-09-01 09:53:44.447 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 447/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:42:40
2025-09-01 09:53:46.275 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 447/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:42:37
2025-09-01 09:53:47.051 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:53:47.101 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch448
2025-09-01 09:53:48.845 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 448/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:42:33
2025-09-01 09:53:50.533 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 448/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 4.2, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:42:30
2025-09-01 09:53:52.349 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 448/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:42:27
2025-09-01 09:53:54.084 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 448/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:42:24
2025-09-01 09:53:55.809 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 448/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 18.9, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 18.9, cls_loss: 0.0, lr: 5.000e-04, size: 448, ETA: 0:42:21
2025-09-01 09:53:57.610 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 448/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.003s, 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: 448, ETA: 0:42:18
2025-09-01 09:53:58.368 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:53:58.489 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch449
2025-09-01 09:54:00.246 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 449/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:42:14
2025-09-01 09:54:02.005 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 449/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.1, l1_loss: 1.0, conf_loss: 3.6, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:42:11
2025-09-01 09:54:03.763 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 449/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:42:08
2025-09-01 09:54:05.546 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 449/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:42:05
2025-09-01 09:54:07.285 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 449/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, 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: 0.7, lr: 5.000e-04, size: 352, ETA: 0:42:03
2025-09-01 09:54:09.017 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 449/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, 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: 544, ETA: 0:42:00
2025-09-01 09:54:09.827 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:54:09.876 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch450
2025-09-01 09:54:11.576 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 450/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:41:56
2025-09-01 09:54:13.237 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 450/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:41:53
2025-09-01 09:54:14.991 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 450/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:41:50
2025-09-01 09:54:16.728 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 450/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:41:47
2025-09-01 09:54:18.398 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 450/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:41:44
2025-09-01 09:54:20.193 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 450/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:41:41
2025-09-01 09:54:20.967 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:54:26.968 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:54:27.732 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:54:28.246 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6270
2025-09-01 09:54:28.355 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5726
2025-09-01 09:54:28.432 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3942
2025-09-01 09:54:28.432 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5313
2025-09-01 09:54:28.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:54:28.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:54:28.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.627
2025-09-01 09:54:28.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.573
2025-09-01 09:54:28.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.394
2025-09-01 09:54:28.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.531
2025-09-01 09:54:28.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:54:28.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:54:28.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:54:28.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:54:28.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:54:28.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:54:28.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:54:28.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:54:28.434 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:54:29.089 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:54:29.746 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:54:30.430 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:54:31.151 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:54:31.802 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:54:32.447 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:54:33.122 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:54:33.749 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:54:34.382 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:54:34.383 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 09:54:34.383 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 09:54:34.383 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:54:34.390 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.91 ms, Average inference time: 2.27 ms

2025-09-01 09:54:34.391 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:54:34.418 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:54:34.450 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch451
2025-09-01 09:54:36.107 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 451/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, 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: 480, ETA: 0:41:37
2025-09-01 09:54:37.886 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 451/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:41:34
2025-09-01 09:54:39.757 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 451/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:41:31
2025-09-01 09:54:41.557 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 451/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:41:28
2025-09-01 09:54:43.235 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 451/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, 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: 448, ETA: 0:41:25
2025-09-01 09:54:45.093 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 451/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.005s, total_loss: 6.7, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:41:22
2025-09-01 09:54:45.886 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:54:45.942 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch452
2025-09-01 09:54:47.725 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 452/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 1.6, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:41:18
2025-09-01 09:54:49.565 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 452/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:41:15
2025-09-01 09:54:51.343 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 452/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.3, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:41:13
2025-09-01 09:54:53.038 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 452/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:41:10
2025-09-01 09:54:54.808 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 452/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 3.0, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:41:07
2025-09-01 09:54:56.594 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 452/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:41:04
2025-09-01 09:54:57.399 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:54:57.447 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch453
2025-09-01 09:54:59.115 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 453/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 1.2, lr: 5.000e-04, size: 352, ETA: 0:41:00
2025-09-01 09:55:00.898 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 453/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:40:57
2025-09-01 09:55:02.661 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 453/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:40:54
2025-09-01 09:55:04.321 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 453/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:40:51
2025-09-01 09:55:06.153 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 453/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 4.2, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:40:48
2025-09-01 09:55:08.126 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 453/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:40:45
2025-09-01 09:55:08.980 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:55:09.020 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch454
2025-09-01 09:55:10.785 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 454/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.5, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:40:41
2025-09-01 09:55:12.604 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 454/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, 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: 416, ETA: 0:40:38
2025-09-01 09:55:14.357 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 454/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 2.6, iou_loss: 1.0, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.4, lr: 5.000e-04, size: 320, ETA: 0:40:36
2025-09-01 09:55:16.062 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 454/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:40:33
2025-09-01 09:55:17.746 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 454/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:40:30
2025-09-01 09:55:19.511 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 454/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:40:27
2025-09-01 09:55:20.328 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:55:20.368 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch455
2025-09-01 09:55:22.205 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 455/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:40:23
2025-09-01 09:55:23.972 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 455/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:40:20
2025-09-01 09:55:25.746 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 455/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:40:17
2025-09-01 09:55:27.549 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 455/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 8.1, iou_loss: 3.3, l1_loss: 1.3, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:40:14
2025-09-01 09:55:29.242 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 455/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:40:11
2025-09-01 09:55:31.037 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 455/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 3.5, iou_loss: 1.1, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:40:09
2025-09-01 09:55:31.819 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:55:37.585 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:55:38.299 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:55:38.713 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6180
2025-09-01 09:55:38.797 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5720
2025-09-01 09:55:38.869 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3692
2025-09-01 09:55:38.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5197
2025-09-01 09:55:38.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:55:38.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:55:38.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.618
2025-09-01 09:55:38.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.572
2025-09-01 09:55:38.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.369
2025-09-01 09:55:38.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.520
2025-09-01 09:55:38.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:55:38.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:55:38.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:55:38.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:55:38.871 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:55:38.872 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:55:38.872 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:55:38.872 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:55:38.872 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:55:39.449 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:55:40.022 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:55:40.594 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:55:41.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:55:41.775 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:55:42.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:55:42.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:55:43.533 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:55:44.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:55:44.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 09:55:44.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 09:55:44.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:55:44.136 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.40 ms, Average NMS time: 0.88 ms, Average inference time: 2.28 ms

2025-09-01 09:55:44.137 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:55:44.164 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:55:44.201 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch456
2025-09-01 09:55:45.956 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 456/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:40:04
2025-09-01 09:55:47.690 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 456/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:40:02
2025-09-01 09:55:49.466 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 456/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:39:59
2025-09-01 09:55:51.244 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 456/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:39:56
2025-09-01 09:55:53.021 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 456/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:39:53
2025-09-01 09:55:54.740 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 456/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 3.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:39:50
2025-09-01 09:55:55.511 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:55:55.559 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch457
2025-09-01 09:55:57.222 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 457/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.001s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:39:46
2025-09-01 09:55:58.954 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 457/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.1, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 0.8, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:39:43
2025-09-01 09:56:00.746 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 457/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:39:40
2025-09-01 09:56:02.560 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 457/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:39:37
2025-09-01 09:56:04.317 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 457/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, 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: 576, ETA: 0:39:35
2025-09-01 09:56:06.169 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 457/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 2.8, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:39:32
2025-09-01 09:56:06.943 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:56:07.009 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch458
2025-09-01 09:56:08.786 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 458/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:39:28
2025-09-01 09:56:10.633 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 458/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, 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: 576, ETA: 0:39:25
2025-09-01 09:56:12.429 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 458/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.7, l1_loss: 1.4, conf_loss: 3.0, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:39:22
2025-09-01 09:56:14.181 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 458/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, 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: 512, ETA: 0:39:19
2025-09-01 09:56:15.866 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 458/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, 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: 288, ETA: 0:39:16
2025-09-01 09:56:17.658 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 458/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:39:14
2025-09-01 09:56:18.425 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:56:18.479 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch459
2025-09-01 09:56:20.203 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 459/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 2.8, cls_loss: 1.2, lr: 5.000e-04, size: 320, ETA: 0:39:09
2025-09-01 09:56:21.969 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 459/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:39:07
2025-09-01 09:56:23.662 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 459/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:39:04
2025-09-01 09:56:25.443 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 459/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:39:01
2025-09-01 09:56:27.329 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 459/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:38:58
2025-09-01 09:56:29.091 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 459/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 8.4, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 4.3, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:38:55
2025-09-01 09:56:29.887 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:56:29.933 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch460
2025-09-01 09:56:31.761 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 460/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.3, l1_loss: 1.7, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:38:51
2025-09-01 09:56:33.550 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 460/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:38:48
2025-09-01 09:56:35.311 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 460/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.7, iou_loss: 3.2, l1_loss: 1.2, conf_loss: 3.5, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:38:45
2025-09-01 09:56:36.955 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 460/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:38:43
2025-09-01 09:56:38.774 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 460/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:38:40
2025-09-01 09:56:40.620 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 460/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:38:37
2025-09-01 09:56:41.362 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:56:47.306 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:56:48.280 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:56:48.919 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6286
2025-09-01 09:56:49.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5817
2025-09-01 09:56:49.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3981
2025-09-01 09:56:49.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5361
2025-09-01 09:56:49.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:56:49.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:56:49.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.629
2025-09-01 09:56:49.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.582
2025-09-01 09:56:49.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.398
2025-09-01 09:56:49.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.536
2025-09-01 09:56:49.115 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:56:49.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:56:49.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:56:49.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:56:49.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:56:49.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:56:49.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:56:49.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:56:49.116 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:56:50.014 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:56:50.836 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:56:51.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:56:52.500 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:56:53.391 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:56:54.255 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:56:55.074 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:56:55.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:56:56.733 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:56:56.733 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 09:56:56.734 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-09-01 09:56:56.734 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:56:56.741 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.93 ms, Average inference time: 2.32 ms

2025-09-01 09:56:56.742 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:56:56.772 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:56:56.822 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch461
2025-09-01 09:56:58.488 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 461/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 4.1, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:38:33
2025-09-01 09:57:00.249 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 461/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, 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: 480, ETA: 0:38:30
2025-09-01 09:57:02.043 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 461/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.088s, data_time: 0.001s, total_loss: 3.8, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:38:27
2025-09-01 09:57:03.815 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 461/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:38:24
2025-09-01 09:57:05.652 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 461/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.5, l1_loss: 1.4, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:38:22
2025-09-01 09:57:07.504 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 461/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 2.8, iou_loss: 1.3, l1_loss: 0.3, conf_loss: 0.8, cls_loss: 0.4, lr: 5.000e-04, size: 320, ETA: 0:38:19
2025-09-01 09:57:08.315 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:57:08.383 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch462
2025-09-01 09:57:10.179 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 462/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, 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: 0.6, lr: 5.000e-04, size: 576, ETA: 0:38:15
2025-09-01 09:57:11.949 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 462/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:38:12
2025-09-01 09:57:13.673 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 462/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:38:09
2025-09-01 09:57:15.361 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 462/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 3.0, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:38:06
2025-09-01 09:57:17.178 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 462/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:38:03
2025-09-01 09:57:18.960 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 462/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:38:01
2025-09-01 09:57:19.756 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:57:19.807 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch463
2025-09-01 09:57:21.469 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 463/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:37:56
2025-09-01 09:57:23.181 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 463/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.0, l1_loss: 0.9, conf_loss: 4.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:37:54
2025-09-01 09:57:24.916 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 463/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:37:51
2025-09-01 09:57:26.680 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 463/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:37:48
2025-09-01 09:57:28.514 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 463/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.4, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:37:45
2025-09-01 09:57:30.302 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 463/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.006s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:37:42
2025-09-01 09:57:31.050 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:57:31.111 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch464
2025-09-01 09:57:32.925 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 464/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:37:38
2025-09-01 09:57:34.698 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 464/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, 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: 288, ETA: 0:37:35
2025-09-01 09:57:36.478 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 464/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:37:33
2025-09-01 09:57:38.155 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 464/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:37:30
2025-09-01 09:57:39.894 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 464/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:37:27
2025-09-01 09:57:41.685 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 464/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 3.6, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:37:24
2025-09-01 09:57:42.515 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:57:42.573 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch465
2025-09-01 09:57:44.306 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 465/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:37:20
2025-09-01 09:57:46.074 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 465/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.0, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:37:17
2025-09-01 09:57:47.829 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 465/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:37:14
2025-09-01 09:57:49.561 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 465/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:37:12
2025-09-01 09:57:51.255 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 465/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:37:09
2025-09-01 09:57:52.985 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 465/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:37:06
2025-09-01 09:57:53.806 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:57:59.727 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:58:00.461 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:58:00.935 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6300
2025-09-01 09:58:01.056 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5757
2025-09-01 09:58:01.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4005
2025-09-01 09:58:01.135 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5354
2025-09-01 09:58:01.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:58:01.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:58:01.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.630
2025-09-01 09:58:01.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.576
2025-09-01 09:58:01.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.400
2025-09-01 09:58:01.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.535
2025-09-01 09:58:01.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:58:01.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:58:01.136 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:58:01.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:58:01.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:58:01.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:58:01.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:58:01.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:58:01.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:58:01.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:58:02.424 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:58:03.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:58:03.671 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:58:04.260 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:58:04.849 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:58:05.440 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:58:06.272 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:58:06.868 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:58:06.868 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 09:58:06.868 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-09-01 09:58:06.869 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:58:06.876 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.89 ms, Average inference time: 2.25 ms

2025-09-01 09:58:06.876 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:58:06.903 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:58:06.936 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch466
2025-09-01 09:58:08.572 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 466/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:37:02
2025-09-01 09:58:10.306 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 466/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:36:59
2025-09-01 09:58:11.991 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 466/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:36:56
2025-09-01 09:58:13.736 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 466/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.4, l1_loss: 1.1, conf_loss: 2.7, cls_loss: 1.2, lr: 5.000e-04, size: 512, ETA: 0:36:53
2025-09-01 09:58:15.511 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 466/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:36:51
2025-09-01 09:58:17.245 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 466/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.5, l1_loss: 0.3, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:36:48
2025-09-01 09:58:18.004 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:58:18.057 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch467
2025-09-01 09:58:19.846 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 467/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:36:44
2025-09-01 09:58:21.583 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 467/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:36:41
2025-09-01 09:58:23.380 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 467/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, 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: 384, ETA: 0:36:38
2025-09-01 09:58:25.152 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 467/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:36:35
2025-09-01 09:58:26.898 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 467/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 3.9, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:36:33
2025-09-01 09:58:28.755 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 467/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 8.3, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:36:30
2025-09-01 09:58:29.511 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:58:29.559 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch468
2025-09-01 09:58:31.255 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 468/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:36:26
2025-09-01 09:58:32.994 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 468/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 1.0, lr: 5.000e-04, size: 352, ETA: 0:36:23
2025-09-01 09:58:34.748 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 468/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 1.1, lr: 5.000e-04, size: 288, ETA: 0:36:20
2025-09-01 09:58:36.558 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 468/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.7, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:36:17
2025-09-01 09:58:38.330 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 468/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:36:15
2025-09-01 09:58:40.218 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 468/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 8.0, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.000e-04, size: 384, ETA: 0:36:12
2025-09-01 09:58:41.006 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:58:41.063 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch469
2025-09-01 09:58:42.864 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 469/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 1.0, lr: 5.000e-04, size: 384, ETA: 0:36:08
2025-09-01 09:58:44.681 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 469/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.087s, 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: 576, ETA: 0:36:05
2025-09-01 09:58:46.514 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 469/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:36:02
2025-09-01 09:58:48.206 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 469/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:35:59
2025-09-01 09:58:49.960 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 469/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:35:57
2025-09-01 09:58:51.734 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 469/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 9.6, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 4.4, cls_loss: 1.0, lr: 5.000e-04, size: 576, ETA: 0:35:54
2025-09-01 09:58:52.598 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:58:52.645 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch470
2025-09-01 09:58:54.393 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 470/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.2, l1_loss: 0.4, conf_loss: 3.3, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:35:50
2025-09-01 09:58:56.167 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 470/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 4.8, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:35:47
2025-09-01 09:58:57.915 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 470/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:35:44
2025-09-01 09:58:59.599 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 470/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 4.4, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:35:41
2025-09-01 09:59:01.372 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 470/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:35:39
2025-09-01 09:59:03.142 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 470/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:35:36
2025-09-01 09:59:03.964 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:59:09.718 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 09:59:10.599 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 09:59:11.198 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6267
2025-09-01 09:59:11.312 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5805
2025-09-01 09:59:11.344 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4206
2025-09-01 09:59:11.344 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5426
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.627
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.581
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.421
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.543
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 09:59:11.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 09:59:11.346 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 09:59:11.346 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 09:59:11.346 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 09:59:11.346 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 09:59:11.346 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 09:59:12.156 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 09:59:12.975 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 09:59:13.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 09:59:14.459 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 09:59:15.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 09:59:15.945 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 09:59:16.678 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 09:59:17.541 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 09:59:18.361 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 09:59:18.361 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 09:59:18.361 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-09-01 09:59:18.361 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 09:59:18.371 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.34 ms, Average NMS time: 0.92 ms, Average inference time: 2.25 ms

2025-09-01 09:59:18.373 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:59:18.396 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:59:18.439 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch471
2025-09-01 09:59:20.160 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 471/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:35:32
2025-09-01 09:59:21.927 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 471/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:35:29
2025-09-01 09:59:23.778 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 471/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.2, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:35:26
2025-09-01 09:59:25.503 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 471/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 4.4, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:35:23
2025-09-01 09:59:27.284 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 471/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:35:21
2025-09-01 09:59:29.137 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 471/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 4.8, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:35:18
2025-09-01 09:59:29.899 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:59:29.954 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch472
2025-09-01 09:59:31.627 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 472/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 4.7, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:35:14
2025-09-01 09:59:33.426 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 472/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:35:11
2025-09-01 09:59:35.227 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 472/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:35:08
2025-09-01 09:59:36.980 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 472/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:35:06
2025-09-01 09:59:38.764 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 472/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, 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: 576, ETA: 0:35:03
2025-09-01 09:59:40.556 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 472/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:35:00
2025-09-01 09:59:41.316 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:59:41.355 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch473
2025-09-01 09:59:43.139 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 473/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:34:56
2025-09-01 09:59:44.900 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 473/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:34:53
2025-09-01 09:59:46.745 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 473/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:34:51
2025-09-01 09:59:48.477 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 473/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:34:48
2025-09-01 09:59:50.167 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 473/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:34:45
2025-09-01 09:59:51.880 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 473/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:34:42
2025-09-01 09:59:52.653 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 09:59:52.768 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch474
2025-09-01 09:59:54.493 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 474/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 3.4, cls_loss: 1.0, lr: 5.000e-04, size: 576, ETA: 0:34:38
2025-09-01 09:59:56.287 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 474/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:34:35
2025-09-01 09:59:58.011 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 474/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:34:33
2025-09-01 09:59:59.771 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 474/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:34:30
2025-09-01 10:00:01.491 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 474/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.081s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:34:27
2025-09-01 10:00:03.213 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 474/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:34:24
2025-09-01 10:00:04.011 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:00:04.078 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch475
2025-09-01 10:00:05.853 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 475/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, 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: 480, ETA: 0:34:20
2025-09-01 10:00:07.674 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 475/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:34:18
2025-09-01 10:00:09.446 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 475/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.4, l1_loss: 0.3, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:34:15
2025-09-01 10:00:11.120 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 475/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.5, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:34:12
2025-09-01 10:00:12.872 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 475/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:34:09
2025-09-01 10:00:14.644 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 475/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:34:06
2025-09-01 10:00:15.412 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:00:21.305 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:00:22.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:00:22.796 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6314
2025-09-01 10:00:22.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5566
2025-09-01 10:00:22.998 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4002
2025-09-01 10:00:22.999 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5294
2025-09-01 10:00:22.999 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:00:23.000 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:00:23.000 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.631
2025-09-01 10:00:23.000 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.557
2025-09-01 10:00:23.000 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.400
2025-09-01 10:00:23.000 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.529
2025-09-01 10:00:23.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:00:23.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:00:23.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:00:23.001 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:00:23.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:00:23.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:00:23.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:00:23.002 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:00:23.003 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:00:23.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:00:24.896 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:00:25.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:00:26.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:00:27.147 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:00:27.885 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:00:28.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:00:29.380 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:00:30.192 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:00:30.192 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 10:00:30.192 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:00:30.192 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:00:30.199 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.90 ms, Average inference time: 2.29 ms

2025-09-01 10:00:30.202 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:00:30.224 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:00:30.255 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch476
2025-09-01 10:00:31.987 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 476/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:34:02
2025-09-01 10:00:33.669 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 476/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:34:00
2025-09-01 10:00:35.454 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 476/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.4, l1_loss: 1.4, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 576, ETA: 0:33:57
2025-09-01 10:00:37.258 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 476/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:33:54
2025-09-01 10:00:39.033 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 476/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:33:51
2025-09-01 10:00:40.789 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 476/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.2, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:33:49
2025-09-01 10:00:41.570 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:00:41.620 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch477
2025-09-01 10:00:43.353 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 477/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:33:45
2025-09-01 10:00:45.116 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 477/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:33:42
2025-09-01 10:00:46.880 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 477/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, 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: 0:33:39
2025-09-01 10:00:48.698 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 477/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, 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: 416, ETA: 0:33:36
2025-09-01 10:00:50.592 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 477/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 4.2, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:33:34
2025-09-01 10:00:52.316 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 477/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:33:31
2025-09-01 10:00:53.128 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:00:53.179 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch478
2025-09-01 10:00:55.013 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 478/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:33:27
2025-09-01 10:00:56.771 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 478/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:33:24
2025-09-01 10:00:58.464 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 478/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:33:21
2025-09-01 10:01:00.247 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 478/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:33:19
2025-09-01 10:01:02.036 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 478/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 4.1, iou_loss: 1.3, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.4, lr: 5.000e-04, size: 544, ETA: 0:33:16
2025-09-01 10:01:03.814 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 478/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, 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: 544, ETA: 0:33:13
2025-09-01 10:01:04.555 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:01:04.596 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch479
2025-09-01 10:01:06.347 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 479/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:33:09
2025-09-01 10:01:08.101 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 479/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, 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: 256, ETA: 0:33:06
2025-09-01 10:01:09.888 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 479/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:33:04
2025-09-01 10:01:11.645 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 479/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:33:01
2025-09-01 10:01:13.446 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 479/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, 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: 320, ETA: 0:32:58
2025-09-01 10:01:15.218 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 479/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, 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: 480, ETA: 0:32:55
2025-09-01 10:01:16.024 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:01:16.061 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch480
2025-09-01 10:01:17.731 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 480/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:32:51
2025-09-01 10:01:19.426 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 480/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, 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: 0:32:49
2025-09-01 10:01:21.247 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 480/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 1.0, lr: 5.000e-04, size: 544, ETA: 0:32:46
2025-09-01 10:01:23.041 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 480/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:32:43
2025-09-01 10:01:24.790 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 480/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:32:41
2025-09-01 10:01:26.558 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 480/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:32:38
2025-09-01 10:01:27.326 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:01:33.374 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:01:33.994 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:01:34.474 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6197
2025-09-01 10:01:34.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5641
2025-09-01 10:01:34.639 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3985
2025-09-01 10:01:34.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5274
2025-09-01 10:01:34.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:01:34.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:01:34.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.620
2025-09-01 10:01:34.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-09-01 10:01:34.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.399
2025-09-01 10:01:34.640 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.527
2025-09-01 10:01:34.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:01:34.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:01:34.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:01:34.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:01:34.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:01:34.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:01:34.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:01:34.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:01:34.641 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:01:35.162 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:01:35.650 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:01:36.142 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:01:36.633 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:01:37.161 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:01:37.649 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:01:38.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:01:38.634 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:01:39.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:01:39.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 10:01:39.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:01:39.129 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:01:39.136 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.89 ms, Average inference time: 2.26 ms

2025-09-01 10:01:39.137 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:01:39.165 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:01:39.196 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch481
2025-09-01 10:01:40.877 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 481/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 1.3, lr: 5.000e-04, size: 384, ETA: 0:32:34
2025-09-01 10:01:42.585 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 481/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 0.7, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:32:31
2025-09-01 10:01:44.328 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 481/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:32:28
2025-09-01 10:01:46.129 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 481/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.001s, 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: 352, ETA: 0:32:26
2025-09-01 10:01:47.906 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 481/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:32:23
2025-09-01 10:01:49.645 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 481/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:32:20
2025-09-01 10:01:50.444 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:01:50.507 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch482
2025-09-01 10:01:52.295 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 482/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:32:16
2025-09-01 10:01:54.127 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 482/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:32:13
2025-09-01 10:01:55.871 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 482/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:32:11
2025-09-01 10:01:57.568 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 482/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:32:08
2025-09-01 10:01:59.420 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 482/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:32:05
2025-09-01 10:02:01.178 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 482/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 11.7, iou_loss: 3.4, l1_loss: 1.4, conf_loss: 5.9, cls_loss: 1.0, lr: 5.000e-04, size: 480, ETA: 0:32:03
2025-09-01 10:02:01.960 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:02:01.998 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch483
2025-09-01 10:02:03.815 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 483/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:31:59
2025-09-01 10:02:05.535 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 483/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:31:56
2025-09-01 10:02:07.284 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 483/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:31:53
2025-09-01 10:02:09.119 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 483/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 12.8, iou_loss: 3.4, l1_loss: 1.0, conf_loss: 7.5, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:31:50
2025-09-01 10:02:10.986 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 483/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.091s, data_time: 0.006s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:31:48
2025-09-01 10:02:12.743 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 483/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:31:45
2025-09-01 10:02:13.519 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:02:13.558 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch484
2025-09-01 10:02:15.292 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 484/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.4, iou_loss: 2.0, l1_loss: 0.4, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:31:41
2025-09-01 10:02:17.036 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 484/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:31:38
2025-09-01 10:02:18.824 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 484/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:31:36
2025-09-01 10:02:20.510 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 484/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:31:33
2025-09-01 10:02:22.304 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 484/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 1.1, lr: 5.000e-04, size: 512, ETA: 0:31:30
2025-09-01 10:02:24.026 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 484/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:31:27
2025-09-01 10:02:24.790 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:02:24.848 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch485
2025-09-01 10:02:26.529 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 485/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:31:23
2025-09-01 10:02:28.268 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 485/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:31:21
2025-09-01 10:02:29.979 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 485/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:31:18
2025-09-01 10:02:31.753 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 485/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:31:15
2025-09-01 10:02:33.532 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 485/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:31:12
2025-09-01 10:02:35.275 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 485/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:31:10
2025-09-01 10:02:36.031 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:02:42.038 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:02:42.624 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:02:43.030 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6393
2025-09-01 10:02:43.111 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5722
2025-09-01 10:02:43.143 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4111
2025-09-01 10:02:43.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5409
2025-09-01 10:02:43.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:02:43.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:02:43.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.639
2025-09-01 10:02:43.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.572
2025-09-01 10:02:43.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.411
2025-09-01 10:02:43.144 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.541
2025-09-01 10:02:43.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:02:43.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:02:43.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:02:43.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:02:43.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:02:43.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:02:43.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:02:43.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:02:43.146 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:02:43.688 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:02:44.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:02:44.684 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:02:45.188 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:02:45.686 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:02:46.180 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:02:46.664 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:02:47.198 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:02:47.687 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:02:47.687 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 10:02:47.687 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-09-01 10:02:47.688 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:02:47.694 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.34 ms, Average NMS time: 0.88 ms, Average inference time: 2.22 ms

2025-09-01 10:02:47.699 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:02:47.737 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:02:47.781 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch486
2025-09-01 10:02:49.468 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 486/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, 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: 448, ETA: 0:31:06
2025-09-01 10:02:51.202 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 486/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:31:03
2025-09-01 10:02:52.922 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 486/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:31:00
2025-09-01 10:02:54.667 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 486/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 2.0, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:30:58
2025-09-01 10:02:56.458 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 486/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:30:55
2025-09-01 10:02:58.316 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 486/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:30:52
2025-09-01 10:02:59.160 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:02:59.205 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch487
2025-09-01 10:03:00.903 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 487/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, 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: 352, ETA: 0:30:48
2025-09-01 10:03:02.714 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 487/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:30:46
2025-09-01 10:03:04.562 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 487/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:30:43
2025-09-01 10:03:06.345 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 487/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:30:40
2025-09-01 10:03:08.186 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 487/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:30:38
2025-09-01 10:03:09.952 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 487/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:30:35
2025-09-01 10:03:10.708 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:03:10.760 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch488
2025-09-01 10:03:12.522 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 488/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, 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: 288, ETA: 0:30:31
2025-09-01 10:03:14.293 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 488/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:30:28
2025-09-01 10:03:16.058 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 488/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, 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: 256, ETA: 0:30:25
2025-09-01 10:03:17.819 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 488/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, 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: 512, ETA: 0:30:23
2025-09-01 10:03:19.709 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 488/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.003s, 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: 448, ETA: 0:30:20
2025-09-01 10:03:21.522 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 488/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:30:17
2025-09-01 10:03:22.378 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:03:22.416 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch489
2025-09-01 10:03:24.151 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 489/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:30:13
2025-09-01 10:03:25.938 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 489/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, 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: 448, ETA: 0:30:11
2025-09-01 10:03:27.701 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 489/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:30:08
2025-09-01 10:03:29.475 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 489/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.4, iou_loss: 3.1, l1_loss: 1.3, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:30:05
2025-09-01 10:03:31.147 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 489/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:30:03
2025-09-01 10:03:32.923 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 489/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:30:00
2025-09-01 10:03:33.669 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:03:33.707 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch490
2025-09-01 10:03:35.431 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 490/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:29:56
2025-09-01 10:03:37.219 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 490/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.0, iou_loss: 1.2, l1_loss: 0.4, conf_loss: 1.1, cls_loss: 0.4, lr: 5.000e-04, size: 352, ETA: 0:29:53
2025-09-01 10:03:38.968 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 490/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:29:51
2025-09-01 10:03:40.756 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 490/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:29:48
2025-09-01 10:03:42.616 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 490/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:29:45
2025-09-01 10:03:44.360 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 490/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 8.2, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 4.0, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:29:43
2025-09-01 10:03:45.169 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:03:51.225 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:03:52.064 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:03:52.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6345
2025-09-01 10:03:52.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5625
2025-09-01 10:03:52.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3872
2025-09-01 10:03:52.778 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5281
2025-09-01 10:03:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:03:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:03:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.634
2025-09-01 10:03:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.562
2025-09-01 10:03:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.387
2025-09-01 10:03:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.528
2025-09-01 10:03:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:03:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:03:52.779 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:03:52.780 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:03:52.780 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:03:52.780 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:03:52.780 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:03:52.780 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:03:52.780 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:03:53.518 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:03:54.204 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:03:55.007 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:03:55.744 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:03:56.420 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:03:57.113 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:03:57.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:03:58.539 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:03:59.366 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:03:59.366 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 10:03:59.366 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:03:59.366 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:03:59.374 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.89 ms, Average inference time: 2.24 ms

2025-09-01 10:03:59.374 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:03:59.404 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:03:59.436 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch491
2025-09-01 10:04:01.059 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 491/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:29:39
2025-09-01 10:04:02.817 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 491/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:29:36
2025-09-01 10:04:04.600 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 491/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:29:33
2025-09-01 10:04:06.315 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 491/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:29:31
2025-09-01 10:04:08.111 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 491/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:29:28
2025-09-01 10:04:09.836 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 491/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:29:25
2025-09-01 10:04:10.581 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:04:10.696 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch492
2025-09-01 10:04:12.415 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 492/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:29:21
2025-09-01 10:04:14.069 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 492/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:29:19
2025-09-01 10:04:15.824 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 492/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:29:16
2025-09-01 10:04:17.557 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 492/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.2Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.3, l1_loss: 0.3, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:29:13
2025-09-01 10:04:19.427 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 492/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 4.8, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:29:10
2025-09-01 10:04:21.284 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 492/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:29:08
2025-09-01 10:04:22.061 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:04:22.108 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch493
2025-09-01 10:04:23.784 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 493/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:29:04
2025-09-01 10:04:25.570 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 493/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:29:01
2025-09-01 10:04:27.282 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 493/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.0, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 3.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:28:58
2025-09-01 10:04:29.017 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 493/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 2.5, iou_loss: 1.1, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:28:56
2025-09-01 10:04:30.780 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 493/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:28:53
2025-09-01 10:04:32.498 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 493/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 1.2, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:28:50
2025-09-01 10:04:33.303 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:04:33.362 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch494
2025-09-01 10:04:35.197 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 494/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:28:47
2025-09-01 10:04:36.965 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 494/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:28:44
2025-09-01 10:04:38.688 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 494/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, 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: 352, ETA: 0:28:41
2025-09-01 10:04:40.461 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 494/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:28:38
2025-09-01 10:04:42.213 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 494/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 8.6, iou_loss: 2.9, l1_loss: 1.4, conf_loss: 3.2, cls_loss: 1.0, lr: 5.000e-04, size: 576, ETA: 0:28:36
2025-09-01 10:04:43.943 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 494/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.5, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:28:33
2025-09-01 10:04:44.717 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:04:44.756 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch495
2025-09-01 10:04:46.516 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 495/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 9.3, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 3.5, cls_loss: 4.2, lr: 5.000e-04, size: 352, ETA: 0:28:29
2025-09-01 10:04:48.243 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 495/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 1.3, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:28:27
2025-09-01 10:04:50.009 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 495/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, 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: 320, ETA: 0:28:24
2025-09-01 10:04:51.819 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 495/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, 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: 384, ETA: 0:28:21
2025-09-01 10:04:53.641 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 495/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, 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: 448, ETA: 0:28:18
2025-09-01 10:04:55.371 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 495/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:28:16
2025-09-01 10:04:56.087 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:05:02.209 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:05:03.044 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:05:03.509 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5564
2025-09-01 10:05:03.704 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.4446
2025-09-01 10:05:03.740 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3296
2025-09-01 10:05:03.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4435
2025-09-01 10:05:03.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:05:03.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:05:03.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.556
2025-09-01 10:05:03.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.445
2025-09-01 10:05:03.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.330
2025-09-01 10:05:03.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.444
2025-09-01 10:05:03.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:05:03.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:05:03.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:05:03.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:05:03.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:05:03.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:05:03.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:05:03.742 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:05:03.743 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:05:04.407 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:05:05.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:05:05.999 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:05:06.773 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:05:07.454 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:05:08.091 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:05:08.796 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:05:09.487 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:05:10.132 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:05:10.132 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.22
2025-09-01 10:05:10.132 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.44
2025-09-01 10:05:10.132 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:05:10.140 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.91 ms, Average inference time: 2.26 ms

2025-09-01 10:05:10.140 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:05:10.162 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:05:10.195 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch496
2025-09-01 10:05:11.960 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 496/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:28:12
2025-09-01 10:05:13.781 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 496/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:28:09
2025-09-01 10:05:15.544 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 496/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.7, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:28:07
2025-09-01 10:05:17.262 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 496/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:28:04
2025-09-01 10:05:19.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 496/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:28:01
2025-09-01 10:05:20.836 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 496/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.9, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:27:59
2025-09-01 10:05:21.612 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:05:21.681 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch497
2025-09-01 10:05:23.414 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 497/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:27:55
2025-09-01 10:05:25.205 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 497/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:27:52
2025-09-01 10:05:26.899 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 497/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:27:49
2025-09-01 10:05:28.586 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 497/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:27:47
2025-09-01 10:05:30.332 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 497/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 3.6, iou_loss: 1.1, l1_loss: 0.4, conf_loss: 1.7, cls_loss: 0.4, lr: 5.000e-04, size: 288, ETA: 0:27:44
2025-09-01 10:05:32.131 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 497/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.5, iou_loss: 2.7, l1_loss: 1.3, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:27:41
2025-09-01 10:05:32.901 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:05:33.027 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch498
2025-09-01 10:05:34.746 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 498/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:27:37
2025-09-01 10:05:36.412 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 498/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.001s, total_loss: 2.7, iou_loss: 1.1, l1_loss: 0.3, conf_loss: 1.1, cls_loss: 0.4, lr: 5.000e-04, size: 320, ETA: 0:27:35
2025-09-01 10:05:38.217 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 498/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:27:32
2025-09-01 10:05:39.953 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 498/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:27:29
2025-09-01 10:05:41.736 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 498/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:27:27
2025-09-01 10:05:43.517 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 498/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:27:24
2025-09-01 10:05:44.255 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:05:44.319 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch499
2025-09-01 10:05:46.025 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 499/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:27:20
2025-09-01 10:05:47.816 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 499/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:27:18
2025-09-01 10:05:49.543 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 499/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, 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: 544, ETA: 0:27:15
2025-09-01 10:05:51.337 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 499/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:27:12
2025-09-01 10:05:53.148 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 499/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 3.4, iou_loss: 1.7, l1_loss: 0.3, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:27:10
2025-09-01 10:05:54.875 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 499/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 12.1, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 12.1, cls_loss: 0.0, lr: 5.000e-04, size: 576, ETA: 0:27:07
2025-09-01 10:05:55.687 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:05:55.751 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch500
2025-09-01 10:05:57.425 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 500/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.080s, data_time: 0.002s, 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: 320, ETA: 0:27:03
2025-09-01 10:05:59.224 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 500/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:27:00
2025-09-01 10:06:00.977 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 500/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:26:58
2025-09-01 10:06:02.767 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 500/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:26:55
2025-09-01 10:06:04.576 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 500/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:26:52
2025-09-01 10:06:06.329 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 500/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:26:50
2025-09-01 10:06:07.146 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:06:12.938 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:06:13.842 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:06:14.388 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6216
2025-09-01 10:06:14.588 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5846
2025-09-01 10:06:14.624 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4008
2025-09-01 10:06:14.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5357
2025-09-01 10:06:14.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:06:14.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:06:14.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.622
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.585
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.401
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.536
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:06:14.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:06:14.627 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:06:15.433 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:06:16.203 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:06:16.918 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:06:17.681 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:06:18.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:06:19.270 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:06:20.061 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:06:20.803 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:06:21.556 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:06:21.556 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 10:06:21.556 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-09-01 10:06:21.556 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:06:21.563 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.93 ms, Average inference time: 2.29 ms

2025-09-01 10:06:21.564 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:06:21.586 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:06:21.618 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch501
2025-09-01 10:06:23.232 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 501/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, data_time: 0.001s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:26:46
2025-09-01 10:06:24.972 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 501/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:26:43
2025-09-01 10:06:26.747 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 501/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:26:41
2025-09-01 10:06:28.466 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 501/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.9, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 3.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:26:38
2025-09-01 10:06:30.273 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 501/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:26:35
2025-09-01 10:06:32.043 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 501/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, 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: 448, ETA: 0:26:33
2025-09-01 10:06:32.843 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:06:32.903 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch502
2025-09-01 10:06:34.626 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 502/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.7, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:26:29
2025-09-01 10:06:36.372 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 502/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:26:26
2025-09-01 10:06:38.105 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 502/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:26:23
2025-09-01 10:06:39.863 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 502/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:26:21
2025-09-01 10:06:41.680 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 502/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.7, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:26:18
2025-09-01 10:06:43.456 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 502/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 1.2, lr: 5.000e-04, size: 544, ETA: 0:26:16
2025-09-01 10:06:44.255 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:06:44.311 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch503
2025-09-01 10:06:46.085 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 503/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:26:12
2025-09-01 10:06:47.868 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 503/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 15.9, iou_loss: 3.6, l1_loss: 1.0, conf_loss: 10.2, cls_loss: 1.1, lr: 5.000e-04, size: 576, ETA: 0:26:09
2025-09-01 10:06:49.634 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 503/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.8, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:26:06
2025-09-01 10:06:51.356 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 503/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:26:04
2025-09-01 10:06:53.166 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 503/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 9.1, iou_loss: 3.2, l1_loss: 1.4, conf_loss: 3.8, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:26:01
2025-09-01 10:06:55.000 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 503/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:25:59
2025-09-01 10:06:55.792 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:06:55.837 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch504
2025-09-01 10:06:57.534 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 504/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:25:55
2025-09-01 10:06:59.252 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 504/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.9, l1_loss: 1.2, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:25:52
2025-09-01 10:07:01.080 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 504/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.3, l1_loss: 0.3, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:25:49
2025-09-01 10:07:02.892 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 504/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:25:47
2025-09-01 10:07:04.619 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 504/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.003s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:25:44
2025-09-01 10:07:06.438 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 504/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:25:41
2025-09-01 10:07:07.270 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:07:07.309 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch505
2025-09-01 10:07:08.997 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 505/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:25:38
2025-09-01 10:07:10.755 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 505/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:25:35
2025-09-01 10:07:12.504 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 505/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:25:32
2025-09-01 10:07:14.271 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 505/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:25:30
2025-09-01 10:07:16.109 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 505/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:25:27
2025-09-01 10:07:17.850 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 505/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.001s, 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: 0:25:24
2025-09-01 10:07:18.601 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:07:24.461 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:07:25.331 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:07:26.026 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6143
2025-09-01 10:07:26.145 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5747
2025-09-01 10:07:26.182 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4149
2025-09-01 10:07:26.182 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5347
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.614
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.575
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.415
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.535
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:07:26.183 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:07:26.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:07:26.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:07:26.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:07:26.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:07:26.184 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:07:26.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:07:27.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:07:28.534 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:07:29.276 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:07:29.999 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:07:30.758 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:07:31.588 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:07:32.381 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:07:33.098 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:07:33.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 10:07:33.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:07:33.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:07:33.106 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.92 ms, Average inference time: 2.30 ms

2025-09-01 10:07:33.107 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:07:33.133 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:07:33.164 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch506
2025-09-01 10:07:34.935 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 506/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 2.7, iou_loss: 1.2, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:25:21
2025-09-01 10:07:36.665 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 506/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 8.5, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 4.4, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:25:18
2025-09-01 10:07:38.415 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 506/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:25:15
2025-09-01 10:07:40.276 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 506/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:25:13
2025-09-01 10:07:42.036 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 506/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.003s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:25:10
2025-09-01 10:07:43.779 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 506/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:25:07
2025-09-01 10:07:44.549 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:07:44.595 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch507
2025-09-01 10:07:46.271 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 507/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:25:04
2025-09-01 10:07:47.985 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 507/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:25:01
2025-09-01 10:07:49.771 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 507/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 7.3, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:24:58
2025-09-01 10:07:51.593 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 507/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:24:56
2025-09-01 10:07:53.322 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 507/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:24:53
2025-09-01 10:07:55.105 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 507/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:24:50
2025-09-01 10:07:55.923 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:07:55.983 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch508
2025-09-01 10:07:57.675 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 508/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:24:47
2025-09-01 10:07:59.415 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 508/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:24:44
2025-09-01 10:08:01.206 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 508/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.3, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 3.6, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:24:41
2025-09-01 10:08:03.047 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 508/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.006s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:24:39
2025-09-01 10:08:04.740 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 508/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:24:36
2025-09-01 10:08:06.451 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 508/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:24:33
2025-09-01 10:08:07.266 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:08:07.330 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch509
2025-09-01 10:08:09.038 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 509/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:24:30
2025-09-01 10:08:10.745 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 509/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 1.0, lr: 5.000e-04, size: 352, ETA: 0:24:27
2025-09-01 10:08:12.480 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 509/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:24:24
2025-09-01 10:08:14.297 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 509/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:24:22
2025-09-01 10:08:16.100 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 509/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:24:19
2025-09-01 10:08:17.849 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 509/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:24:17
2025-09-01 10:08:18.595 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:08:18.634 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch510
2025-09-01 10:08:20.337 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 510/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 10.2, iou_loss: 3.3, l1_loss: 1.0, conf_loss: 5.0, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:24:13
2025-09-01 10:08:22.200 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 510/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:24:10
2025-09-01 10:08:23.976 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 510/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 1.2, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:24:08
2025-09-01 10:08:25.800 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 510/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:24:05
2025-09-01 10:08:27.542 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 510/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:24:02
2025-09-01 10:08:29.286 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 510/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.3, iou_loss: 1.7, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:24:00
2025-09-01 10:08:30.112 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:08:35.894 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:08:36.611 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:08:37.071 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6228
2025-09-01 10:08:37.163 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5707
2025-09-01 10:08:37.238 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3987
2025-09-01 10:08:37.239 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5307
2025-09-01 10:08:37.239 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:08:37.239 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:08:37.239 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.623
2025-09-01 10:08:37.239 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.571
2025-09-01 10:08:37.239 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.399
2025-09-01 10:08:37.239 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.531
2025-09-01 10:08:37.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:08:37.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:08:37.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:08:37.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:08:37.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:08:37.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:08:37.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:08:37.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:08:37.240 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:08:37.817 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:08:38.394 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:08:38.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:08:39.554 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:08:40.169 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:08:40.759 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:08:41.338 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:08:41.907 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:08:42.510 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:08:42.511 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 10:08:42.511 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:08:42.511 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:08:42.517 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.88 ms, Average inference time: 2.24 ms

2025-09-01 10:08:42.518 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:08:42.545 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:08:42.576 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch511
2025-09-01 10:08:44.212 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 511/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.001s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:23:56
2025-09-01 10:08:46.026 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 511/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:23:53
2025-09-01 10:08:47.817 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 511/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:23:51
2025-09-01 10:08:49.705 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 511/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.093s, data_time: 0.003s, total_loss: 8.8, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 4.2, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:23:48
2025-09-01 10:08:51.439 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 511/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:23:45
2025-09-01 10:08:53.148 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 511/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:23:43
2025-09-01 10:08:53.903 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:08:53.975 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch512
2025-09-01 10:08:55.734 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 512/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:23:39
2025-09-01 10:08:57.440 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 512/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 8.4, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 3.7, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:23:36
2025-09-01 10:08:59.129 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 512/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:23:34
2025-09-01 10:09:00.905 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 512/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.5, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:23:31
2025-09-01 10:09:02.703 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 512/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:23:29
2025-09-01 10:09:04.452 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 512/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 0.8, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:23:26
2025-09-01 10:09:05.183 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:09:05.222 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch513
2025-09-01 10:09:06.987 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 513/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, 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: 256, ETA: 0:23:22
2025-09-01 10:09:08.836 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 513/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:23:20
2025-09-01 10:09:10.560 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 513/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 18.6, iou_loss: 0.0, l1_loss: 0.0, conf_loss: 18.6, cls_loss: 0.0, lr: 5.000e-04, size: 416, ETA: 0:23:17
2025-09-01 10:09:12.350 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 513/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:23:14
2025-09-01 10:09:14.028 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 513/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:23:12
2025-09-01 10:09:15.775 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 513/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:23:09
2025-09-01 10:09:16.583 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:09:16.625 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch514
2025-09-01 10:09:18.369 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 514/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:23:05
2025-09-01 10:09:20.188 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 514/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 3.7, iou_loss: 1.1, l1_loss: 0.3, conf_loss: 1.9, cls_loss: 0.4, lr: 5.000e-04, size: 288, ETA: 0:23:03
2025-09-01 10:09:21.892 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 514/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:23:00
2025-09-01 10:09:23.752 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 514/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 1.3, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:22:58
2025-09-01 10:09:25.579 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 514/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:22:55
2025-09-01 10:09:27.374 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 514/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 1.0, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:22:52
2025-09-01 10:09:28.181 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:09:28.217 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch515
2025-09-01 10:09:30.085 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 515/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:22:49
2025-09-01 10:09:31.970 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 515/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:22:46
2025-09-01 10:09:33.752 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 515/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:22:43
2025-09-01 10:09:35.513 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 515/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:22:41
2025-09-01 10:09:37.275 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 515/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:22:38
2025-09-01 10:09:39.010 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 515/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:22:36
2025-09-01 10:09:39.775 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:09:45.574 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:09:46.152 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:09:46.450 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6247
2025-09-01 10:09:46.598 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5770
2025-09-01 10:09:46.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3999
2025-09-01 10:09:46.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5339
2025-09-01 10:09:46.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:09:46.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:09:46.630 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.625
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.577
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.400
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.534
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:09:46.631 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:09:46.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:09:46.632 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:09:47.114 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:09:47.579 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:09:48.068 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:09:48.543 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:09:49.029 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:09:49.575 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:09:50.073 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:09:50.610 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:09:51.098 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:09:51.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 10:09:51.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:09:51.099 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:09:51.105 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.34 ms, Average NMS time: 0.87 ms, Average inference time: 2.20 ms

2025-09-01 10:09:51.106 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:09:51.134 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:09:51.164 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch516
2025-09-01 10:09:52.858 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 516/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.001s, 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: 576, ETA: 0:22:32
2025-09-01 10:09:54.637 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 516/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:22:29
2025-09-01 10:09:56.419 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 516/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:22:27
2025-09-01 10:09:58.214 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 516/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:22:24
2025-09-01 10:09:59.949 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 516/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:22:21
2025-09-01 10:10:01.748 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 516/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:22:19
2025-09-01 10:10:02.505 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:10:02.586 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch517
2025-09-01 10:10:04.333 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 517/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:22:15
2025-09-01 10:10:06.075 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 517/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.7, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:22:12
2025-09-01 10:10:07.767 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 517/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.4, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:22:10
2025-09-01 10:10:09.523 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 517/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:22:07
2025-09-01 10:10:11.265 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 517/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:22:05
2025-09-01 10:10:12.974 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 517/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:22:02
2025-09-01 10:10:13.790 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:10:13.871 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch518
2025-09-01 10:10:15.671 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 518/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:21:58
2025-09-01 10:10:17.384 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 518/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.3, l1_loss: 0.6, conf_loss: 0.8, cls_loss: 0.4, lr: 5.000e-04, size: 448, ETA: 0:21:56
2025-09-01 10:10:19.195 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 518/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:21:53
2025-09-01 10:10:20.993 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 518/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:21:50
2025-09-01 10:10:22.781 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 518/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:21:48
2025-09-01 10:10:24.549 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 518/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, 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: 544, ETA: 0:21:45
2025-09-01 10:10:25.336 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:10:25.374 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch519
2025-09-01 10:10:27.102 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 519/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:21:42
2025-09-01 10:10:28.866 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 519/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.001s, 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: 448, ETA: 0:21:39
2025-09-01 10:10:30.639 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 519/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:21:36
2025-09-01 10:10:32.472 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 519/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:21:34
2025-09-01 10:10:34.261 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 519/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 4.0, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:21:31
2025-09-01 10:10:36.113 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 519/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:21:29
2025-09-01 10:10:36.965 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:10:37.005 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch520
2025-09-01 10:10:38.758 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 520/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:21:25
2025-09-01 10:10:40.445 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 520/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:21:22
2025-09-01 10:10:42.198 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 520/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:21:20
2025-09-01 10:10:43.958 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 520/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 7.0, iou_loss: 1.6, l1_loss: 1.0, conf_loss: 3.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:21:17
2025-09-01 10:10:45.681 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 520/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:21:15
2025-09-01 10:10:47.535 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 520/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:21:12
2025-09-01 10:10:48.298 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:10:54.132 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:10:54.834 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:10:55.283 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6180
2025-09-01 10:10:55.376 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5298
2025-09-01 10:10:55.410 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4054
2025-09-01 10:10:55.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5178
2025-09-01 10:10:55.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:10:55.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:10:55.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.618
2025-09-01 10:10:55.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.530
2025-09-01 10:10:55.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.405
2025-09-01 10:10:55.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.518
2025-09-01 10:10:55.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:10:55.412 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:10:55.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:10:55.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:10:55.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:10:55.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:10:55.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:10:55.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:10:55.413 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:10:55.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:10:56.576 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:10:57.138 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:10:57.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:10:58.257 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:10:58.863 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:10:59.425 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:10:59.977 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:11:00.532 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:11:00.532 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 10:11:00.532 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 10:11:00.532 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:11:00.539 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.91 ms, Average inference time: 2.26 ms

2025-09-01 10:11:00.540 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:11:00.568 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:11:00.598 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch521
2025-09-01 10:11:02.285 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 521/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.1, l1_loss: 1.3, conf_loss: 2.0, cls_loss: 1.1, lr: 5.000e-04, size: 576, ETA: 0:21:08
2025-09-01 10:11:04.132 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 521/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 2.8, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:21:06
2025-09-01 10:11:05.883 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 521/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:21:03
2025-09-01 10:11:07.776 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 521/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 1.0, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:21:00
2025-09-01 10:11:09.550 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 521/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:20:58
2025-09-01 10:11:11.318 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 521/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:20:55
2025-09-01 10:11:12.090 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:11:12.131 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch522
2025-09-01 10:11:13.841 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 522/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:20:52
2025-09-01 10:11:15.632 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 522/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:20:49
2025-09-01 10:11:17.378 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 522/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:20:46
2025-09-01 10:11:19.214 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 522/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:20:44
2025-09-01 10:11:20.920 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 522/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:20:41
2025-09-01 10:11:22.711 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 522/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 2.0, iou_loss: 1.0, l1_loss: 0.2, conf_loss: 0.5, cls_loss: 0.3, lr: 5.000e-04, size: 480, ETA: 0:20:39
2025-09-01 10:11:23.499 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:11:23.572 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch523
2025-09-01 10:11:25.429 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 523/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.6, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:20:35
2025-09-01 10:11:27.201 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 523/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:20:32
2025-09-01 10:11:28.969 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 523/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:20:30
2025-09-01 10:11:30.767 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 523/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.006s, total_loss: 4.0, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:20:27
2025-09-01 10:11:32.563 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 523/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.1, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 3.6, cls_loss: 0.9, lr: 5.000e-04, size: 544, ETA: 0:20:25
2025-09-01 10:11:34.251 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 523/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:20:22
2025-09-01 10:11:35.007 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:11:35.046 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch524
2025-09-01 10:11:36.718 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 524/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.001s, total_loss: 7.4, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:20:18
2025-09-01 10:11:38.495 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 524/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, 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: 576, ETA: 0:20:16
2025-09-01 10:11:40.255 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 524/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:20:13
2025-09-01 10:11:42.169 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 524/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.091s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 1.0, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:20:11
2025-09-01 10:11:43.925 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 524/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:20:08
2025-09-01 10:11:45.634 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 524/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, 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: 448, ETA: 0:20:05
2025-09-01 10:11:46.402 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:11:46.456 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch525
2025-09-01 10:11:48.167 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 525/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.7, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:20:02
2025-09-01 10:11:49.945 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 525/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.3, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:19:59
2025-09-01 10:11:51.722 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 525/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:19:57
2025-09-01 10:11:53.556 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 525/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 6.3, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:19:54
2025-09-01 10:11:55.285 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 525/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:19:51
2025-09-01 10:11:56.991 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 525/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:19:49
2025-09-01 10:11:57.746 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:12:03.666 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:12:04.379 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:12:04.763 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5647
2025-09-01 10:12:04.855 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5353
2025-09-01 10:12:04.965 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3268
2025-09-01 10:12:04.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4756
2025-09-01 10:12:04.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:12:04.966 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:12:04.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.565
2025-09-01 10:12:04.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.535
2025-09-01 10:12:04.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.327
2025-09-01 10:12:04.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.476
2025-09-01 10:12:04.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:12:04.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:12:04.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:12:04.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:12:04.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:12:04.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:12:04.968 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:12:04.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:12:04.969 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:12:05.568 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:12:06.068 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:12:06.564 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:12:07.111 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:12:07.625 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:12:08.168 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:12:08.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:12:09.210 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:12:09.703 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:12:09.703 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.25
2025-09-01 10:12:09.704 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-09-01 10:12:09.704 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:12:09.710 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.87 ms, Average inference time: 2.25 ms

2025-09-01 10:12:09.711 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:12:09.733 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:12:09.763 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch526
2025-09-01 10:12:11.418 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 526/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:19:45
2025-09-01 10:12:13.132 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 526/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:19:43
2025-09-01 10:12:14.865 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 526/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:19:40
2025-09-01 10:12:16.622 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 526/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, 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: 576, ETA: 0:19:37
2025-09-01 10:12:18.456 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 526/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, 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: 544, ETA: 0:19:35
2025-09-01 10:12:20.282 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 526/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:19:32
2025-09-01 10:12:21.065 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:12:21.116 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch527
2025-09-01 10:12:22.839 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 527/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:19:29
2025-09-01 10:12:24.552 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 527/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:19:26
2025-09-01 10:12:26.388 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 527/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:19:24
2025-09-01 10:12:28.160 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 527/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:19:21
2025-09-01 10:12:29.926 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 527/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, 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: 480, ETA: 0:19:18
2025-09-01 10:12:31.689 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 527/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, 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: 0.5, lr: 5.000e-04, size: 576, ETA: 0:19:16
2025-09-01 10:12:32.504 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:12:32.553 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch528
2025-09-01 10:12:34.348 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 528/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 10.9, iou_loss: 3.4, l1_loss: 1.0, conf_loss: 5.6, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:19:12
2025-09-01 10:12:36.148 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 528/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:19:10
2025-09-01 10:12:37.895 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 528/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, 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: 544, ETA: 0:19:07
2025-09-01 10:12:39.673 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 528/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.4, lr: 5.000e-04, size: 576, ETA: 0:19:04
2025-09-01 10:12:41.440 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 528/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:19:02
2025-09-01 10:12:43.224 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 528/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.3, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 0.4, lr: 5.000e-04, size: 576, ETA: 0:18:59
2025-09-01 10:12:44.038 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:12:44.082 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch529
2025-09-01 10:12:45.848 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 529/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.5, iou_loss: 2.2, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:18:56
2025-09-01 10:12:47.566 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 529/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:18:53
2025-09-01 10:12:49.291 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 529/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.9, iou_loss: 3.2, l1_loss: 1.2, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:18:51
2025-09-01 10:12:51.153 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 529/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.005s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:18:48
2025-09-01 10:12:52.949 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 529/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:18:45
2025-09-01 10:12:54.703 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 529/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:18:43
2025-09-01 10:12:55.469 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:12:55.506 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch530
2025-09-01 10:12:57.223 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 530/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:18:39
2025-09-01 10:12:58.969 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 530/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:18:37
2025-09-01 10:13:00.727 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 530/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.9, iou_loss: 3.4, l1_loss: 1.5, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:18:34
2025-09-01 10:13:02.504 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 530/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 3.4, iou_loss: 1.6, l1_loss: 0.3, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:18:32
2025-09-01 10:13:04.267 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 530/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.0, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:18:29
2025-09-01 10:13:06.004 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 530/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:18:26
2025-09-01 10:13:06.771 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:13:12.641 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:13:13.629 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:13:14.286 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6042
2025-09-01 10:13:14.409 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5280
2025-09-01 10:13:14.488 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3987
2025-09-01 10:13:14.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5103
2025-09-01 10:13:14.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:13:14.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:13:14.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.604
2025-09-01 10:13:14.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.528
2025-09-01 10:13:14.489 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.399
2025-09-01 10:13:14.490 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.510
2025-09-01 10:13:14.490 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:13:14.490 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:13:14.490 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:13:14.490 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:13:14.490 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:13:14.491 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:13:14.491 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:13:14.491 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:13:14.491 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:13:15.432 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:13:16.298 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:13:17.112 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:13:17.967 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:13:18.782 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:13:19.664 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:13:20.484 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:13:21.351 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:13:22.271 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:13:22.271 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 10:13:22.271 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 10:13:22.272 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:13:22.281 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.94 ms, Average inference time: 2.32 ms

2025-09-01 10:13:22.282 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:13:22.322 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:13:22.368 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch531
2025-09-01 10:13:24.004 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 531/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:18:23
2025-09-01 10:13:25.661 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 531/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:18:20
2025-09-01 10:13:27.328 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 531/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.3, l1_loss: 0.3, conf_loss: 1.5, cls_loss: 0.4, lr: 5.000e-04, size: 288, ETA: 0:18:18
2025-09-01 10:13:29.046 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 531/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.003s, total_loss: 4.2, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:18:15
2025-09-01 10:13:30.818 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 531/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:18:12
2025-09-01 10:13:32.659 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 531/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 1.2, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:18:10
2025-09-01 10:13:33.506 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:13:33.560 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch532
2025-09-01 10:13:35.271 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 532/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:18:06
2025-09-01 10:13:36.948 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 532/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.079s, 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: 416, ETA: 0:18:04
2025-09-01 10:13:38.684 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 532/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 1.1, lr: 5.000e-04, size: 384, ETA: 0:18:01
2025-09-01 10:13:40.473 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 532/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 1.0, lr: 5.000e-04, size: 544, ETA: 0:17:59
2025-09-01 10:13:42.225 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 532/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:17:56
2025-09-01 10:13:43.904 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 532/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:17:54
2025-09-01 10:13:44.649 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:13:44.690 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch533
2025-09-01 10:13:46.371 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 533/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:17:50
2025-09-01 10:13:48.158 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 533/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:17:47
2025-09-01 10:13:49.990 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 533/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.3, l1_loss: 1.2, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:17:45
2025-09-01 10:13:51.808 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 533/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:17:42
2025-09-01 10:13:53.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 533/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, 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: 448, ETA: 0:17:40
2025-09-01 10:13:55.415 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 533/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, 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: 544, ETA: 0:17:37
2025-09-01 10:13:56.245 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:13:56.295 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch534
2025-09-01 10:13:58.039 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 534/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:17:33
2025-09-01 10:13:59.783 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 534/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 1.0, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:17:31
2025-09-01 10:14:01.513 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 534/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 1.1, lr: 5.000e-04, size: 288, ETA: 0:17:28
2025-09-01 10:14:03.405 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 534/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:17:26
2025-09-01 10:14:05.144 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 534/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.2, l1_loss: 0.3, conf_loss: 1.3, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:17:23
2025-09-01 10:14:06.843 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 534/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.3, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:17:21
2025-09-01 10:14:07.601 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:14:07.656 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch535
2025-09-01 10:14:09.382 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 535/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, 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: 384, ETA: 0:17:17
2025-09-01 10:14:11.157 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 535/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:17:15
2025-09-01 10:14:12.924 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 535/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:17:12
2025-09-01 10:14:14.645 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 535/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:17:09
2025-09-01 10:14:16.369 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 535/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.4, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 0.8, lr: 5.000e-04, size: 448, ETA: 0:17:07
2025-09-01 10:14:18.107 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 535/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:17:04
2025-09-01 10:14:18.897 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:14:24.775 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:14:25.436 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:14:25.895 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5976
2025-09-01 10:14:26.041 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5553
2025-09-01 10:14:26.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3379
2025-09-01 10:14:26.076 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4969
2025-09-01 10:14:26.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:14:26.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:14:26.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.598
2025-09-01 10:14:26.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.555
2025-09-01 10:14:26.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.338
2025-09-01 10:14:26.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.497
2025-09-01 10:14:26.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:14:26.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:14:26.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:14:26.078 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:14:26.078 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:14:26.078 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:14:26.078 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:14:26.078 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:14:26.078 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:14:26.713 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:14:27.268 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:14:27.820 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:14:28.416 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:14:28.963 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:14:29.506 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:14:30.055 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:14:30.601 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:14:31.185 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:14:31.185 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-09-01 10:14:31.186 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-09-01 10:14:31.186 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:14:31.192 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.42 ms, Average NMS time: 0.89 ms, Average inference time: 2.32 ms

2025-09-01 10:14:31.193 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:14:31.233 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:14:31.283 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch536
2025-09-01 10:14:32.974 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 536/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:17:01
2025-09-01 10:14:34.730 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 536/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:16:58
2025-09-01 10:14:36.430 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 536/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, 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: 320, ETA: 0:16:56
2025-09-01 10:14:38.162 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 536/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.003s, total_loss: 2.8, iou_loss: 1.2, l1_loss: 0.4, conf_loss: 0.8, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:16:53
2025-09-01 10:14:39.928 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 536/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:16:51
2025-09-01 10:14:41.668 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 536/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:16:48
2025-09-01 10:14:42.464 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:14:42.525 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch537
2025-09-01 10:14:44.337 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 537/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.6, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:16:44
2025-09-01 10:14:46.067 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 537/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:16:42
2025-09-01 10:14:47.918 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 537/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, 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: 512, ETA: 0:16:39
2025-09-01 10:14:49.669 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 537/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 4.1, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:16:37
2025-09-01 10:14:51.391 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 537/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, 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: 480, ETA: 0:16:34
2025-09-01 10:14:53.150 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 537/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:16:32
2025-09-01 10:14:53.946 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:14:53.999 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch538
2025-09-01 10:14:55.716 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 538/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.8, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:16:28
2025-09-01 10:14:57.443 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 538/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:16:26
2025-09-01 10:14:59.329 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 538/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:16:23
2025-09-01 10:15:01.116 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 538/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.4, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:16:20
2025-09-01 10:15:02.914 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 538/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.5, l1_loss: 0.3, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:16:18
2025-09-01 10:15:04.657 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 538/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:16:15
2025-09-01 10:15:05.489 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:15:05.546 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch539
2025-09-01 10:15:07.393 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 539/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:16:12
2025-09-01 10:15:09.147 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 539/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:16:09
2025-09-01 10:15:10.957 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 539/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:16:07
2025-09-01 10:15:12.853 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 539/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:16:04
2025-09-01 10:15:14.574 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 539/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:16:02
2025-09-01 10:15:16.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 539/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:15:59
2025-09-01 10:15:17.124 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:15:17.181 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch540
2025-09-01 10:15:18.837 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 540/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:15:56
2025-09-01 10:15:20.570 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 540/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:15:53
2025-09-01 10:15:22.366 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 540/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:15:50
2025-09-01 10:15:24.163 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 540/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 1.1, lr: 5.000e-04, size: 256, ETA: 0:15:48
2025-09-01 10:15:25.915 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 540/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:15:45
2025-09-01 10:15:27.720 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 540/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:15:43
2025-09-01 10:15:28.480 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:15:34.304 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:15:35.059 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:15:35.525 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6021
2025-09-01 10:15:35.651 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5523
2025-09-01 10:15:35.695 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3890
2025-09-01 10:15:35.695 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5145
2025-09-01 10:15:35.695 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.602
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.552
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.389
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.514
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:15:35.696 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:15:35.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:15:35.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:15:35.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:15:35.697 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:15:36.351 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:15:37.012 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:15:37.635 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:15:38.266 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:15:38.930 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:15:39.557 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:15:40.185 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:15:40.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:15:41.497 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:15:41.498 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 10:15:41.498 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 10:15:41.498 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:15:41.505 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.90 ms, Average inference time: 2.27 ms

2025-09-01 10:15:41.506 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:15:41.534 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:15:41.565 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch541
2025-09-01 10:15:43.207 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 541/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:15:39
2025-09-01 10:15:44.985 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 541/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:15:37
2025-09-01 10:15:46.844 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 541/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:15:34
2025-09-01 10:15:48.509 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 541/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 1.2, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:15:32
2025-09-01 10:15:50.270 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 541/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:15:29
2025-09-01 10:15:52.004 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 541/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:15:27
2025-09-01 10:15:52.745 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:15:52.781 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch542
2025-09-01 10:15:54.554 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 542/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:15:23
2025-09-01 10:15:56.273 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 542/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, 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: 288, ETA: 0:15:21
2025-09-01 10:15:58.103 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 542/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 3.0, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:15:18
2025-09-01 10:15:59.871 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 542/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:15:16
2025-09-01 10:16:01.641 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 542/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.8, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:15:13
2025-09-01 10:16:03.338 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 542/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.5, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:15:10
2025-09-01 10:16:04.109 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:16:04.152 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch543
2025-09-01 10:16:05.883 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 543/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:15:07
2025-09-01 10:16:07.591 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 543/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:15:04
2025-09-01 10:16:09.378 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 543/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 3.7, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:15:02
2025-09-01 10:16:11.114 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 543/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:14:59
2025-09-01 10:16:12.838 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 543/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:14:57
2025-09-01 10:16:14.628 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 543/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:14:54
2025-09-01 10:16:15.417 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:16:15.486 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch544
2025-09-01 10:16:17.267 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 544/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:14:51
2025-09-01 10:16:19.072 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 544/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:14:48
2025-09-01 10:16:20.867 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 544/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 5.2, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:14:46
2025-09-01 10:16:22.713 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 544/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.7, l1_loss: 1.0, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:14:43
2025-09-01 10:16:24.470 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 544/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 1.3, lr: 5.000e-04, size: 576, ETA: 0:14:41
2025-09-01 10:16:26.287 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 544/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:14:38
2025-09-01 10:16:27.044 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:16:27.091 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch545
2025-09-01 10:16:28.823 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 545/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 4.5, iou_loss: 1.7, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:14:34
2025-09-01 10:16:30.617 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 545/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:14:32
2025-09-01 10:16:32.382 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 545/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 7.9, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:14:29
2025-09-01 10:16:34.130 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 545/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:14:27
2025-09-01 10:16:35.849 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 545/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:14:24
2025-09-01 10:16:37.555 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 545/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.001s, total_loss: 4.3, iou_loss: 1.6, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:14:22
2025-09-01 10:16:38.342 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:16:44.289 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:16:44.865 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:16:45.212 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5679
2025-09-01 10:16:45.323 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5270
2025-09-01 10:16:45.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3498
2025-09-01 10:16:45.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4816
2025-09-01 10:16:45.364 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.568
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.527
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.350
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.482
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:16:45.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:16:45.366 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:16:45.366 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:16:45.870 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:16:46.361 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:16:46.914 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:16:47.513 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:16:48.040 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:16:48.531 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:16:49.017 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:16:49.499 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:16:49.980 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:16:49.980 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 10:16:49.980 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.48
2025-09-01 10:16:49.980 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:16:49.987 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.87 ms, Average inference time: 2.26 ms

2025-09-01 10:16:49.987 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:16:50.027 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:16:50.069 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch546
2025-09-01 10:16:51.740 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 546/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:14:18
2025-09-01 10:16:53.462 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 546/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 10.5, iou_loss: 3.4, l1_loss: 1.3, conf_loss: 5.0, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:14:16
2025-09-01 10:16:55.235 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 546/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:14:13
2025-09-01 10:16:57.007 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 546/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:14:11
2025-09-01 10:16:58.742 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 546/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:14:08
2025-09-01 10:17:00.475 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 546/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.6, l1_loss: 1.3, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:14:06
2025-09-01 10:17:01.251 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:17:01.288 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch547
2025-09-01 10:17:02.990 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 547/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 9.3, iou_loss: 3.1, l1_loss: 1.1, conf_loss: 4.3, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:14:02
2025-09-01 10:17:04.725 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 547/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:14:00
2025-09-01 10:17:06.557 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 547/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:13:57
2025-09-01 10:17:08.360 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 547/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:13:55
2025-09-01 10:17:10.106 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 547/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.4, iou_loss: 3.0, l1_loss: 1.0, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:13:52
2025-09-01 10:17:11.915 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 547/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:13:50
2025-09-01 10:17:12.731 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:17:12.790 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch548
2025-09-01 10:17:14.528 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 548/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:13:46
2025-09-01 10:17:16.295 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 548/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 2.7, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:13:44
2025-09-01 10:17:18.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 548/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.8, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:13:41
2025-09-01 10:17:19.844 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 548/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.001s, 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: 384, ETA: 0:13:39
2025-09-01 10:17:21.593 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 548/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:13:36
2025-09-01 10:17:23.403 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 548/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:13:34
2025-09-01 10:17:24.169 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:17:24.219 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch549
2025-09-01 10:17:26.004 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 549/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.1, l1_loss: 0.9, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:13:30
2025-09-01 10:17:27.804 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 549/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:13:27
2025-09-01 10:17:29.684 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 549/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.007s, total_loss: 3.0, iou_loss: 1.3, l1_loss: 0.5, conf_loss: 0.8, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:13:25
2025-09-01 10:17:31.461 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 549/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.7, l1_loss: 0.5, conf_loss: 1.0, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:13:23
2025-09-01 10:17:33.179 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 549/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:13:20
2025-09-01 10:17:34.925 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 549/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:13:18
2025-09-01 10:17:35.716 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:17:35.756 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch550
2025-09-01 10:17:37.475 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 550/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:13:14
2025-09-01 10:17:39.279 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 550/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:13:11
2025-09-01 10:17:41.087 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 550/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:13:09
2025-09-01 10:17:42.851 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 550/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:13:06
2025-09-01 10:17:44.616 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 550/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.6, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:13:04
2025-09-01 10:17:46.321 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 550/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:13:01
2025-09-01 10:17:47.120 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:17:53.047 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:17:54.015 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:17:54.652 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5413
2025-09-01 10:17:54.741 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5254
2025-09-01 10:17:54.825 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3514
2025-09-01 10:17:54.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4727
2025-09-01 10:17:54.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:17:54.826 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:17:54.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.541
2025-09-01 10:17:54.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.525
2025-09-01 10:17:54.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.351
2025-09-01 10:17:54.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.473
2025-09-01 10:17:54.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:17:54.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:17:54.827 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:17:54.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:17:54.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:17:54.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:17:54.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:17:54.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:17:54.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:17:55.578 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:17:56.375 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:17:57.128 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:17:57.914 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:17:58.671 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:17:59.460 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:18:00.211 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:18:01.082 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:18:01.859 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:18:01.860 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.26
2025-09-01 10:18:01.860 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.47
2025-09-01 10:18:01.860 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:18:01.868 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.42 ms, Average NMS time: 0.93 ms, Average inference time: 2.35 ms

2025-09-01 10:18:01.870 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:18:01.892 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:18:01.928 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch551
2025-09-01 10:18:03.543 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 551/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:12:58
2025-09-01 10:18:05.364 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 551/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:12:55
2025-09-01 10:18:07.216 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 551/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 4.1, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:12:53
2025-09-01 10:18:08.908 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 551/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:12:50
2025-09-01 10:18:10.617 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 551/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:12:48
2025-09-01 10:18:12.450 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 551/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:12:45
2025-09-01 10:18:13.194 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:18:13.231 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch552
2025-09-01 10:18:14.958 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 552/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 6.1, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:12:42
2025-09-01 10:18:16.683 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 552/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.7, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 1.1, lr: 5.000e-04, size: 320, ETA: 0:12:39
2025-09-01 10:18:18.444 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 552/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.007s, 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: 256, ETA: 0:12:37
2025-09-01 10:18:20.305 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 552/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:12:34
2025-09-01 10:18:21.975 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 552/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:12:32
2025-09-01 10:18:23.732 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 552/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, 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: 512, ETA: 0:12:29
2025-09-01 10:18:24.545 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:18:24.585 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch553
2025-09-01 10:18:26.306 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 553/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:12:26
2025-09-01 10:18:28.115 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 553/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:12:23
2025-09-01 10:18:29.936 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 553/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:12:21
2025-09-01 10:18:31.675 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 553/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:12:18
2025-09-01 10:18:33.382 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 553/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:12:16
2025-09-01 10:18:35.181 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 553/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:12:13
2025-09-01 10:18:35.978 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:18:36.037 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch554
2025-09-01 10:18:37.770 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 554/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:12:10
2025-09-01 10:18:39.586 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 554/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:12:07
2025-09-01 10:18:41.301 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 554/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.003s, total_loss: 4.2, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:12:05
2025-09-01 10:18:42.975 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 554/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 2.4, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:12:02
2025-09-01 10:18:44.722 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 554/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:12:00
2025-09-01 10:18:46.596 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 554/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.9, lr: 5.000e-04, size: 320, ETA: 0:11:57
2025-09-01 10:18:47.360 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:18:47.424 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch555
2025-09-01 10:18:49.124 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 555/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:11:54
2025-09-01 10:18:50.871 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 555/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:11:51
2025-09-01 10:18:52.645 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 555/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 3.0, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 0.9, cls_loss: 0.4, lr: 5.000e-04, size: 256, ETA: 0:11:49
2025-09-01 10:18:54.369 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 555/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.0, l1_loss: 0.5, conf_loss: 2.8, cls_loss: 0.3, lr: 5.000e-04, size: 512, ETA: 0:11:46
2025-09-01 10:18:56.183 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 555/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.004s, total_loss: 3.1, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:11:44
2025-09-01 10:18:57.939 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 555/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:11:41
2025-09-01 10:18:58.711 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:19:04.534 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:19:05.619 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:19:06.298 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6166
2025-09-01 10:19:06.494 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5449
2025-09-01 10:19:06.543 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4151
2025-09-01 10:19:06.544 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5255
2025-09-01 10:19:06.544 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:19:06.544 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:19:06.544 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.617
2025-09-01 10:19:06.544 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.545
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.415
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.526
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:19:06.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:19:06.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:19:07.531 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:19:08.400 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:19:09.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:19:10.232 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:19:11.121 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:19:12.019 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:19:12.878 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:19:13.770 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:19:14.668 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:19:14.669 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 10:19:14.669 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:19:14.669 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:19:14.676 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.41 ms, Average NMS time: 0.93 ms, Average inference time: 2.34 ms

2025-09-01 10:19:14.677 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:19:14.704 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:19:14.736 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch556
2025-09-01 10:19:16.488 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 556/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.004s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:11:38
2025-09-01 10:19:18.279 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 556/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:11:35
2025-09-01 10:19:20.036 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 556/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:11:33
2025-09-01 10:19:21.787 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 556/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.0, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:11:30
2025-09-01 10:19:23.468 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 556/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:11:28
2025-09-01 10:19:25.213 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 556/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:11:26
2025-09-01 10:19:25.939 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:19:25.989 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch557
2025-09-01 10:19:27.799 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 557/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:11:22
2025-09-01 10:19:29.563 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 557/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 8.2, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 4.7, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:11:19
2025-09-01 10:19:31.199 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 557/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:11:17
2025-09-01 10:19:32.950 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 557/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:11:14
2025-09-01 10:19:34.686 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 557/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:11:12
2025-09-01 10:19:36.371 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 557/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:11:10
2025-09-01 10:19:37.158 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:19:37.204 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch558
2025-09-01 10:19:38.984 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 558/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 9.1, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 4.4, cls_loss: 0.9, lr: 5.000e-04, size: 480, ETA: 0:11:06
2025-09-01 10:19:40.679 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 558/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.8, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:11:04
2025-09-01 10:19:42.518 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 558/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 3.3, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:11:01
2025-09-01 10:19:44.306 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 558/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, 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: 384, ETA: 0:10:59
2025-09-01 10:19:46.098 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 558/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:10:56
2025-09-01 10:19:47.845 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 558/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 2.5, iou_loss: 1.1, l1_loss: 0.4, conf_loss: 0.7, cls_loss: 0.4, lr: 5.000e-04, size: 544, ETA: 0:10:54
2025-09-01 10:19:48.616 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:19:48.683 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch559
2025-09-01 10:19:50.372 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 559/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.1, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:10:50
2025-09-01 10:19:52.122 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 559/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:10:48
2025-09-01 10:19:53.898 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 559/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:10:45
2025-09-01 10:19:55.620 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 559/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:10:43
2025-09-01 10:19:57.403 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 559/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.4, l1_loss: 1.4, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:10:40
2025-09-01 10:19:59.217 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 559/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:10:38
2025-09-01 10:20:00.021 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:20:00.070 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch560
2025-09-01 10:20:01.831 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 560/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:10:34
2025-09-01 10:20:03.694 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 560/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.091s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:10:32
2025-09-01 10:20:05.436 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 560/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.003s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:10:29
2025-09-01 10:20:07.211 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 560/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:10:27
2025-09-01 10:20:08.939 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 560/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 4.6, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:10:24
2025-09-01 10:20:10.674 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 560/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 6.6, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:10:22
2025-09-01 10:20:11.461 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:20:17.298 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:20:17.982 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:20:18.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6236
2025-09-01 10:20:18.510 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5612
2025-09-01 10:20:18.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4229
2025-09-01 10:20:18.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5359
2025-09-01 10:20:18.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:20:18.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:20:18.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.624
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.561
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.423
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.536
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:20:18.548 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:20:18.549 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:20:19.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:20:19.787 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:20:20.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:20:20.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:20:21.531 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:20:22.095 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:20:22.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:20:23.250 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:20:23.916 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:20:23.916 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 10:20:23.916 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.54
2025-09-01 10:20:23.916 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:20:23.923 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.40 ms, Average NMS time: 0.91 ms, Average inference time: 2.31 ms

2025-09-01 10:20:23.925 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:20:23.952 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:20:23.984 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch561
2025-09-01 10:20:25.625 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 561/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:10:18
2025-09-01 10:20:27.303 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 561/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:10:16
2025-09-01 10:20:29.114 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 561/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.1, iou_loss: 2.2, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:10:13
2025-09-01 10:20:31.003 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 561/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.092s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:10:11
2025-09-01 10:20:32.736 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 561/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:10:08
2025-09-01 10:20:34.490 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 561/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:10:06
2025-09-01 10:20:35.287 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:20:35.337 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch562
2025-09-01 10:20:37.192 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 562/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:10:02
2025-09-01 10:20:38.900 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 562/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:10:00
2025-09-01 10:20:40.656 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 562/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, 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: 0.6, lr: 5.000e-04, size: 512, ETA: 0:09:58
2025-09-01 10:20:42.442 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 562/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:09:55
2025-09-01 10:20:44.168 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 562/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 3.3, iou_loss: 1.1, l1_loss: 0.4, conf_loss: 1.4, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:09:53
2025-09-01 10:20:45.908 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 562/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.1, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 0.8, cls_loss: 0.4, lr: 5.000e-04, size: 544, ETA: 0:09:50
2025-09-01 10:20:46.696 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:20:46.746 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch563
2025-09-01 10:20:48.489 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 563/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 2.9, iou_loss: 1.2, l1_loss: 0.5, conf_loss: 0.8, cls_loss: 0.4, lr: 5.000e-04, size: 512, ETA: 0:09:47
2025-09-01 10:20:50.185 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 563/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:09:44
2025-09-01 10:20:51.933 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 563/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 3.1, cls_loss: 1.1, lr: 5.000e-04, size: 384, ETA: 0:09:42
2025-09-01 10:20:53.704 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 563/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:09:39
2025-09-01 10:20:55.424 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 563/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 9.6, iou_loss: 3.0, l1_loss: 1.1, conf_loss: 4.7, cls_loss: 0.8, lr: 5.000e-04, size: 512, ETA: 0:09:37
2025-09-01 10:20:57.238 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 563/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:09:34
2025-09-01 10:20:58.070 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:20:58.121 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch564
2025-09-01 10:20:59.831 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 564/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, 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: 352, ETA: 0:09:31
2025-09-01 10:21:01.690 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 564/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:09:28
2025-09-01 10:21:03.417 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 564/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:09:26
2025-09-01 10:21:05.173 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 564/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:09:23
2025-09-01 10:21:06.898 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 564/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:09:21
2025-09-01 10:21:08.699 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 564/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, 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: 480, ETA: 0:09:19
2025-09-01 10:21:09.458 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:21:09.496 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch565
2025-09-01 10:21:11.171 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 565/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:09:15
2025-09-01 10:21:12.912 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 565/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:09:13
2025-09-01 10:21:14.759 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 565/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:09:10
2025-09-01 10:21:16.486 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 565/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, 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: 256, ETA: 0:09:08
2025-09-01 10:21:18.342 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 565/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:09:05
2025-09-01 10:21:20.151 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 565/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, 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: 0.6, lr: 5.000e-04, size: 384, ETA: 0:09:03
2025-09-01 10:21:20.902 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:21:26.823 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:21:27.559 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:21:28.077 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6226
2025-09-01 10:21:28.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5638
2025-09-01 10:21:28.206 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4014
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5293
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.623
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.401
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.529
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:21:28.207 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:21:28.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:21:28.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:21:28.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:21:28.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:21:28.208 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:21:28.900 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:21:29.666 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:21:30.427 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:21:31.146 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:21:31.828 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:21:32.502 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:21:33.132 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:21:33.869 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:21:34.510 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:21:34.511 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.30
2025-09-01 10:21:34.511 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:21:34.511 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:21:34.518 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.35 ms, Average NMS time: 0.87 ms, Average inference time: 2.22 ms

2025-09-01 10:21:34.518 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:21:34.545 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:21:34.576 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch566
2025-09-01 10:21:36.206 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 566/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.001s, total_loss: 4.6, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:08:59
2025-09-01 10:21:37.913 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 566/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 3.1, iou_loss: 1.3, l1_loss: 0.4, conf_loss: 1.0, cls_loss: 0.4, lr: 5.000e-04, size: 320, ETA: 0:08:57
2025-09-01 10:21:39.807 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 566/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.6, iou_loss: 2.9, l1_loss: 1.1, conf_loss: 3.0, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:08:54
2025-09-01 10:21:41.553 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 566/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.1, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:08:52
2025-09-01 10:21:43.219 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 566/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:08:49
2025-09-01 10:21:44.979 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 566/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:08:47
2025-09-01 10:21:45.741 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:21:45.789 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch567
2025-09-01 10:21:47.565 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 567/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:08:43
2025-09-01 10:21:49.311 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 567/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 7.4, iou_loss: 2.9, l1_loss: 1.0, conf_loss: 2.7, cls_loss: 0.7, lr: 5.000e-04, size: 544, ETA: 0:08:41
2025-09-01 10:21:51.121 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 567/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.3, iou_loss: 2.7, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:08:39
2025-09-01 10:21:52.886 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 567/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.2, iou_loss: 1.7, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:08:36
2025-09-01 10:21:54.728 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 567/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.7, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 0.7, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:08:34
2025-09-01 10:21:56.615 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 567/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.091s, 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: 256, ETA: 0:08:31
2025-09-01 10:21:57.436 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:21:57.474 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch568
2025-09-01 10:21:59.240 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 568/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:08:28
2025-09-01 10:22:01.021 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 568/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:08:25
2025-09-01 10:22:02.871 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 568/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 7.8, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:08:23
2025-09-01 10:22:04.577 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 568/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:08:20
2025-09-01 10:22:06.292 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 568/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.4, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 2.7, cls_loss: 1.0, lr: 5.000e-04, size: 256, ETA: 0:08:18
2025-09-01 10:22:08.013 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 568/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:08:16
2025-09-01 10:22:08.813 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:22:08.868 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch569
2025-09-01 10:22:10.501 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 569/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.078s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:08:12
2025-09-01 10:22:12.348 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 569/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:08:10
2025-09-01 10:22:14.063 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 569/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.003s, total_loss: 3.0, iou_loss: 1.6, l1_loss: 0.5, conf_loss: 0.5, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:08:07
2025-09-01 10:22:15.768 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 569/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.0, cls_loss: 0.4, lr: 5.000e-04, size: 352, ETA: 0:08:05
2025-09-01 10:22:17.526 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 569/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:08:02
2025-09-01 10:22:19.298 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 569/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:08:00
2025-09-01 10:22:20.061 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:22:20.100 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch570
2025-09-01 10:22:21.826 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 570/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, 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: 0:07:56
2025-09-01 10:22:23.573 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 570/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, 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: 512, ETA: 0:07:54
2025-09-01 10:22:25.318 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 570/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 5.1, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:07:51
2025-09-01 10:22:26.980 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 570/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.2, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:07:49
2025-09-01 10:22:28.711 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 570/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:07:47
2025-09-01 10:22:30.517 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 570/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 9.0, iou_loss: 3.4, l1_loss: 1.3, conf_loss: 3.6, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:07:44
2025-09-01 10:22:31.318 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:22:37.172 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:22:37.889 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:22:38.399 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5783
2025-09-01 10:22:38.544 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5180
2025-09-01 10:22:38.600 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3648
2025-09-01 10:22:38.601 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.4870
2025-09-01 10:22:38.601 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:22:38.601 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:22:38.601 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.578
2025-09-01 10:22:38.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.518
2025-09-01 10:22:38.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.365
2025-09-01 10:22:38.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.487
2025-09-01 10:22:38.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:22:38.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:22:38.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:22:38.602 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:22:38.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:22:38.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:22:38.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:22:38.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:22:38.603 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:22:39.222 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:22:39.878 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:22:40.490 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:22:41.120 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:22:41.737 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:22:42.445 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:22:43.046 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:22:43.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:22:44.261 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:22:44.262 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.27
2025-09-01 10:22:44.262 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.49
2025-09-01 10:22:44.262 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:22:44.269 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.36 ms, Average NMS time: 0.86 ms, Average inference time: 2.22 ms

2025-09-01 10:22:44.269 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:22:44.346 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:22:44.379 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch571
2025-09-01 10:22:46.050 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 571/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:07:41
2025-09-01 10:22:47.775 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 571/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:07:38
2025-09-01 10:22:49.621 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 571/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:07:36
2025-09-01 10:22:51.348 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 571/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.9, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:07:33
2025-09-01 10:22:53.051 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 571/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.3, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 480, ETA: 0:07:31
2025-09-01 10:22:54.747 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 571/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 7.2, iou_loss: 3.1, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 256, ETA: 0:07:28
2025-09-01 10:22:55.449 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:22:55.525 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch572
2025-09-01 10:22:57.201 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 572/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, 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: 448, ETA: 0:07:25
2025-09-01 10:22:58.995 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 572/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:07:22
2025-09-01 10:23:00.845 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 572/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.003s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:07:20
2025-09-01 10:23:02.589 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 572/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 9.7, iou_loss: 2.9, l1_loss: 2.1, conf_loss: 3.9, cls_loss: 0.8, lr: 5.000e-04, size: 576, ETA: 0:07:18
2025-09-01 10:23:04.306 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 572/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:07:15
2025-09-01 10:23:06.116 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 572/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 5.1, iou_loss: 1.5, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:07:13
2025-09-01 10:23:06.885 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:23:06.939 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch573
2025-09-01 10:23:08.661 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 573/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:07:09
2025-09-01 10:23:10.425 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 573/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:07:07
2025-09-01 10:23:12.365 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 573/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.095s, data_time: 0.003s, 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: 320, ETA: 0:07:04
2025-09-01 10:23:14.167 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 573/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, 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: 448, ETA: 0:07:02
2025-09-01 10:23:15.930 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 573/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:07:00
2025-09-01 10:23:17.591 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 573/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:06:57
2025-09-01 10:23:18.451 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:23:18.499 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch574
2025-09-01 10:23:20.308 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 574/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:06:54
2025-09-01 10:23:22.030 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 574/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, 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: 480, ETA: 0:06:51
2025-09-01 10:23:23.798 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 574/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.0, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:06:49
2025-09-01 10:23:25.561 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 574/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, 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: 416, ETA: 0:06:46
2025-09-01 10:23:27.361 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 574/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.001s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:06:44
2025-09-01 10:23:29.135 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 574/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 3.4, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:06:41
2025-09-01 10:23:29.877 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:23:29.920 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch575
2025-09-01 10:23:31.692 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 575/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:06:38
2025-09-01 10:23:33.478 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 575/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:06:36
2025-09-01 10:23:35.196 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 575/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 19.7, iou_loss: 3.8, l1_loss: 3.6, conf_loss: 11.0, cls_loss: 1.3, lr: 5.000e-04, size: 512, ETA: 0:06:33
2025-09-01 10:23:36.916 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 575/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.5, l1_loss: 1.1, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:06:31
2025-09-01 10:23:38.655 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 575/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 1.0, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:06:28
2025-09-01 10:23:40.425 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 575/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.0, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:06:26
2025-09-01 10:23:41.183 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:23:47.074 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:23:47.905 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:23:48.367 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6161
2025-09-01 10:23:48.506 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5645
2025-09-01 10:23:48.544 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3832
2025-09-01 10:23:48.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5212
2025-09-01 10:23:48.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:23:48.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:23:48.545 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.616
2025-09-01 10:23:48.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.564
2025-09-01 10:23:48.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.383
2025-09-01 10:23:48.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.521
2025-09-01 10:23:48.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:23:48.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:23:48.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:23:48.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:23:48.546 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:23:48.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:23:48.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:23:48.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:23:48.547 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:23:49.249 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:23:49.877 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:23:50.543 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:23:51.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:23:51.813 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:23:52.639 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:23:53.345 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:23:53.973 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:23:54.641 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:23:54.641 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 10:23:54.641 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.52
2025-09-01 10:23:54.641 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:23:54.648 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.90 ms, Average inference time: 2.28 ms

2025-09-01 10:23:54.649 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:23:54.681 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:23:54.713 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch576
2025-09-01 10:23:56.402 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 576/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:06:22
2025-09-01 10:23:58.183 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 576/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, 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: 0:06:20
2025-09-01 10:23:59.886 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 576/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.3, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.4, lr: 5.000e-04, size: 416, ETA: 0:06:17
2025-09-01 10:24:01.600 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 576/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:06:15
2025-09-01 10:24:03.417 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 576/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 6.0, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.7, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:06:13
2025-09-01 10:24:05.092 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 576/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.0, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:06:10
2025-09-01 10:24:05.842 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:24:05.892 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch577
2025-09-01 10:24:07.676 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 577/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:06:07
2025-09-01 10:24:09.373 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 577/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.5, l1_loss: 1.3, conf_loss: 1.6, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:06:04
2025-09-01 10:24:11.124 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 577/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:06:02
2025-09-01 10:24:12.967 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 577/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.6, l1_loss: 0.7, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:05:59
2025-09-01 10:24:14.687 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 577/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, 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: 416, ETA: 0:05:57
2025-09-01 10:24:16.382 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 577/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.001s, 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: 320, ETA: 0:05:55
2025-09-01 10:24:17.102 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:24:17.141 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch578
2025-09-01 10:24:18.888 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 578/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.8, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:05:51
2025-09-01 10:24:20.649 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 578/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 4.1, iou_loss: 1.4, l1_loss: 0.4, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:05:49
2025-09-01 10:24:22.488 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 578/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:05:46
2025-09-01 10:24:24.244 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 578/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:05:44
2025-09-01 10:24:25.945 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 578/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.6, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:05:41
2025-09-01 10:24:27.670 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 578/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:05:39
2025-09-01 10:24:28.440 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:24:28.482 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch579
2025-09-01 10:24:30.288 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 579/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 1.2, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:05:36
2025-09-01 10:24:32.089 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 579/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 5.5, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 1.1, lr: 5.000e-04, size: 512, ETA: 0:05:33
2025-09-01 10:24:33.836 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 579/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.6, l1_loss: 1.1, conf_loss: 2.5, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:05:31
2025-09-01 10:24:35.588 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 579/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 1.1, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:05:28
2025-09-01 10:24:37.389 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 579/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 4.6, iou_loss: 2.1, l1_loss: 0.5, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:05:26
2025-09-01 10:24:39.211 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 579/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:05:24
2025-09-01 10:24:39.984 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:24:40.038 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch580
2025-09-01 10:24:41.728 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 580/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 6.8, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:05:20
2025-09-01 10:24:43.498 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 580/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 3.9, iou_loss: 1.2, l1_loss: 0.4, conf_loss: 1.9, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:05:18
2025-09-01 10:24:45.302 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 580/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:05:15
2025-09-01 10:24:47.070 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 580/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.9, iou_loss: 1.6, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:05:13
2025-09-01 10:24:48.853 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 580/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.5, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:05:10
2025-09-01 10:24:50.677 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 580/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:05:08
2025-09-01 10:24:51.474 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:24:57.465 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:24:58.126 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:24:58.493 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6108
2025-09-01 10:24:58.583 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5667
2025-09-01 10:24:58.689 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4074
2025-09-01 10:24:58.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5283
2025-09-01 10:24:58.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:24:58.690 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:24:58.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.611
2025-09-01 10:24:58.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.567
2025-09-01 10:24:58.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.407
2025-09-01 10:24:58.691 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.528
2025-09-01 10:24:58.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:24:58.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:24:58.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:24:58.692 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:24:58.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:24:58.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:24:58.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:24:58.693 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:24:58.694 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:24:59.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:24:59.812 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:25:00.337 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:25:00.857 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:25:01.411 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:25:01.928 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:25:02.443 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:25:02.971 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:25:03.497 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:25:03.498 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 10:25:03.498 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:25:03.498 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:25:03.505 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.39 ms, Average NMS time: 0.90 ms, Average inference time: 2.28 ms

2025-09-01 10:25:03.506 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:25:03.538 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:25:03.569 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch581
2025-09-01 10:25:05.288 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 581/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 4.4, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:05:05
2025-09-01 10:25:07.052 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 581/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 5.1, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 2.5, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:05:02
2025-09-01 10:25:08.875 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 581/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, 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: 480, ETA: 0:05:00
2025-09-01 10:25:10.657 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 581/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.001s, total_loss: 4.1, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:04:57
2025-09-01 10:25:12.498 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 581/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 2.8, cls_loss: 1.1, lr: 5.000e-04, size: 288, ETA: 0:04:55
2025-09-01 10:25:14.261 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 581/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:04:52
2025-09-01 10:25:15.033 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:25:15.089 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch582
2025-09-01 10:25:16.785 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 582/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.1, cls_loss: 0.5, lr: 5.000e-04, size: 352, ETA: 0:04:49
2025-09-01 10:25:18.606 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 582/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.006s, total_loss: 4.6, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.3, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:04:47
2025-09-01 10:25:20.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 582/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 0.7, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:04:44
2025-09-01 10:25:22.128 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 582/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.9, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.8, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:04:42
2025-09-01 10:25:23.838 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 582/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.4, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.0, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:04:39
2025-09-01 10:25:25.648 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 582/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.3, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.3, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:04:37
2025-09-01 10:25:26.379 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:25:26.422 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch583
2025-09-01 10:25:28.144 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 583/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.9, lr: 5.000e-04, size: 288, ETA: 0:04:33
2025-09-01 10:25:29.946 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 583/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 4.6, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 512, ETA: 0:04:31
2025-09-01 10:25:31.837 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 583/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 3.4, iou_loss: 1.5, l1_loss: 0.4, conf_loss: 1.0, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:04:29
2025-09-01 10:25:33.650 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 583/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 5.9, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.8, lr: 5.000e-04, size: 256, ETA: 0:04:26
2025-09-01 10:25:35.364 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 583/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:04:24
2025-09-01 10:25:37.137 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 583/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.2, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 544, ETA: 0:04:22
2025-09-01 10:25:37.877 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:25:37.931 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch584
2025-09-01 10:25:39.702 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 584/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.9, lr: 5.000e-04, size: 352, ETA: 0:04:18
2025-09-01 10:25:41.448 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 584/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:04:16
2025-09-01 10:25:43.170 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 584/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.001s, total_loss: 6.4, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:04:13
2025-09-01 10:25:44.878 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 584/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.4, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:04:11
2025-09-01 10:25:46.655 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 584/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, 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: 576, ETA: 0:04:08
2025-09-01 10:25:48.395 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 584/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.9, conf_loss: 1.9, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:04:06
2025-09-01 10:25:49.158 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:25:49.208 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch585
2025-09-01 10:25:50.907 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 585/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 9.9, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 4.8, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:04:03
2025-09-01 10:25:52.776 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 585/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 6.9, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 3.0, cls_loss: 0.8, lr: 5.000e-04, size: 544, ETA: 0:04:00
2025-09-01 10:25:54.470 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 585/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:03:58
2025-09-01 10:25:56.160 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 585/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 8.2, iou_loss: 3.3, l1_loss: 1.1, conf_loss: 3.1, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:03:55
2025-09-01 10:25:57.849 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 585/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.3, l1_loss: 0.8, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:03:53
2025-09-01 10:25:59.604 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 585/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.5, l1_loss: 0.7, conf_loss: 1.3, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:03:51
2025-09-01 10:26:00.373 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:26:06.404 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:26:07.068 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:26:07.485 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.5944
2025-09-01 10:26:07.574 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5475
2025-09-01 10:26:07.653 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3761
2025-09-01 10:26:07.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5060
2025-09-01 10:26:07.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:26:07.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:26:07.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.594
2025-09-01 10:26:07.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.547
2025-09-01 10:26:07.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.376
2025-09-01 10:26:07.654 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.506
2025-09-01 10:26:07.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:26:07.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:26:07.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:26:07.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:26:07.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:26:07.655 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:26:07.656 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:26:07.656 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:26:07.656 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:26:08.193 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:26:08.721 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:26:09.255 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:26:09.790 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:26:10.498 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:26:11.026 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:26:11.552 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:26:12.087 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:26:12.613 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:26:12.613 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.28
2025-09-01 10:26:12.613 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.51
2025-09-01 10:26:12.613 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:26:12.620 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.38 ms, Average NMS time: 0.90 ms, Average inference time: 2.29 ms

2025-09-01 10:26:12.621 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:26:12.648 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:26:12.678 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch586
2025-09-01 10:26:14.446 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 586/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:03:47
2025-09-01 10:26:16.224 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 586/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.005s, total_loss: 6.1, iou_loss: 2.3, l1_loss: 1.0, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:03:45
2025-09-01 10:26:18.039 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 586/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 7.3, iou_loss: 2.6, l1_loss: 1.0, conf_loss: 3.0, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:03:42
2025-09-01 10:26:19.747 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 586/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.001s, total_loss: 7.5, iou_loss: 2.8, l1_loss: 1.0, conf_loss: 2.9, cls_loss: 0.8, lr: 5.000e-04, size: 288, ETA: 0:03:40
2025-09-01 10:26:21.510 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 586/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.5, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 384, ETA: 0:03:38
2025-09-01 10:26:23.355 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 586/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.4, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:03:35
2025-09-01 10:26:24.172 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:26:24.224 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch587
2025-09-01 10:26:26.010 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 587/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.3, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:03:32
2025-09-01 10:26:27.762 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 587/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:03:29
2025-09-01 10:26:29.519 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 587/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 2.4, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:03:27
2025-09-01 10:26:31.397 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 587/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.089s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:03:24
2025-09-01 10:26:33.173 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 587/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.6, iou_loss: 1.5, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:03:22
2025-09-01 10:26:34.954 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 587/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.5, iou_loss: 2.4, l1_loss: 0.8, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 448, ETA: 0:03:20
2025-09-01 10:26:35.748 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:26:35.790 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch588
2025-09-01 10:26:37.521 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 588/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 7.2, iou_loss: 2.9, l1_loss: 1.2, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:03:16
2025-09-01 10:26:39.288 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 588/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.003s, total_loss: 6.5, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 3.2, cls_loss: 0.5, lr: 5.000e-04, size: 576, ETA: 0:03:14
2025-09-01 10:26:41.115 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 588/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.5, iou_loss: 1.1, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.4, lr: 5.000e-04, size: 384, ETA: 0:03:11
2025-09-01 10:26:42.791 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 588/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.4, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:03:09
2025-09-01 10:26:44.548 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 588/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.4, iou_loss: 2.3, l1_loss: 0.6, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:03:07
2025-09-01 10:26:46.370 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 588/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.002s, total_loss: 3.8, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:03:04
2025-09-01 10:26:47.181 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:26:47.222 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch589
2025-09-01 10:26:48.972 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 589/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.7, iou_loss: 1.8, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:03:01
2025-09-01 10:26:50.787 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 589/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.2, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:02:58
2025-09-01 10:26:52.575 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 589/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, 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: 0:02:56
2025-09-01 10:26:54.328 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 589/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, 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: 512, ETA: 0:02:54
2025-09-01 10:26:56.086 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 589/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 3.2, iou_loss: 1.4, l1_loss: 0.5, conf_loss: 0.9, cls_loss: 0.4, lr: 5.000e-04, size: 256, ETA: 0:02:51
2025-09-01 10:26:57.928 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 589/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 8.4, iou_loss: 2.8, l1_loss: 1.5, conf_loss: 3.4, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:02:49
2025-09-01 10:26:58.681 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:26:58.715 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch590
2025-09-01 10:27:00.446 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 590/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:02:45
2025-09-01 10:27:02.228 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 590/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.3, l1_loss: 0.7, conf_loss: 2.3, cls_loss: 0.9, lr: 5.000e-04, size: 256, ETA: 0:02:43
2025-09-01 10:27:03.902 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 590/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.078s, data_time: 0.002s, 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: 416, ETA: 0:02:41
2025-09-01 10:27:05.629 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 590/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 7.0, iou_loss: 2.9, l1_loss: 0.9, conf_loss: 2.5, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:02:38
2025-09-01 10:27:07.387 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 590/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 4.2, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 0.8, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:02:36
2025-09-01 10:27:09.153 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 590/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.001s, total_loss: 5.4, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:02:34
2025-09-01 10:27:09.949 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:27:15.927 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:27:16.636 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:27:17.021 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6128
2025-09-01 10:27:17.157 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5631
2025-09-01 10:27:17.195 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4028
2025-09-01 10:27:17.196 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5262
2025-09-01 10:27:17.196 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.613
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.563
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.403
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.526
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:27:17.197 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:27:17.198 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:27:17.198 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:27:17.198 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:27:17.198 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:27:17.747 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:27:18.300 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:27:18.854 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:27:19.574 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:27:20.189 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:27:20.822 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:27:21.368 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:27:21.910 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:27:22.492 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:27:22.492 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 10:27:22.492 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:27:22.493 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:27:22.499 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.40 ms, Average NMS time: 0.92 ms, Average inference time: 2.32 ms

2025-09-01 10:27:22.501 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:27:22.523 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:27:22.555 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch591
2025-09-01 10:27:24.181 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 591/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.9, conf_loss: 2.2, cls_loss: 0.6, lr: 5.000e-04, size: 512, ETA: 0:02:30
2025-09-01 10:27:25.918 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 591/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.0, l1_loss: 0.7, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:02:28
2025-09-01 10:27:27.667 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 591/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:02:25
2025-09-01 10:27:29.380 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 591/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.7, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:02:23
2025-09-01 10:27:31.137 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 591/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 1.1, cls_loss: 0.8, lr: 5.000e-04, size: 320, ETA: 0:02:21
2025-09-01 10:27:32.813 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 591/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.4, l1_loss: 1.1, conf_loss: 2.4, cls_loss: 0.6, lr: 5.000e-04, size: 480, ETA: 0:02:18
2025-09-01 10:27:33.605 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:27:33.654 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch592
2025-09-01 10:27:35.439 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 592/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.002s, total_loss: 4.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:02:15
2025-09-01 10:27:37.292 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 592/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 5.8, iou_loss: 2.4, l1_loss: 0.7, conf_loss: 2.0, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:02:12
2025-09-01 10:27:39.161 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 592/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:02:10
2025-09-01 10:27:40.799 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 592/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.3, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:02:08
2025-09-01 10:27:42.525 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 592/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.8, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:02:05
2025-09-01 10:27:44.265 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 592/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.4, l1_loss: 1.0, conf_loss: 1.9, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:02:03
2025-09-01 10:27:45.055 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:27:45.104 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch593
2025-09-01 10:27:46.832 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 593/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:01:59
2025-09-01 10:27:48.699 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 593/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.4, iou_loss: 1.9, l1_loss: 1.1, conf_loss: 2.8, cls_loss: 0.6, lr: 5.000e-04, size: 576, ETA: 0:01:57
2025-09-01 10:27:50.434 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 593/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.9, l1_loss: 1.0, conf_loss: 1.6, cls_loss: 1.0, lr: 5.000e-04, size: 544, ETA: 0:01:55
2025-09-01 10:27:52.192 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 593/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, 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: 0:01:52
2025-09-01 10:27:53.981 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 593/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, 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: 320, ETA: 0:01:50
2025-09-01 10:27:55.702 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 593/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.5, l1_loss: 0.5, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:01:47
2025-09-01 10:27:56.448 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:27:56.508 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch594
2025-09-01 10:27:58.242 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 594/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:01:44
2025-09-01 10:27:59.966 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 594/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 4.7, iou_loss: 2.1, l1_loss: 0.6, conf_loss: 1.5, cls_loss: 0.6, lr: 5.000e-04, size: 256, ETA: 0:01:42
2025-09-01 10:28:01.751 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 594/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, 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: 416, ETA: 0:01:39
2025-09-01 10:28:03.651 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 594/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 6.1, iou_loss: 2.1, l1_loss: 1.1, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:01:37
2025-09-01 10:28:05.370 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 594/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.2, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 320, ETA: 0:01:35
2025-09-01 10:28:07.158 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 594/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.8, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 352, ETA: 0:01:32
2025-09-01 10:28:07.886 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:28:07.926 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch595
2025-09-01 10:28:09.620 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 595/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 7.8, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 3.2, cls_loss: 0.8, lr: 5.000e-04, size: 416, ETA: 0:01:29
2025-09-01 10:28:11.320 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 595/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 5.5, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 2.5, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:01:26
2025-09-01 10:28:13.114 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 595/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.8, l1_loss: 0.9, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:01:24
2025-09-01 10:28:14.882 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 595/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.001s, total_loss: 6.0, iou_loss: 2.5, l1_loss: 0.9, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 352, ETA: 0:01:22
2025-09-01 10:28:16.679 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 595/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.3Gb, 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: 0.6, lr: 5.000e-04, size: 576, ETA: 0:01:19
2025-09-01 10:28:18.471 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 595/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 5.0, iou_loss: 1.9, l1_loss: 0.9, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:01:17
2025-09-01 10:28:19.227 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:28:25.021 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:28:25.702 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:28:26.227 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6272
2025-09-01 10:28:26.365 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5661
2025-09-01 10:28:26.402 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.4116
2025-09-01 10:28:26.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5350
2025-09-01 10:28:26.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:28:26.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:28:26.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.627
2025-09-01 10:28:26.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.566
2025-09-01 10:28:26.403 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.412
2025-09-01 10:28:26.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.535
2025-09-01 10:28:26.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:28:26.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:28:26.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:28:26.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:28:26.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:28:26.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:28:26.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:28:26.404 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:28:26.405 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:28:27.005 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:28:27.626 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:28:28.196 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:28:28.765 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:28:29.338 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:28:29.912 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:28:30.628 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:28:31.218 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:28:31.805 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:28:31.805 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 10:28:31.805 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.53
2025-09-01 10:28:31.806 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:28:31.812 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.42 ms, Average NMS time: 0.89 ms, Average inference time: 2.31 ms

2025-09-01 10:28:31.813 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:28:31.840 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:28:31.872 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch596
2025-09-01 10:28:33.566 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 596/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.001s, total_loss: 4.7, iou_loss: 2.0, l1_loss: 0.6, conf_loss: 1.6, cls_loss: 0.5, lr: 5.000e-04, size: 416, ETA: 0:01:13
2025-09-01 10:28:35.350 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 596/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.003s, total_loss: 4.5, iou_loss: 1.8, l1_loss: 0.8, conf_loss: 1.4, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:01:11
2025-09-01 10:28:37.134 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 596/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, 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: 0:01:09
2025-09-01 10:28:38.912 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 596/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 1.2, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:01:06
2025-09-01 10:28:40.691 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 596/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 8.0, iou_loss: 3.1, l1_loss: 1.2, conf_loss: 2.9, cls_loss: 0.7, lr: 5.000e-04, size: 416, ETA: 0:01:04
2025-09-01 10:28:42.436 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 596/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 4.9, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:01:02
2025-09-01 10:28:43.196 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:28:43.243 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch597
2025-09-01 10:28:44.998 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 597/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.085s, data_time: 0.002s, total_loss: 6.0, iou_loss: 2.2, l1_loss: 1.0, conf_loss: 2.1, cls_loss: 0.7, lr: 5.000e-04, size: 576, ETA: 0:00:58
2025-09-01 10:28:46.808 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 597/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.088s, data_time: 0.003s, total_loss: 4.2, iou_loss: 2.1, l1_loss: 0.7, conf_loss: 0.9, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:00:56
2025-09-01 10:28:48.548 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 597/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.7, iou_loss: 2.5, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.6, lr: 5.000e-04, size: 288, ETA: 0:00:53
2025-09-01 10:28:50.234 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 597/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.079s, data_time: 0.002s, total_loss: 4.2, iou_loss: 1.7, l1_loss: 0.3, conf_loss: 1.7, cls_loss: 0.5, lr: 5.000e-04, size: 288, ETA: 0:00:51
2025-09-01 10:28:51.941 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 597/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.7, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.6, cls_loss: 0.7, lr: 5.000e-04, size: 480, ETA: 0:00:49
2025-09-01 10:28:53.659 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 597/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 0.8, conf_loss: 2.3, cls_loss: 0.6, lr: 5.000e-04, size: 320, ETA: 0:00:46
2025-09-01 10:28:54.418 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:28:54.460 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch598
2025-09-01 10:28:56.171 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 598/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.7, l1_loss: 1.1, conf_loss: 1.8, cls_loss: 0.9, lr: 5.000e-04, size: 416, ETA: 0:00:43
2025-09-01 10:28:57.950 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 598/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.087s, data_time: 0.006s, 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: 544, ETA: 0:00:40
2025-09-01 10:28:59.727 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 598/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.3, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 2.0, cls_loss: 0.5, lr: 5.000e-04, size: 512, ETA: 0:00:38
2025-09-01 10:29:01.499 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 598/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.083s, data_time: 0.001s, total_loss: 4.8, iou_loss: 1.9, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 544, ETA: 0:00:36
2025-09-01 10:29:03.333 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 598/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, data_time: 0.002s, total_loss: 3.3, iou_loss: 1.6, l1_loss: 0.4, conf_loss: 0.9, cls_loss: 0.5, lr: 5.000e-04, size: 256, ETA: 0:00:33
2025-09-01 10:29:05.083 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 598/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, 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: 288, ETA: 0:00:31
2025-09-01 10:29:05.815 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:29:05.856 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch599
2025-09-01 10:29:07.573 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 599/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.5, iou_loss: 2.6, l1_loss: 0.8, conf_loss: 2.4, cls_loss: 0.7, lr: 5.000e-04, size: 448, ETA: 0:00:28
2025-09-01 10:29:09.358 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 599/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.5Gb, iter_time: 0.084s, data_time: 0.003s, total_loss: 6.2, iou_loss: 2.8, l1_loss: 0.8, conf_loss: 1.8, cls_loss: 0.7, lr: 5.000e-04, size: 288, ETA: 0:00:25
2025-09-01 10:29:11.243 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 599/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.091s, 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: 320, ETA: 0:00:23
2025-09-01 10:29:12.980 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 599/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.084s, data_time: 0.002s, total_loss: 5.1, iou_loss: 2.0, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.7, lr: 5.000e-04, size: 384, ETA: 0:00:21
2025-09-01 10:29:14.704 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 599/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 0.9, conf_loss: 2.4, cls_loss: 0.8, lr: 5.000e-04, size: 352, ETA: 0:00:18
2025-09-01 10:29:16.399 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 599/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 5.6, iou_loss: 1.9, l1_loss: 0.7, conf_loss: 2.1, cls_loss: 0.8, lr: 5.000e-04, size: 384, ETA: 0:00:16
2025-09-01 10:29:17.177 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:29:17.218 | INFO     | yolox_microbt.core.trainer:before_epoch:190 - ---> start train epoch600
2025-09-01 10:29:18.937 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 600/600, iter: 20/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.082s, data_time: 0.002s, total_loss: 4.4, iou_loss: 1.9, l1_loss: 0.5, conf_loss: 1.5, cls_loss: 0.5, lr: 5.000e-04, size: 480, ETA: 0:00:12
2025-09-01 10:29:20.815 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 600/600, iter: 40/129, gpu mem: 1663Mb, mem: 47.3Gb, iter_time: 0.090s, data_time: 0.003s, total_loss: 3.4, iou_loss: 1.7, l1_loss: 0.6, conf_loss: 0.7, cls_loss: 0.5, lr: 5.000e-04, size: 320, ETA: 0:00:10
2025-09-01 10:29:22.582 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 600/600, iter: 60/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.086s, 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: 576, ETA: 0:00:08
2025-09-01 10:29:24.458 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 600/600, iter: 80/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.090s, data_time: 0.002s, total_loss: 4.3, iou_loss: 1.9, l1_loss: 0.6, conf_loss: 1.4, cls_loss: 0.5, lr: 5.000e-04, size: 448, ETA: 0:00:05
2025-09-01 10:29:26.107 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 600/600, iter: 100/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.080s, data_time: 0.002s, total_loss: 5.2, iou_loss: 2.1, l1_loss: 0.8, conf_loss: 1.6, cls_loss: 0.6, lr: 5.000e-04, size: 384, ETA: 0:00:03
2025-09-01 10:29:27.787 | INFO     | yolox_microbt.core.trainer:after_iter:258 - epoch: 600/600, iter: 120/129, gpu mem: 1663Mb, mem: 47.4Gb, iter_time: 0.081s, data_time: 0.002s, total_loss: 6.4, iou_loss: 2.2, l1_loss: 0.8, conf_loss: 2.9, cls_loss: 0.6, lr: 5.000e-04, size: 416, ETA: 0:00:01
2025-09-01 10:29:28.556 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:29:34.463 | INFO     | yolox.evaluators.voc_evaluator:evaluate_prediction:144 - Evaluate in main process...
2025-09-01 10:29:35.362 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.50
2025-09-01 10:29:35.980 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for person = 0.6091
2025-09-01 10:29:36.137 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for car = 0.5370
2025-09-01 10:29:36.172 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:324 - AP for dog = 0.3623
2025-09-01 10:29:36.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:329 - Mean AP = 0.5028
2025-09-01 10:29:36.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:330 - ~~~~~~~~
2025-09-01 10:29:36.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:331 - Results:
2025-09-01 10:29:36.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.609
2025-09-01 10:29:36.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.537
2025-09-01 10:29:36.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:333 - 0.362
2025-09-01 10:29:36.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:334 - 0.503
2025-09-01 10:29:36.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:335 - ~~~~~~~~
2025-09-01 10:29:36.173 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:336 - 
2025-09-01 10:29:36.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:337 - --------------------------------------------------------------
2025-09-01 10:29:36.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:338 - Results computed with the **unofficial** Python eval code.
2025-09-01 10:29:36.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:339 - Results should be very close to the official MATLAB eval code.
2025-09-01 10:29:36.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:340 - Recompute with `./tools/reval.py --matlab ...` for your paper.
2025-09-01 10:29:36.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:341 - -- Thanks, The Management
2025-09-01 10:29:36.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:342 - --------------------------------------------------------------
2025-09-01 10:29:36.174 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.55
2025-09-01 10:29:36.953 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.60
2025-09-01 10:29:37.748 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.65
2025-09-01 10:29:38.504 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.70
2025-09-01 10:29:39.305 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.75
2025-09-01 10:29:40.058 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.80
2025-09-01 10:29:40.844 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.85
2025-09-01 10:29:41.687 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.90
2025-09-01 10:29:42.440 | INFO     | yolox_microbt.data.datasets.voc:_do_python_eval:304 - Eval IoU : 0.95
2025-09-01 10:29:43.230 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:252 - --------------------------------------------------------------
2025-09-01 10:29:43.230 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:253 - map_5095: 0.29
2025-09-01 10:29:43.230 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:254 - map_50: 0.50
2025-09-01 10:29:43.230 | INFO     | yolox_microbt.data.datasets.voc:evaluate_detections:255 - --------------------------------------------------------------
2025-09-01 10:29:43.237 | INFO     | yolox_microbt.core.trainer:evaluate_and_save_model:368 - 
Average forward time: 1.37 ms, Average NMS time: 0.90 ms, Average inference time: 2.27 ms

2025-09-01 10:29:43.238 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:29:43.275 | INFO     | yolox_microbt.core.trainer:save_ckpt:389 - Save weights to ./YOLOX_outputs/sa6921_vnne_3classes_voc_float_600e_185k_trainset
2025-09-01 10:29:43.315 | INFO     | yolox_microbt.core.trainer:after_train:172 - Training of experiment is done and the best AP is 30.96
