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[2024-11-25 20:48:31,396][ train_val.py][line: 116][ INFO] args: Namespace(config='../configs/onenip_config.yaml', evaluate=True, local_rank='0', opts=['dataset.image_reader.kwargs.image_dir', '/fuxi_team2/persons/danylgao/weicun_ceph/datasets/mvtec+btad+visa', 'dataset.train.dtd_dir', '/fuxi_team2/persons/danylgao/weicun_ceph/datasets/dtd', 'dataset.train.meta_file', '../data/mvtec+btad+visa/train.json', 'dataset.test.meta_file', '../data/mvtec+btad+visa/test.json', 'dataset.input_size', '[320, 320]', 'net[2].kwargs.num_encoder_layers', '4', 'net[2].kwargs.num_decoder_layers', '4', 'saver.save_dir', '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320'])
[2024-11-25 20:48:31,398][ train_val.py][line: 117][ INFO] config: {'criterion': [{'kwargs': {'weight': 1.0},
'name': 'FeatureMSELoss',
'type': 'FeatureMSELoss'},
{'kwargs': {'weight': 0.5},
'name': 'DiceLoss',
'type': 'DiceLoss'}],
'dataset': {'batch_size': 8,
'image_reader': {'kwargs': {'color_mode': 'RGB',
'image_dir': '/fuxi_team2/persons/danylgao/weicun_ceph/datasets/mvtec+btad+visa'},
'type': 'opencv'},
'input_size': [320, 320],
'pixel_mean': [0.485, 0.456, 0.406],
'pixel_std': [0.229, 0.224, 0.225],
'test': {'meta_file': '../data/mvtec+btad+visa/test.json'},
'train': {'dtd_dir': '/fuxi_team2/persons/danylgao/weicun_ceph/datasets/dtd',
'hflip': False,
'meta_file': '../data/mvtec+btad+visa/train.json',
'rebalance': False,
'rotate': False,
'vflip': False},
'type': 'onenip',
'workers': 4},
'evaluator': {'eval_dir': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320/result_eval_temp',
'key_metric': 'mean_pixel_auc',
'metrics': {'auc': [{'kwargs': {'avgpool_size': [16, 16]},
'name': 'max'},
{'name': 'pixel'}]},
'save_dir': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320/result_eval_temp',
'vis_compound': {'max_score': None,
'min_score': None,
'save_dir': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320/vis_compound'}},
'exp_path': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320',
'frozen_layers': ['backbone'],
'log_path': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320/log',
'net': [{'frozen': True,
'kwargs': {'outblocks': [1, 5, 9, 21],
'outstrides': [2, 4, 8, 16],
'pretrained': True},
'name': 'backbone',
'type': 'models.backbones.efficientnet_b4'},
{'kwargs': {'outplanes': [272], 'outstrides': [16]},
'name': 'neck',
'prev': 'backbone',
'type': 'models.necks.MFCN'},
{'kwargs': {'activation': 'relu',
'dim_feedforward': 1024,
'dropout': 0.1,
'feature_jitter': {'prob': 1.0, 'scale': 20.0},
'feature_size': [20, 20],
'hidden_dim': 256,
'initializer': {'method': 'xavier_uniform'},
'neighbor_mask': {'mask': [True, True, True],
'neighbor_size': [10, 10]},
'nhead': 8,
'normalize_before': False,
'num_decoder_layers': 4.0,
'num_encoder_layers': 4.0,
'pos_embed_type': 'learned',
'save_recon': {'save_dir': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320/result_recon'}},
'name': 'reconstruction',
'prev': 'neck',
'type': 'models.reconstructions.OneNIP'}],
'port': 11111,
'random_seed': 133,
'save_path': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320',
'saver': {'always_save': False,
'auto_resume': False,
'load_path': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320/ckpt.pkl',
'log_dir': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320/log',
'save_dir': '../checkpoints-retraining-1111/onenip-mvtec+btad+visa-4-4-320'},
'trainer': {'clip_max_norm': 0.1,
'lr_scheduler': {'kwargs': {'gamma': 0.1, 'step_size': 800},
'type': 'StepLR'},
'max_epoch': 1000,
'optimizer': {'kwargs': {'betas': [0.9, 0.999],
'lr': 0.0001,
'weight_decay': 0.0001},
'type': 'AdamW'},
'print_freq_step': 1,
'tb_freq_step': 1,
'val_freq_epoch': 10},
'version': 'v1.0.0'}
[2024-11-25 20:48:31,779][ utils.py][line: 740][ INFO] not exist, load from https://github.com/lukemelas/EfficientNet-PyTorch/releases/download/1.0/efficientnet-b4-6ed6700e.pth
[2024-11-25 20:48:31,896][ utils.py][line: 761][ INFO] Loaded ImageNet pretrained efficientnet-b4
[2024-11-25 20:48:35,654][ train_val.py][line: 143][ INFO] layers: ['backbone', 'neck', 'reconstruction']
[2024-11-25 20:48:35,654][ train_val.py][line: 144][ INFO] active layers: ['neck', 'reconstruction']
[2024-11-25 20:48:44,680][custom_dataset.py][line: 175][ INFO] building CustomDataset from: ../data/mvtec+btad+visa/train.json
[2024-11-25 20:48:44,777][custom_dataset.py][line: 175][ INFO] building CustomDataset from: ../data/mvtec+btad+visa/test.json
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[2024-11-25 20:53:15,931][ train_val.py][line: 392][ INFO] Gathering final results ...
[2024-11-25 20:53:15,932][ train_val.py][line: 394][ INFO] * Loss 5.18637 total_num=4628.0
[2024-11-25 20:58:46,814][ eval_helper.py][line: 343][ INFO]
| clsname | max_auc | max_ap | pixel_auc | pixel_ap |
|:----------:|:---------:|:--------:|:-----------:|:----------:|
| 01 | 99.9028 | 99.9592 | 98.1321 | 66.9595 |
| 02 | 84.3411 | 97.4561 | 96.9983 | 66.8145 |
| 03 | 99.2526 | 90.713 | 99.6267 | 58.2697 |
| bottle | 99.8413 | 99.9512 | 98.0281 | 77.8237 |
| cable | 94.9775 | 97.3864 | 96.576 | 53.3999 |
| candle | 96.79 | 96.9572 | 99.4605 | 33.3569 |
| capsule | 90.5066 | 97.7088 | 98.8327 | 53.0329 |
| capsules | 83.9 | 91.5791 | 99.0935 | 59.5791 |
| carpet | 99.8796 | 99.9634 | 99.2779 | 76.0377 |
| cashew | 89.02 | 94.3662 | 97.0285 | 52.1332 |
| chewinggum | 99.54 | 99.798 | 99.1324 | 62.364 |
| fryum | 93.64 | 96.9864 | 96.96 | 42.8372 |
| grid | 98.5798 | 99.597 | 98.8479 | 52.6452 |
| hazelnut | 99.3214 | 99.5587 | 97.5634 | 57.9697 |
| leather | 100 | 100 | 99.6805 | 74.8001 |
| macaroni1 | 94.32 | 94.6294 | 99.528 | 29.3498 |
| macaroni2 | 82.47 | 83.6732 | 98.9454 | 12.9008 |
| metal_nut | 99.7067 | 99.9314 | 93.1692 | 59.0764 |
| pcb1 | 97.75 | 97.0222 | 99.7295 | 78.7282 |
| pcb2 | 96.11 | 96.0981 | 98.8421 | 15.3277 |
| pcb3 | 95.0891 | 96.0798 | 99.1157 | 26.3537 |
| pcb4 | 99.6634 | 99.66 | 97.7044 | 44.1281 |
| pill | 93.2624 | 98.7356 | 95.5627 | 46.0952 |
| pipe_fryum | 98.12 | 99.1571 | 99.1028 | 60.5437 |
| screw | 89.9775 | 96.5787 | 99.145 | 48.5419 |
| tile | 99.8557 | 99.943 | 94.9554 | 73.6619 |
| toothbrush | 93.6111 | 97.3895 | 98.6143 | 51.5741 |
| transistor | 98.2917 | 97.3447 | 94.749 | 60.2709 |
| wood | 99.386 | 99.8207 | 94.7803 | 62.2907 |
| zipper | 99.6849 | 99.9173 | 98.2727 | 66.527 |
| mean | 95.5597 | 97.2654 | 97.9152 | 54.1131 |