-
Notifications
You must be signed in to change notification settings - Fork 1
/
dec_20241125_201314.log
326 lines (326 loc) · 27.7 KB
/
dec_20241125_201314.log
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
[2024-11-25 20:13:14,709][ 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', 'dataset.train.dtd_dir', '/fuxi_team2/persons/danylgao/weicun_ceph/datasets/dtd', 'dataset.train.meta_file', '../data/mvtec/train.json', 'dataset.test.meta_file', '../data/mvtec/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-4-4-320'])
[2024-11-25 20:13:14,714][ 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'},
'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/test.json'},
'train': {'dtd_dir': '/fuxi_team2/persons/danylgao/weicun_ceph/datasets/dtd',
'hflip': False,
'meta_file': '../data/mvtec/train.json',
'rebalance': False,
'rotate': False,
'vflip': False},
'type': 'onenip',
'workers': 4},
'evaluator': {'eval_dir': '../checkpoints-retraining-1111/onenip-mvtec-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-4-4-320/result_eval_temp',
'vis_compound': {'max_score': None,
'min_score': None,
'save_dir': '../checkpoints-retraining-1111/onenip-mvtec-4-4-320/vis_compound'}},
'exp_path': '../checkpoints-retraining-1111/onenip-mvtec-4-4-320',
'frozen_layers': ['backbone'],
'log_path': '../checkpoints-retraining-1111/onenip-mvtec-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-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-4-4-320',
'saver': {'always_save': False,
'auto_resume': False,
'load_path': '../checkpoints-retraining-1111/onenip-mvtec-4-4-320/ckpt.pkl',
'log_dir': '../checkpoints-retraining-1111/onenip-mvtec-4-4-320/log',
'save_dir': '../checkpoints-retraining-1111/onenip-mvtec-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 20:13:15,129][ 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 20:13:15,259][ utils.py][line: 761][ INFO] Loaded ImageNet pretrained efficientnet-b4
[2024-11-25 20:13:18,874][ train_val.py][line: 143][ INFO] layers: ['backbone', 'neck', 'reconstruction']
[2024-11-25 20:13:18,874][ train_val.py][line: 144][ INFO] active layers: ['reconstruction', 'neck']
[2024-11-25 20:13:29,149][custom_dataset.py][line: 175][ INFO] building CustomDataset from: ../data/mvtec/train.json
[2024-11-25 20:13:29,194][custom_dataset.py][line: 175][ INFO] building CustomDataset from: ../data/mvtec/test.json
[2024-11-25 20:13:33,345][ train_val.py][line: 371][ INFO] Test: [1/216] Time 4.113 (4.113)
[2024-11-25 20:13:33,785][ train_val.py][line: 371][ INFO] Test: [2/216] Time 0.440 (2.277)
[2024-11-25 20:13:34,227][ train_val.py][line: 371][ INFO] Test: [3/216] Time 0.442 (1.665)
[2024-11-25 20:13:34,653][ train_val.py][line: 371][ INFO] Test: [4/216] Time 0.425 (1.355)
[2024-11-25 20:13:35,093][ train_val.py][line: 371][ INFO] Test: [5/216] Time 0.440 (1.172)
[2024-11-25 20:13:35,522][ train_val.py][line: 371][ INFO] Test: [6/216] Time 0.429 (1.048)
[2024-11-25 20:13:35,963][ train_val.py][line: 371][ INFO] Test: [7/216] Time 0.441 (0.962)
[2024-11-25 20:13:36,422][ train_val.py][line: 371][ INFO] Test: [8/216] Time 0.458 (0.899)
[2024-11-25 20:13:36,858][ train_val.py][line: 371][ INFO] Test: [9/216] Time 0.436 (0.847)
[2024-11-25 20:13:37,345][ train_val.py][line: 371][ INFO] Test: [10/216] Time 0.487 (0.811)
[2024-11-25 20:13:37,825][ train_val.py][line: 371][ INFO] Test: [11/216] Time 0.481 (0.781)
[2024-11-25 20:13:38,249][ train_val.py][line: 371][ INFO] Test: [12/216] Time 0.423 (0.751)
[2024-11-25 20:13:38,683][ train_val.py][line: 371][ INFO] Test: [13/216] Time 0.434 (0.727)
[2024-11-25 20:13:39,126][ train_val.py][line: 371][ INFO] Test: [14/216] Time 0.443 (0.707)
[2024-11-25 20:13:39,549][ train_val.py][line: 371][ INFO] Test: [15/216] Time 0.423 (0.688)
[2024-11-25 20:13:39,976][ train_val.py][line: 371][ INFO] Test: [16/216] Time 0.427 (0.671)
[2024-11-25 20:13:40,409][ train_val.py][line: 371][ INFO] Test: [17/216] Time 0.434 (0.658)
[2024-11-25 20:13:40,854][ train_val.py][line: 371][ INFO] Test: [18/216] Time 0.445 (0.646)
[2024-11-25 20:13:41,289][ train_val.py][line: 371][ INFO] Test: [19/216] Time 0.434 (0.635)
[2024-11-25 20:13:41,730][ train_val.py][line: 371][ INFO] Test: [20/216] Time 0.441 (0.625)
[2024-11-25 20:13:42,158][ train_val.py][line: 371][ INFO] Test: [21/216] Time 0.429 (0.616)
[2024-11-25 20:13:42,592][ train_val.py][line: 371][ INFO] Test: [22/216] Time 0.434 (0.607)
[2024-11-25 20:13:43,033][ train_val.py][line: 371][ INFO] Test: [23/216] Time 0.441 (0.600)
[2024-11-25 20:13:43,544][ train_val.py][line: 371][ INFO] Test: [24/216] Time 0.511 (0.596)
[2024-11-25 20:13:43,980][ train_val.py][line: 371][ INFO] Test: [25/216] Time 0.436 (0.590)
[2024-11-25 20:13:44,401][ train_val.py][line: 371][ INFO] Test: [26/216] Time 0.421 (0.583)
[2024-11-25 20:13:44,824][ train_val.py][line: 371][ INFO] Test: [27/216] Time 0.423 (0.577)
[2024-11-25 20:13:45,300][ train_val.py][line: 371][ INFO] Test: [28/216] Time 0.476 (0.574)
[2024-11-25 20:13:45,764][ train_val.py][line: 371][ INFO] Test: [29/216] Time 0.464 (0.570)
[2024-11-25 20:13:46,187][ train_val.py][line: 371][ INFO] Test: [30/216] Time 0.423 (0.565)
[2024-11-25 20:13:46,624][ train_val.py][line: 371][ INFO] Test: [31/216] Time 0.437 (0.561)
[2024-11-25 20:13:47,064][ train_val.py][line: 371][ INFO] Test: [32/216] Time 0.440 (0.557)
[2024-11-25 20:13:47,491][ train_val.py][line: 371][ INFO] Test: [33/216] Time 0.427 (0.553)
[2024-11-25 20:13:47,932][ train_val.py][line: 371][ INFO] Test: [34/216] Time 0.441 (0.550)
[2024-11-25 20:13:48,352][ train_val.py][line: 371][ INFO] Test: [35/216] Time 0.420 (0.546)
[2024-11-25 20:13:48,785][ train_val.py][line: 371][ INFO] Test: [36/216] Time 0.433 (0.543)
[2024-11-25 20:13:49,211][ train_val.py][line: 371][ INFO] Test: [37/216] Time 0.426 (0.540)
[2024-11-25 20:13:49,666][ train_val.py][line: 371][ INFO] Test: [38/216] Time 0.455 (0.538)
[2024-11-25 20:13:50,107][ train_val.py][line: 371][ INFO] Test: [39/216] Time 0.441 (0.535)
[2024-11-25 20:13:50,533][ train_val.py][line: 371][ INFO] Test: [40/216] Time 0.426 (0.533)
[2024-11-25 20:13:50,968][ train_val.py][line: 371][ INFO] Test: [41/216] Time 0.435 (0.530)
[2024-11-25 20:13:51,389][ train_val.py][line: 371][ INFO] Test: [42/216] Time 0.421 (0.528)
[2024-11-25 20:13:51,819][ train_val.py][line: 371][ INFO] Test: [43/216] Time 0.430 (0.525)
[2024-11-25 20:13:52,251][ train_val.py][line: 371][ INFO] Test: [44/216] Time 0.432 (0.523)
[2024-11-25 20:13:52,674][ train_val.py][line: 371][ INFO] Test: [45/216] Time 0.423 (0.521)
[2024-11-25 20:13:53,099][ train_val.py][line: 371][ INFO] Test: [46/216] Time 0.425 (0.519)
[2024-11-25 20:13:53,520][ train_val.py][line: 371][ INFO] Test: [47/216] Time 0.421 (0.517)
[2024-11-25 20:13:53,940][ train_val.py][line: 371][ INFO] Test: [48/216] Time 0.420 (0.515)
[2024-11-25 20:13:54,393][ train_val.py][line: 371][ INFO] Test: [49/216] Time 0.453 (0.513)
[2024-11-25 20:13:54,836][ train_val.py][line: 371][ INFO] Test: [50/216] Time 0.443 (0.512)
[2024-11-25 20:13:55,296][ train_val.py][line: 371][ INFO] Test: [51/216] Time 0.460 (0.511)
[2024-11-25 20:13:55,737][ train_val.py][line: 371][ INFO] Test: [52/216] Time 0.441 (0.510)
[2024-11-25 20:13:56,177][ train_val.py][line: 371][ INFO] Test: [53/216] Time 0.440 (0.508)
[2024-11-25 20:13:56,606][ train_val.py][line: 371][ INFO] Test: [54/216] Time 0.429 (0.507)
[2024-11-25 20:13:57,045][ train_val.py][line: 371][ INFO] Test: [55/216] Time 0.439 (0.506)
[2024-11-25 20:13:57,468][ train_val.py][line: 371][ INFO] Test: [56/216] Time 0.423 (0.504)
[2024-11-25 20:13:57,895][ train_val.py][line: 371][ INFO] Test: [57/216] Time 0.427 (0.503)
[2024-11-25 20:13:58,321][ train_val.py][line: 371][ INFO] Test: [58/216] Time 0.427 (0.502)
[2024-11-25 20:13:58,759][ train_val.py][line: 371][ INFO] Test: [59/216] Time 0.438 (0.500)
[2024-11-25 20:13:59,185][ train_val.py][line: 371][ INFO] Test: [60/216] Time 0.426 (0.499)
[2024-11-25 20:13:59,622][ train_val.py][line: 371][ INFO] Test: [61/216] Time 0.437 (0.498)
[2024-11-25 20:14:00,072][ train_val.py][line: 371][ INFO] Test: [62/216] Time 0.450 (0.497)
[2024-11-25 20:14:00,511][ train_val.py][line: 371][ INFO] Test: [63/216] Time 0.439 (0.496)
[2024-11-25 20:14:00,943][ train_val.py][line: 371][ INFO] Test: [64/216] Time 0.432 (0.495)
[2024-11-25 20:14:01,397][ train_val.py][line: 371][ INFO] Test: [65/216] Time 0.454 (0.495)
[2024-11-25 20:14:03,798][ train_val.py][line: 371][ INFO] Test: [66/216] Time 2.401 (0.524)
[2024-11-25 20:14:04,402][ train_val.py][line: 371][ INFO] Test: [67/216] Time 0.604 (0.525)
[2024-11-25 20:14:04,887][ train_val.py][line: 371][ INFO] Test: [68/216] Time 0.485 (0.524)
[2024-11-25 20:14:05,328][ train_val.py][line: 371][ INFO] Test: [69/216] Time 0.441 (0.523)
[2024-11-25 20:14:05,753][ train_val.py][line: 371][ INFO] Test: [70/216] Time 0.425 (0.522)
[2024-11-25 20:14:06,179][ train_val.py][line: 371][ INFO] Test: [71/216] Time 0.426 (0.520)
[2024-11-25 20:14:06,623][ train_val.py][line: 371][ INFO] Test: [72/216] Time 0.444 (0.519)
[2024-11-25 20:14:07,064][ train_val.py][line: 371][ INFO] Test: [73/216] Time 0.441 (0.518)
[2024-11-25 20:14:07,511][ train_val.py][line: 371][ INFO] Test: [74/216] Time 0.447 (0.517)
[2024-11-25 20:14:07,937][ train_val.py][line: 371][ INFO] Test: [75/216] Time 0.425 (0.516)
[2024-11-25 20:14:08,388][ train_val.py][line: 371][ INFO] Test: [76/216] Time 0.451 (0.515)
[2024-11-25 20:14:08,815][ train_val.py][line: 371][ INFO] Test: [77/216] Time 0.426 (0.514)
[2024-11-25 20:14:09,251][ train_val.py][line: 371][ INFO] Test: [78/216] Time 0.436 (0.513)
[2024-11-25 20:14:09,676][ train_val.py][line: 371][ INFO] Test: [79/216] Time 0.425 (0.512)
[2024-11-25 20:14:10,113][ train_val.py][line: 371][ INFO] Test: [80/216] Time 0.437 (0.511)
[2024-11-25 20:14:10,577][ train_val.py][line: 371][ INFO] Test: [81/216] Time 0.465 (0.510)
[2024-11-25 20:14:11,017][ train_val.py][line: 371][ INFO] Test: [82/216] Time 0.440 (0.510)
[2024-11-25 20:14:11,442][ train_val.py][line: 371][ INFO] Test: [83/216] Time 0.425 (0.509)
[2024-11-25 20:14:11,867][ train_val.py][line: 371][ INFO] Test: [84/216] Time 0.425 (0.508)
[2024-11-25 20:14:12,292][ train_val.py][line: 371][ INFO] Test: [85/216] Time 0.425 (0.507)
[2024-11-25 20:14:12,734][ train_val.py][line: 371][ INFO] Test: [86/216] Time 0.442 (0.506)
[2024-11-25 20:14:13,156][ train_val.py][line: 371][ INFO] Test: [87/216] Time 0.422 (0.505)
[2024-11-25 20:14:13,698][ train_val.py][line: 371][ INFO] Test: [88/216] Time 0.542 (0.505)
[2024-11-25 20:14:14,130][ train_val.py][line: 371][ INFO] Test: [89/216] Time 0.432 (0.504)
[2024-11-25 20:14:14,582][ train_val.py][line: 371][ INFO] Test: [90/216] Time 0.452 (0.504)
[2024-11-25 20:14:15,008][ train_val.py][line: 371][ INFO] Test: [91/216] Time 0.426 (0.503)
[2024-11-25 20:14:15,430][ train_val.py][line: 371][ INFO] Test: [92/216] Time 0.422 (0.502)
[2024-11-25 20:14:15,871][ train_val.py][line: 371][ INFO] Test: [93/216] Time 0.440 (0.501)
[2024-11-25 20:14:16,307][ train_val.py][line: 371][ INFO] Test: [94/216] Time 0.436 (0.501)
[2024-11-25 20:14:16,749][ train_val.py][line: 371][ INFO] Test: [95/216] Time 0.442 (0.500)
[2024-11-25 20:14:17,177][ train_val.py][line: 371][ INFO] Test: [96/216] Time 0.428 (0.499)
[2024-11-25 20:14:17,614][ train_val.py][line: 371][ INFO] Test: [97/216] Time 0.437 (0.499)
[2024-11-25 20:14:18,038][ train_val.py][line: 371][ INFO] Test: [98/216] Time 0.424 (0.498)
[2024-11-25 20:14:18,464][ train_val.py][line: 371][ INFO] Test: [99/216] Time 0.427 (0.497)
[2024-11-25 20:14:18,903][ train_val.py][line: 371][ INFO] Test: [100/216] Time 0.439 (0.497)
[2024-11-25 20:14:19,342][ train_val.py][line: 371][ INFO] Test: [101/216] Time 0.439 (0.496)
[2024-11-25 20:14:19,771][ train_val.py][line: 371][ INFO] Test: [102/216] Time 0.429 (0.495)
[2024-11-25 20:14:20,249][ train_val.py][line: 371][ INFO] Test: [103/216] Time 0.478 (0.495)
[2024-11-25 20:14:20,670][ train_val.py][line: 371][ INFO] Test: [104/216] Time 0.420 (0.495)
[2024-11-25 20:14:21,093][ train_val.py][line: 371][ INFO] Test: [105/216] Time 0.423 (0.494)
[2024-11-25 20:14:21,519][ train_val.py][line: 371][ INFO] Test: [106/216] Time 0.426 (0.493)
[2024-11-25 20:14:21,952][ train_val.py][line: 371][ INFO] Test: [107/216] Time 0.433 (0.493)
[2024-11-25 20:14:22,392][ train_val.py][line: 371][ INFO] Test: [108/216] Time 0.440 (0.492)
[2024-11-25 20:14:22,833][ train_val.py][line: 371][ INFO] Test: [109/216] Time 0.441 (0.492)
[2024-11-25 20:14:23,260][ train_val.py][line: 371][ INFO] Test: [110/216] Time 0.427 (0.491)
[2024-11-25 20:14:23,683][ train_val.py][line: 371][ INFO] Test: [111/216] Time 0.423 (0.491)
[2024-11-25 20:14:24,119][ train_val.py][line: 371][ INFO] Test: [112/216] Time 0.436 (0.490)
[2024-11-25 20:14:24,541][ train_val.py][line: 371][ INFO] Test: [113/216] Time 0.422 (0.489)
[2024-11-25 20:14:24,975][ train_val.py][line: 371][ INFO] Test: [114/216] Time 0.434 (0.489)
[2024-11-25 20:14:25,402][ train_val.py][line: 371][ INFO] Test: [115/216] Time 0.427 (0.488)
[2024-11-25 20:14:25,838][ train_val.py][line: 371][ INFO] Test: [116/216] Time 0.436 (0.488)
[2024-11-25 20:14:26,279][ train_val.py][line: 371][ INFO] Test: [117/216] Time 0.441 (0.488)
[2024-11-25 20:14:26,709][ train_val.py][line: 371][ INFO] Test: [118/216] Time 0.430 (0.487)
[2024-11-25 20:14:27,183][ train_val.py][line: 371][ INFO] Test: [119/216] Time 0.474 (0.487)
[2024-11-25 20:14:27,624][ train_val.py][line: 371][ INFO] Test: [120/216] Time 0.441 (0.487)
[2024-11-25 20:14:28,049][ train_val.py][line: 371][ INFO] Test: [121/216] Time 0.425 (0.486)
[2024-11-25 20:14:28,487][ train_val.py][line: 371][ INFO] Test: [122/216] Time 0.438 (0.486)
[2024-11-25 20:14:28,911][ train_val.py][line: 371][ INFO] Test: [123/216] Time 0.424 (0.485)
[2024-11-25 20:14:29,339][ train_val.py][line: 371][ INFO] Test: [124/216] Time 0.428 (0.485)
[2024-11-25 20:14:29,772][ train_val.py][line: 371][ INFO] Test: [125/216] Time 0.433 (0.484)
[2024-11-25 20:14:30,242][ train_val.py][line: 371][ INFO] Test: [126/216] Time 0.470 (0.484)
[2024-11-25 20:14:30,666][ train_val.py][line: 371][ INFO] Test: [127/216] Time 0.425 (0.484)
[2024-11-25 20:14:31,098][ train_val.py][line: 371][ INFO] Test: [128/216] Time 0.432 (0.483)
[2024-11-25 20:14:31,539][ train_val.py][line: 371][ INFO] Test: [129/216] Time 0.441 (0.483)
[2024-11-25 20:14:31,980][ train_val.py][line: 371][ INFO] Test: [130/216] Time 0.441 (0.483)
[2024-11-25 20:14:32,406][ train_val.py][line: 371][ INFO] Test: [131/216] Time 0.426 (0.482)
[2024-11-25 20:14:32,842][ train_val.py][line: 371][ INFO] Test: [132/216] Time 0.436 (0.482)
[2024-11-25 20:14:33,281][ train_val.py][line: 371][ INFO] Test: [133/216] Time 0.439 (0.482)
[2024-11-25 20:14:33,708][ train_val.py][line: 371][ INFO] Test: [134/216] Time 0.427 (0.481)
[2024-11-25 20:14:34,149][ train_val.py][line: 371][ INFO] Test: [135/216] Time 0.441 (0.481)
[2024-11-25 20:14:34,585][ train_val.py][line: 371][ INFO] Test: [136/216] Time 0.437 (0.481)
[2024-11-25 20:14:35,038][ train_val.py][line: 371][ INFO] Test: [137/216] Time 0.452 (0.480)
[2024-11-25 20:14:35,460][ train_val.py][line: 371][ INFO] Test: [138/216] Time 0.423 (0.480)
[2024-11-25 20:14:35,899][ train_val.py][line: 371][ INFO] Test: [139/216] Time 0.439 (0.480)
[2024-11-25 20:14:36,324][ train_val.py][line: 371][ INFO] Test: [140/216] Time 0.425 (0.479)
[2024-11-25 20:14:36,763][ train_val.py][line: 371][ INFO] Test: [141/216] Time 0.439 (0.479)
[2024-11-25 20:14:37,206][ train_val.py][line: 371][ INFO] Test: [142/216] Time 0.443 (0.479)
[2024-11-25 20:14:37,635][ train_val.py][line: 371][ INFO] Test: [143/216] Time 0.429 (0.478)
[2024-11-25 20:14:38,092][ train_val.py][line: 371][ INFO] Test: [144/216] Time 0.457 (0.478)
[2024-11-25 20:14:38,534][ train_val.py][line: 371][ INFO] Test: [145/216] Time 0.442 (0.478)
[2024-11-25 20:14:38,966][ train_val.py][line: 371][ INFO] Test: [146/216] Time 0.432 (0.478)
[2024-11-25 20:14:39,401][ train_val.py][line: 371][ INFO] Test: [147/216] Time 0.435 (0.477)
[2024-11-25 20:14:39,825][ train_val.py][line: 371][ INFO] Test: [148/216] Time 0.425 (0.477)
[2024-11-25 20:14:40,280][ train_val.py][line: 371][ INFO] Test: [149/216] Time 0.455 (0.477)
[2024-11-25 20:14:40,705][ train_val.py][line: 371][ INFO] Test: [150/216] Time 0.425 (0.476)
[2024-11-25 20:14:41,132][ train_val.py][line: 371][ INFO] Test: [151/216] Time 0.427 (0.476)
[2024-11-25 20:14:41,586][ train_val.py][line: 371][ INFO] Test: [152/216] Time 0.454 (0.476)
[2024-11-25 20:14:42,030][ train_val.py][line: 371][ INFO] Test: [153/216] Time 0.444 (0.476)
[2024-11-25 20:14:42,461][ train_val.py][line: 371][ INFO] Test: [154/216] Time 0.431 (0.476)
[2024-11-25 20:14:42,898][ train_val.py][line: 371][ INFO] Test: [155/216] Time 0.437 (0.475)
[2024-11-25 20:14:43,340][ train_val.py][line: 371][ INFO] Test: [156/216] Time 0.442 (0.475)
[2024-11-25 20:14:43,900][ train_val.py][line: 371][ INFO] Test: [157/216] Time 0.560 (0.476)
[2024-11-25 20:14:44,324][ train_val.py][line: 371][ INFO] Test: [158/216] Time 0.424 (0.475)
[2024-11-25 20:14:44,751][ train_val.py][line: 371][ INFO] Test: [159/216] Time 0.427 (0.475)
[2024-11-25 20:14:45,289][ train_val.py][line: 371][ INFO] Test: [160/216] Time 0.538 (0.475)
[2024-11-25 20:14:45,720][ train_val.py][line: 371][ INFO] Test: [161/216] Time 0.431 (0.475)
[2024-11-25 20:14:46,173][ train_val.py][line: 371][ INFO] Test: [162/216] Time 0.453 (0.475)
[2024-11-25 20:14:46,601][ train_val.py][line: 371][ INFO] Test: [163/216] Time 0.428 (0.475)
[2024-11-25 20:14:47,036][ train_val.py][line: 371][ INFO] Test: [164/216] Time 0.435 (0.474)
[2024-11-25 20:14:47,463][ train_val.py][line: 371][ INFO] Test: [165/216] Time 0.427 (0.474)
[2024-11-25 20:14:47,886][ train_val.py][line: 371][ INFO] Test: [166/216] Time 0.423 (0.474)
[2024-11-25 20:14:48,312][ train_val.py][line: 371][ INFO] Test: [167/216] Time 0.426 (0.474)
[2024-11-25 20:14:48,746][ train_val.py][line: 371][ INFO] Test: [168/216] Time 0.435 (0.473)
[2024-11-25 20:14:49,185][ train_val.py][line: 371][ INFO] Test: [169/216] Time 0.439 (0.473)
[2024-11-25 20:14:49,627][ train_val.py][line: 371][ INFO] Test: [170/216] Time 0.442 (0.473)
[2024-11-25 20:14:50,051][ train_val.py][line: 371][ INFO] Test: [171/216] Time 0.424 (0.473)
[2024-11-25 20:14:50,480][ train_val.py][line: 371][ INFO] Test: [172/216] Time 0.428 (0.472)
[2024-11-25 20:14:50,914][ train_val.py][line: 371][ INFO] Test: [173/216] Time 0.434 (0.472)
[2024-11-25 20:14:51,339][ train_val.py][line: 371][ INFO] Test: [174/216] Time 0.425 (0.472)
[2024-11-25 20:14:51,782][ train_val.py][line: 371][ INFO] Test: [175/216] Time 0.443 (0.472)
[2024-11-25 20:14:52,218][ train_val.py][line: 371][ INFO] Test: [176/216] Time 0.436 (0.472)
[2024-11-25 20:14:52,642][ train_val.py][line: 371][ INFO] Test: [177/216] Time 0.423 (0.471)
[2024-11-25 20:14:53,080][ train_val.py][line: 371][ INFO] Test: [178/216] Time 0.438 (0.471)
[2024-11-25 20:14:53,519][ train_val.py][line: 371][ INFO] Test: [179/216] Time 0.439 (0.471)
[2024-11-25 20:14:53,960][ train_val.py][line: 371][ INFO] Test: [180/216] Time 0.441 (0.471)
[2024-11-25 20:14:54,401][ train_val.py][line: 371][ INFO] Test: [181/216] Time 0.441 (0.471)
[2024-11-25 20:14:54,830][ train_val.py][line: 371][ INFO] Test: [182/216] Time 0.429 (0.470)
[2024-11-25 20:14:55,304][ train_val.py][line: 371][ INFO] Test: [183/216] Time 0.474 (0.470)
[2024-11-25 20:14:55,732][ train_val.py][line: 371][ INFO] Test: [184/216] Time 0.428 (0.470)
[2024-11-25 20:14:56,167][ train_val.py][line: 371][ INFO] Test: [185/216] Time 0.435 (0.470)
[2024-11-25 20:14:56,591][ train_val.py][line: 371][ INFO] Test: [186/216] Time 0.424 (0.470)
[2024-11-25 20:14:57,016][ train_val.py][line: 371][ INFO] Test: [187/216] Time 0.424 (0.469)
[2024-11-25 20:14:57,461][ train_val.py][line: 371][ INFO] Test: [188/216] Time 0.446 (0.469)
[2024-11-25 20:14:57,897][ train_val.py][line: 371][ INFO] Test: [189/216] Time 0.436 (0.469)
[2024-11-25 20:14:58,323][ train_val.py][line: 371][ INFO] Test: [190/216] Time 0.426 (0.469)
[2024-11-25 20:14:59,062][ train_val.py][line: 371][ INFO] Test: [191/216] Time 0.739 (0.470)
[2024-11-25 20:14:59,486][ train_val.py][line: 371][ INFO] Test: [192/216] Time 0.424 (0.470)
[2024-11-25 20:14:59,915][ train_val.py][line: 371][ INFO] Test: [193/216] Time 0.429 (0.470)
[2024-11-25 20:15:00,359][ train_val.py][line: 371][ INFO] Test: [194/216] Time 0.444 (0.470)
[2024-11-25 20:15:00,795][ train_val.py][line: 371][ INFO] Test: [195/216] Time 0.436 (0.470)
[2024-11-25 20:15:01,241][ train_val.py][line: 371][ INFO] Test: [196/216] Time 0.447 (0.469)
[2024-11-25 20:15:01,697][ train_val.py][line: 371][ INFO] Test: [197/216] Time 0.456 (0.469)
[2024-11-25 20:15:03,903][ train_val.py][line: 371][ INFO] Test: [198/216] Time 2.206 (0.478)
[2024-11-25 20:15:04,419][ train_val.py][line: 371][ INFO] Test: [199/216] Time 0.516 (0.478)
[2024-11-25 20:15:04,919][ train_val.py][line: 371][ INFO] Test: [200/216] Time 0.500 (0.478)
[2024-11-25 20:15:05,347][ train_val.py][line: 371][ INFO] Test: [201/216] Time 0.428 (0.478)
[2024-11-25 20:15:05,784][ train_val.py][line: 371][ INFO] Test: [202/216] Time 0.437 (0.478)
[2024-11-25 20:15:06,230][ train_val.py][line: 371][ INFO] Test: [203/216] Time 0.447 (0.478)
[2024-11-25 20:15:06,669][ train_val.py][line: 371][ INFO] Test: [204/216] Time 0.439 (0.478)
[2024-11-25 20:15:07,093][ train_val.py][line: 371][ INFO] Test: [205/216] Time 0.424 (0.477)
[2024-11-25 20:15:07,534][ train_val.py][line: 371][ INFO] Test: [206/216] Time 0.441 (0.477)
[2024-11-25 20:15:08,008][ train_val.py][line: 371][ INFO] Test: [207/216] Time 0.474 (0.477)
[2024-11-25 20:15:08,431][ train_val.py][line: 371][ INFO] Test: [208/216] Time 0.422 (0.477)
[2024-11-25 20:15:08,869][ train_val.py][line: 371][ INFO] Test: [209/216] Time 0.439 (0.477)
[2024-11-25 20:15:09,289][ train_val.py][line: 371][ INFO] Test: [210/216] Time 0.420 (0.476)
[2024-11-25 20:15:09,732][ train_val.py][line: 371][ INFO] Test: [211/216] Time 0.443 (0.476)
[2024-11-25 20:15:10,172][ train_val.py][line: 371][ INFO] Test: [212/216] Time 0.440 (0.476)
[2024-11-25 20:15:10,602][ train_val.py][line: 371][ INFO] Test: [213/216] Time 0.430 (0.476)
[2024-11-25 20:15:11,056][ train_val.py][line: 371][ INFO] Test: [214/216] Time 0.454 (0.476)
[2024-11-25 20:15:11,478][ train_val.py][line: 371][ INFO] Test: [215/216] Time 0.422 (0.476)
[2024-11-25 20:15:12,661][ train_val.py][line: 371][ INFO] Test: [216/216] Time 1.183 (0.479)
[2024-11-25 20:15:12,702][ train_val.py][line: 392][ INFO] Gathering final results ...
[2024-11-25 20:15:12,702][ train_val.py][line: 394][ INFO] * Loss 6.62277 total_num=1725.0
[2024-11-25 20:17:11,090][ eval_helper.py][line: 343][ INFO]
| clsname | max_auc | max_ap | pixel_auc | pixel_ap |
|:----------:|:---------:|:--------:|:-----------:|:----------:|
| bottle | 100 | 100 | 98.7072 | 84.0309 |
| cable | 99.1192 | 99.4682 | 98.2509 | 68.9106 |
| capsule | 93.0195 | 98.2538 | 99.0121 | 55.813 |
| carpet | 99.5987 | 99.8771 | 99.2648 | 75.7944 |
| grid | 98.8304 | 99.6541 | 99.1191 | 52.7451 |
| hazelnut | 99.8571 | 99.9178 | 98.4754 | 69.2104 |
| leather | 100 | 100 | 99.7051 | 76.1053 |
| metal_nut | 99.8045 | 99.9535 | 96.0486 | 71.9331 |
| pill | 97.3813 | 99.5115 | 95.9018 | 48.0041 |
| screw | 95.3679 | 98.3311 | 99.4474 | 51.3659 |
| tile | 99.9639 | 99.986 | 96.0371 | 78.0619 |
| toothbrush | 94.4444 | 97.7702 | 98.9261 | 57.0354 |
| transistor | 99.625 | 99.4247 | 97.5586 | 78.4769 |
| wood | 99.5614 | 99.8646 | 95.4884 | 66.822 |
| zipper | 99.3435 | 99.8239 | 98.0315 | 65.8514 |
| mean | 98.3945 | 99.4558 | 97.9983 | 66.6774 |