-
Notifications
You must be signed in to change notification settings - Fork 41
/
Copy pathcascade_rcnn_voc.txt
103 lines (103 loc) · 10.2 KB
/
cascade_rcnn_voc.txt
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
[INFO] 2020-12-20 14:13:35 ==================Configs==================
[INFO] 2020-12-20 14:13:35 MODEL:
[INFO] 2020-12-20 14:13:35 NAME: Cascade_RCNN
[INFO] 2020-12-20 14:13:35 BACKBONE: resnet50
[INFO] 2020-12-20 14:13:35
[INFO] 2020-12-20 14:13:35 DATA:
[INFO] 2020-12-20 14:13:35 DATASET: voc
[INFO] 2020-12-20 14:13:35 TRANSFORM: frcnn
[INFO] 2020-12-20 14:13:35 SCALE: [800, 1333]
[INFO] 2020-12-20 14:13:35 OPTIMIZE:
[INFO] 2020-12-20 14:13:35 OPTIMIZER: sgd
[INFO] 2020-12-20 14:13:35 BASE_LR: 0.016
[INFO] 2020-12-20 14:13:35 SCHEDULER: 1x
[INFO] 2020-12-20 14:13:35 BATCH_SIZE: 2
[INFO] 2020-12-20 14:13:35 TEST:
[INFO] 2020-12-20 14:13:35 NMS_THRESH : 0.5
[INFO] 2020-12-20 14:13:35 CONF_THRESH: 0.05
[INFO] 2020-12-20 14:13:35 MISC:
[INFO] 2020-12-20 14:13:35 VAL_FREQ: 1
[INFO] 2020-12-20 14:13:35 SAVE_FREQ: 1
[INFO] 2020-12-20 14:13:35 NUM_WORKERS: 2
[INFO] 2020-12-20 14:13:35 ==================Options==================
[INFO] 2020-12-20 14:13:35 config=work_config/cascade_rcnn_voc_dist.yml
[INFO] 2020-12-20 14:13:35 debug=False
[INFO] 2020-12-20 14:13:35 device=cuda:0
[INFO] 2020-12-20 14:13:35 gpu_id=0
[INFO] 2020-12-20 14:13:35 load=None
[INFO] 2020-12-20 14:13:35 local_rank=0
[INFO] 2020-12-20 14:13:35 no_val=False
[INFO] 2020-12-20 14:13:35 resume=False
[INFO] 2020-12-20 14:13:35 save_path=None
[INFO] 2020-12-20 14:13:35 tag=cascade_rcnn_voc_dist
[INFO] 2020-12-20 14:13:35 vis=False
[INFO] 2020-12-20 14:13:35 ===========================================
[INFO] 2020-12-20 14:13:42 train_trasforms: Compose([
OneOf([
HueSaturationValue(always_apply=False, p=0.95, hue_shift_limit=(-0.3, 0.3), sat_shift_limit=(-0.3, 0.3), val_shift_limit=(-0.3, 0.3)),
RandomBrightnessContrast(always_apply=False, p=0.95, brightness_limit=(-0.3, 0.3), contrast_limit=(-0.3, 0.3), brightness_by_max=True),
], p=1.0),
ToGray(always_apply=False, p=0.01),
HorizontalFlip(always_apply=False, p=0.5),
ToTensorV2(always_apply=True, p=1.0, transpose_mask=False),
], p=1.0, bbox_params={'format': 'pascal_voc', 'label_fields': ['labels'], 'min_area': 0, 'min_visibility': 0, 'check_each_transform': True}, keypoint_params=None, additional_targets={})
[INFO] 2020-12-20 14:13:42 ===========================================
[INFO] 2020-12-20 14:13:42 val_trasforms: Compose([
ToTensorV2(always_apply=True, p=1.0, transpose_mask=False),
], p=1.0, bbox_params={'format': 'pascal_voc', 'label_fields': ['labels'], 'min_area': 0, 'min_visibility': 0, 'check_each_transform': True}, keypoint_params=None, additional_targets={})
[INFO] 2020-12-20 14:13:42 ===========================================
[INFO] 2020-12-20 14:13:42 scheduler: (Lambda scheduler)
{'epochs': [8, 11, 13], 'ratios': [1, 0.1, 0.01]}
[INFO] 2020-12-20 14:13:42 ===========================================
[INFO] 2020-12-20 14:20:20 Train epoch: 1, lr: 0.016000, (loss) loss: 0.5812 |
[INFO] 2020-12-20 14:24:28 Eva(val) epoch 1, IoU: 0.5, APs: [ 0.56697 0.56754 0.57068 0.31707 0.46456 0.59547 0.7903 0.67342 0.37387 0.42979], mAP: 0.5068394240291385
[INFO] 2020-12-20 14:24:33 Eva(val) epoch 1, IoU: 0.75, APs: [ 0.25964 0.24755 0.17655 0.046121 0.12975 0.47317 0.54004 0.33451 0.088598 0.26358], mAP: 0.22643006079428218
[INFO] 2020-12-20 14:24:37 Eva(val) epoch 1, mean of (AP50-AP95): 0.2551193151209014
[INFO] 2020-12-20 14:30:39 Train epoch: 2, lr: 0.016000, (loss) loss: 0.6237 |
[INFO] 2020-12-20 14:34:47 Eva(val) epoch 2, IoU: 0.5, APs: [ 0.61203 0.77226 0.61406 0.44791 0.53355 0.7032 0.83855 0.758 0.47507 0.5951], mAP: 0.6378925934287268
[INFO] 2020-12-20 14:34:51 Eva(val) epoch 2, IoU: 0.75, APs: [ 0.38417 0.44927 0.34975 0.17086 0.32909 0.53522 0.62782 0.45461 0.20673 0.41167], mAP: 0.37682115355603074
[INFO] 2020-12-20 14:34:55 Eva(val) epoch 2, mean of (AP50-AP95): 0.365688466672441
[INFO] 2020-12-20 14:40:33 Train epoch: 3, lr: 0.016000, (loss) loss: 0.5958 |
[INFO] 2020-12-20 14:44:52 Eva(val) epoch 3, IoU: 0.5, APs: [ 0.80109 0.80442 0.66754 0.55034 0.66577 0.81531 0.86708 0.82569 0.43176 0.59235], mAP: 0.6967119710020826
[INFO] 2020-12-20 14:44:56 Eva(val) epoch 3, IoU: 0.75, APs: [ 0.53677 0.54776 0.36607 0.18818 0.35941 0.66007 0.65217 0.56789 0.22556 0.34028], mAP: 0.4302514468341293
[INFO] 2020-12-20 14:44:59 Eva(val) epoch 3, mean of (AP50-AP95): 0.4156075066259125
[INFO] 2020-12-20 14:50:38 Train epoch: 4, lr: 0.016000, (loss) loss: 0.5160 |
[INFO] 2020-12-20 14:54:49 Eva(val) epoch 4, IoU: 0.5, APs: [ 0.8321 0.77912 0.7761 0.53685 0.64652 0.78757 0.86434 0.83983 0.52081 0.56351], mAP: 0.7138759487706283
[INFO] 2020-12-20 14:54:53 Eva(val) epoch 4, IoU: 0.75, APs: [ 0.60179 0.3912 0.42738 0.27534 0.35675 0.70711 0.68814 0.62726 0.25814 0.37354], mAP: 0.45019020552634226
[INFO] 2020-12-20 14:54:57 Eva(val) epoch 4, mean of (AP50-AP95): 0.42828300505163314
[INFO] 2020-12-20 15:00:34 Train epoch: 5, lr: 0.016000, (loss) loss: 0.4884 |
[INFO] 2020-12-20 15:04:49 Eva(val) epoch 5, IoU: 0.5, APs: [ 0.83088 0.81936 0.76458 0.59385 0.67318 0.84183 0.87011 0.85826 0.55931 0.72397], mAP: 0.7401051708694814
[INFO] 2020-12-20 15:04:54 Eva(val) epoch 5, IoU: 0.75, APs: [ 0.54939 0.60887 0.4846 0.28524 0.39958 0.70705 0.67598 0.6384 0.27556 0.51166], mAP: 0.4848815453991412
[INFO] 2020-12-20 15:04:57 Eva(val) epoch 5, mean of (AP50-AP95): 0.45534004089405944
[INFO] 2020-12-20 15:10:38 Train epoch: 6, lr: 0.016000, (loss) loss: 0.4683 |
[INFO] 2020-12-20 15:14:50 Eva(val) epoch 6, IoU: 0.5, APs: [ 0.77685 0.8269 0.76957 0.62062 0.66628 0.83859 0.88247 0.84898 0.51713 0.71026], mAP: 0.7451036164180584
[INFO] 2020-12-20 15:14:55 Eva(val) epoch 6, IoU: 0.75, APs: [ 0.60374 0.57454 0.435 0.30252 0.44319 0.74185 0.7196 0.63031 0.26159 0.50116], mAP: 0.5050815360366002
[INFO] 2020-12-20 15:14:58 Eva(val) epoch 6, mean of (AP50-AP95): 0.47178826200533186
[INFO] 2020-12-20 15:20:40 Train epoch: 7, lr: 0.016000, (loss) loss: 0.3932 |
[INFO] 2020-12-20 15:24:48 Eva(val) epoch 7, IoU: 0.5, APs: [ 0.86672 0.8359 0.75993 0.65503 0.69283 0.80565 0.87799 0.88929 0.53872 0.61333], mAP: 0.745538747052736
[INFO] 2020-12-20 15:24:53 Eva(val) epoch 7, IoU: 0.75, APs: [ 0.67855 0.61584 0.48611 0.32541 0.48011 0.65936 0.70243 0.6341 0.32112 0.40174], mAP: 0.5043629277645936
[INFO] 2020-12-20 15:24:57 Eva(val) epoch 7, mean of (AP50-AP95): 0.4710846743047569
[INFO] 2020-12-20 15:30:34 Train epoch: 8, lr: 0.016000, (loss) loss: 0.5190 |
[INFO] 2020-12-20 15:34:44 Eva(val) epoch 8, IoU: 0.5, APs: [ 0.85846 0.84116 0.75554 0.60838 0.66344 0.85863 0.88943 0.85549 0.53989 0.78489], mAP: 0.7562900568417447
[INFO] 2020-12-20 15:34:49 Eva(val) epoch 8, IoU: 0.75, APs: [ 0.65563 0.59688 0.4837 0.30407 0.46717 0.74837 0.72742 0.64975 0.29964 0.61438], mAP: 0.5243910381928651
[INFO] 2020-12-20 15:34:52 Eva(val) epoch 8, mean of (AP50-AP95): 0.4834530426485932
[INFO] 2020-12-20 15:40:29 Train epoch: 9, lr: 0.001600, (loss) loss: 0.3707 |
[INFO] 2020-12-20 15:44:41 Eva(val) epoch 9, IoU: 0.5, APs: [ 0.89737 0.88586 0.8461 0.71131 0.7453 0.89916 0.92037 0.91275 0.61294 0.83368], mAP: 0.8154165044491302
[INFO] 2020-12-20 15:44:45 Eva(val) epoch 9, IoU: 0.75, APs: [ 0.71351 0.69241 0.57194 0.42616 0.53512 0.80267 0.78137 0.75438 0.38088 0.61884], mAP: 0.6087679965786903
[INFO] 2020-12-20 15:44:48 Eva(val) epoch 9, mean of (AP50-AP95): 0.5531757632898494
[INFO] 2020-12-20 15:50:24 Train epoch: 10, lr: 0.001600, (loss) loss: 0.4365 |
[INFO] 2020-12-20 15:54:34 Eva(val) epoch 10, IoU: 0.5, APs: [ 0.89377 0.8781 0.85242 0.70307 0.74476 0.89096 0.91886 0.92315 0.60902 0.83313], mAP: 0.8147662644079796
[INFO] 2020-12-20 15:54:38 Eva(val) epoch 10, IoU: 0.75, APs: [ 0.75602 0.69129 0.59686 0.4385 0.5359 0.80804 0.77606 0.73614 0.38383 0.65218], mAP: 0.6171464113550154
[INFO] 2020-12-20 15:54:41 Eva(val) epoch 10, mean of (AP50-AP95): 0.5578245588041277
[INFO] 2020-12-20 16:00:18 Train epoch: 11, lr: 0.001600, (loss) loss: 0.3325 |
[INFO] 2020-12-20 16:04:28 Eva(val) epoch 11, IoU: 0.5, APs: [ 0.89666 0.88861 0.8433 0.72572 0.72285 0.89597 0.916 0.92127 0.60614 0.8382], mAP: 0.8154680490172899
[INFO] 2020-12-20 16:04:32 Eva(val) epoch 11, IoU: 0.75, APs: [ 0.74307 0.68582 0.58604 0.46758 0.53005 0.78963 0.77809 0.76378 0.38044 0.63268], mAP: 0.617129541554802
[INFO] 2020-12-20 16:04:35 Eva(val) epoch 11, mean of (AP50-AP95): 0.5574707240161455
[INFO] 2020-12-20 16:10:10 Train epoch: 12, lr: 0.000160, (loss) loss: 0.3284 |
[INFO] 2020-12-20 16:14:20 Eva(val) epoch 12, IoU: 0.5, APs: [ 0.90114 0.8892 0.84577 0.71855 0.73418 0.90343 0.91908 0.92771 0.60889 0.84563], mAP: 0.8176173116625387
[INFO] 2020-12-20 16:14:24 Eva(val) epoch 12, IoU: 0.75, APs: [ 0.73123 0.69676 0.58785 0.44224 0.53395 0.80226 0.77561 0.7835 0.37214 0.64338], mAP: 0.6207939883561446
[INFO] 2020-12-20 16:14:27 Eva(val) epoch 12, mean of (AP50-AP95): 0.5619778817631519
[INFO] 2020-12-20 16:20:01 Train epoch: 13, lr: 0.000160, (loss) loss: 0.4349 |
[INFO] 2020-12-20 16:24:11 Eva(val) epoch 13, IoU: 0.5, APs: [ 0.89852 0.88686 0.84302 0.72996 0.73693 0.90875 0.91747 0.92181 0.61025 0.8514], mAP: 0.8189825318699819
[INFO] 2020-12-20 16:24:14 Eva(val) epoch 13, IoU: 0.75, APs: [ 0.74788 0.69126 0.58032 0.46332 0.5284 0.8087 0.78421 0.77453 0.3715 0.64563], mAP: 0.622840968884203
[INFO] 2020-12-20 16:24:18 Eva(val) epoch 13, mean of (AP50-AP95): 0.5626005588114829