-
Notifications
You must be signed in to change notification settings - Fork 557
/
d_adapt.sh
141 lines (125 loc) · 8.8 KB
/
d_adapt.sh
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
# ResNet101 Based Faster RCNN: Faster RCNN: VOC->Clipart
# 44.8
pretrained_models=../logs/source_only/faster_rcnn_R_101_C4/voc2clipart/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py \
--config-file config/faster_rcnn_R_101_C4_voc.yaml \
-s VOC2007 ../datasets/VOC2007 VOC2012 ../datasets/VOC2012 \
-t Clipart ../datasets/clipart --test Clipart ../datasets/clipart \
--finetune --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/voc2clipart/phase1 MODEL.WEIGHTS ${pretrained_models} SEED 0
# 47.9
pretrained_models=logs/faster_rcnn_R_101_C4/voc2clipart/phase1/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --confidence-ratio-c 0.1 \
--config-file config/faster_rcnn_R_101_C4_voc.yaml \
-s VOC2007 ../datasets/VOC2007 VOC2012 ../datasets/VOC2012 \
-t Clipart ../datasets/clipart --test Clipart ../datasets/clipart \
--finetune --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/voc2clipart/phase2 MODEL.WEIGHTS ${pretrained_models} SEED 0
# 49.0
pretrained_models=logs/faster_rcnn_R_101_C4/voc2clipart/phase2/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --confidence-ratio-c 0.2 \
--config-file config/faster_rcnn_R_101_C4_voc.yaml \
-s VOC2007 ../datasets/VOC2007 VOC2012 ../datasets/VOC2012 \
-t Clipart ../datasets/clipart --test Clipart ../datasets/clipart \
--finetune --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/voc2clipart/phase3 MODEL.WEIGHTS ${pretrained_models} SEED 0
# ResNet101 Based Faster RCNN: Faster RCNN: VOC->WaterColor
# 54.1
pretrained_models=../logs/source_only/faster_rcnn_R_101_C4/voc2watercolor_comic/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py \
--config-file config/faster_rcnn_R_101_C4_voc.yaml \
-s VOC2007Partial ../datasets/VOC2007 VOC2012Partial ../datasets/VOC2012 \
-t WaterColor ../datasets/watercolor --test WaterColorTest ../datasets/watercolor --finetune --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/voc2watercolor/phase1 MODEL.ROI_HEADS.NUM_CLASSES 6 MODEL.WEIGHTS ${pretrained_models} SEED 0
# 57.5
pretrained_models=logs/faster_rcnn_R_101_C4/voc2watercolor/phase1/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --confidence-ratio-c 0.1 \
--config-file config/faster_rcnn_R_101_C4_voc.yaml \
-s VOC2007Partial ../datasets/VOC2007 VOC2012Partial ../datasets/VOC2012 \
-t WaterColor ../datasets/watercolor --test WaterColorTest ../datasets/watercolor --finetune --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/voc2watercolor/phase2 MODEL.ROI_HEADS.NUM_CLASSES 6 MODEL.WEIGHTS ${pretrained_models} SEED 0
# ResNet101 Based Faster RCNN: Faster RCNN: VOC->Comic
# 39.7
pretrained_models=../logs/source_only/faster_rcnn_R_101_C4/voc2watercolor_comic/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py \
--config-file config/faster_rcnn_R_101_C4_voc.yaml \
-s VOC2007Partial ../datasets/VOC2007 VOC2012Partial ../datasets/VOC2012 \
-t Comic ../datasets/comic --test ComicTest ../datasets/comic --finetune --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/voc2comic/phase1 MODEL.ROI_HEADS.NUM_CLASSES 6 MODEL.WEIGHTS ${pretrained_models} SEED 0
# 41.0
pretrained_models=logs/faster_rcnn_R_101_C4/voc2comic/phase1/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --confidence-ratio-c 0.1 \
--config-file config/faster_rcnn_R_101_C4_voc.yaml \
-s VOC2007Partial ../datasets/VOC2007 VOC2012Partial ../datasets/VOC2012 \
-t Comic ../datasets/comic --test ComicTest ../datasets/comic --finetune --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/voc2comic/phase2 MODEL.ROI_HEADS.NUM_CLASSES 6 MODEL.WEIGHTS ${pretrained_models} SEED 0
# ResNet101 Based Faster RCNN: Cityscapes -> Foggy Cityscapes
# 40.1
pretrained_models=../logs/source_only/faster_rcnn_R_101_C4/cityscapes2foggy/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --workers-c 4 --max-train-c 20 --ignored-scores-c 0.05 0.5 \
--config-file config/faster_rcnn_R_101_C4_cityscapes.yaml \
-s Cityscapes ../datasets/cityscapes_in_voc -t FoggyCityscapes ../datasets/foggy_cityscapes_in_voc/ \
--test FoggyCityscapesTest ../datasets/foggy_cityscapes_in_voc/ --finetune --trade-off 0.5 --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/cityscapes2foggy/phase1 MODEL.WEIGHTS ${pretrained_models} SEED 0
# 42.4
pretrained_models=logs/faster_rcnn_R_101_C4/cityscapes2foggy/phase1/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --workers-c 4 --max-train-c 20 --ignored-scores-c 0.05 0.5 --confidence-ratio-c 0.1 \
--config-file config/faster_rcnn_R_101_C4_cityscapes.yaml \
-s Cityscapes ../datasets/cityscapes_in_voc -t FoggyCityscapes ../datasets/foggy_cityscapes_in_voc/ \
--test FoggyCityscapesTest ../datasets/foggy_cityscapes_in_voc/ --finetune --trade-off 0.5 --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/cityscapes2foggy/phase2 MODEL.WEIGHTS ${pretrained_models} SEED 0
# VGG Based Faster RCNN: Cityscapes -> Foggy Cityscapes
# 33.3
pretrained_models=../logs/source_only/faster_rcnn_vgg_16/cityscapes2foggy/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --workers-c 4 --max-train-c 20 --ignored-scores-c 0.05 0.5 \
--config-file config/faster_rcnn_vgg_16_cityscapes.yaml \
-s Cityscapes ../datasets/cityscapes_in_voc -t FoggyCityscapes ../datasets/foggy_cityscapes_in_voc/ \
--test FoggyCityscapesTest ../datasets/foggy_cityscapes_in_voc/ --finetune --trade-off 0.5 --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_vgg_16/cityscapes2foggy/phase1 MODEL.WEIGHTS ${pretrained_models} SEED 0
# 37.0
pretrained_models=logs/faster_rcnn_vgg_16/cityscapes2foggy/phase1/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --workers-c 4 --max-train-c 20 --ignored-scores-c 0.05 0.5 --confidence-ratio-c 0.1 \
--config-file config/faster_rcnn_vgg_16_cityscapes.yaml \
-s Cityscapes ../datasets/cityscapes_in_voc -t FoggyCityscapes ../datasets/foggy_cityscapes_in_voc/ \
--test FoggyCityscapesTest ../datasets/foggy_cityscapes_in_voc/ --finetune --trade-off 0.5 --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_vgg_16/cityscapes2foggy/phase2 MODEL.WEIGHTS ${pretrained_models} SEED 0
# 38.9
pretrained_models=logs/faster_rcnn_vgg_16/cityscapes2foggy/phase2/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --workers-c 4 --max-train-c 20 --ignored-scores-c 0.05 0.5 --confidence-ratio-c 0.2 \
--config-file config/faster_rcnn_vgg_16_cityscapes.yaml \
-s Cityscapes ../datasets/cityscapes_in_voc -t FoggyCityscapes ../datasets/foggy_cityscapes_in_voc/ \
--test FoggyCityscapesTest ../datasets/foggy_cityscapes_in_voc/ --finetune --trade-off 0.5 --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_vgg_16/cityscapes2foggy/phase3 MODEL.WEIGHTS ${pretrained_models} SEED 0
# ResNet101 Based Faster RCNN: Sim10k -> Cityscapes Car
# 51.9
pretrained_models=../logs/source_only/faster_rcnn_R_101_C4/sim10k2cityscapes_car/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --workers-c 8 --ignored-scores-c 0.05 0.5 --bottleneck-dim-c 256 --bottleneck-dim-b 256 \
--config-file config/faster_rcnn_R_101_C4_cityscapes.yaml \
-s Sim10kCar ../datasets/sim10k -t CityscapesCar ../datasets/cityscapes_in_voc/ \
--test CityscapesCarTest ../datasets/cityscapes_in_voc/ --finetune --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_R_101_C4/sim10k2cityscapes_car/phase1 MODEL.ROI_HEADS.NUM_CLASSES 1 MODEL.WEIGHTS ${pretrained_models} SEED 0
# VGG Based Faster RCNN: Sim10k -> Cityscapes Car
# 49.3
pretrained_models=../logs/source_only/faster_rcnn_vgg_16/sim10k2cityscapes_car/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --workers-c 8 --ignored-scores-c 0.05 0.5 --bottleneck-dim-c 256 --bottleneck-dim-b 256 \
--config-file config/faster_rcnn_vgg_16_cityscapes.yaml \
-s Sim10kCar ../datasets/sim10k -t CityscapesCar ../datasets/cityscapes_in_voc/ \
--test CityscapesCarTest ../datasets/cityscapes_in_voc/ --finetune --trade-off 0.5 --bbox-refine \
OUTPUT_DIR logs/faster_rcnn_vgg_16/sim10k2cityscapes_car/phase1 MODEL.ROI_HEADS.NUM_CLASSES 1 MODEL.WEIGHTS ${pretrained_models} SEED 0
# RetinaNet: VOC->Clipart
# 44.7
pretrained_models=../logs/source_only/retinanet_R_101_FPN/voc2clipart/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --remove-bg \
--config-file config/retinanet_R_101_FPN_voc.yaml \
-s VOC2007 ../datasets/VOC2007 VOC2012 ../datasets/VOC2012 \
-t Clipart ../datasets/clipart --test Clipart ../datasets/clipart \
--finetune --bbox-refine \
OUTPUT_DIR logs/retinanet_R_101_FPN/voc2clipart/phase1 MODEL.WEIGHTS ${pretrained_models} SEED 0
# 46.3
pretrained_models=logs/retinanet_R_101_FPN/voc2clipart/phase1/model_final.pth
CUDA_VISIBLE_DEVICES=0 python d_adapt.py --remove-bg --confidence-ratio 0.1 \
--config-file config/retinanet_R_101_FPN_voc.yaml \
-s VOC2007 ../datasets/VOC2007 VOC2012 ../datasets/VOC2012 \
-t Clipart ../datasets/clipart --test Clipart ../datasets/clipart \
--finetune --bbox-refine \
OUTPUT_DIR logs/retinanet_R_101_FPN/voc2clipart/phase2 MODEL.WEIGHTS ${pretrained_models} SEED 0