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  1. Base-DensePose-RCNN-FPN-Human.yaml +20 -0
  2. Base-DensePose-RCNN-FPN.yaml +60 -0
  3. densepose_rcnn_R_50_FPN_DL_s1x.yaml +12 -0
  4. densepose_rcnn_R_50_FPN_DL_soft_s1x.yaml +12 -0
  5. densepose_rcnn_R_50_FPN_s1x.yaml +12 -0
  6. densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_16k.yaml +133 -0
  7. densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_4k.yaml +133 -0
  8. densepose_rcnn_R_50_FPN_soft_animals_finetune_16k.yaml +119 -0
  9. densepose_rcnn_R_50_FPN_soft_animals_finetune_4k.yaml +119 -0
Base-DensePose-RCNN-FPN-Human.yaml ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ ROI_DENSEPOSE_HEAD:
4
+ CSE:
5
+ EMBEDDERS:
6
+ "smpl_27554":
7
+ TYPE: vertex_feature
8
+ NUM_VERTICES: 27554
9
+ FEATURE_DIM: 256
10
+ FEATURES_TRAINABLE: False
11
+ IS_TRAINABLE: True
12
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_smpl_27554_256.pkl"
13
+ DATASETS:
14
+ TRAIN:
15
+ - "densepose_coco_2014_train_cse"
16
+ - "densepose_coco_2014_valminusminival_cse"
17
+ TEST:
18
+ - "densepose_coco_2014_minival_cse"
19
+ CLASS_TO_MESH_NAME_MAPPING:
20
+ "0": "smpl_27554"
Base-DensePose-RCNN-FPN.yaml ADDED
@@ -0,0 +1,60 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ VERSION: 2
2
+ MODEL:
3
+ META_ARCHITECTURE: "GeneralizedRCNN"
4
+ BACKBONE:
5
+ NAME: "build_resnet_fpn_backbone"
6
+ RESNETS:
7
+ OUT_FEATURES: ["res2", "res3", "res4", "res5"]
8
+ FPN:
9
+ IN_FEATURES: ["res2", "res3", "res4", "res5"]
10
+ ANCHOR_GENERATOR:
11
+ SIZES: [[32], [64], [128], [256], [512]] # One size for each in feature map
12
+ ASPECT_RATIOS: [[0.5, 1.0, 2.0]] # Three aspect ratios (same for all in feature maps)
13
+ RPN:
14
+ IN_FEATURES: ["p2", "p3", "p4", "p5", "p6"]
15
+ PRE_NMS_TOPK_TRAIN: 2000 # Per FPN level
16
+ PRE_NMS_TOPK_TEST: 1000 # Per FPN level
17
+ # Detectron1 uses 2000 proposals per-batch,
18
+ # (See "modeling/rpn/rpn_outputs.py" for details of this legacy issue)
19
+ # which is approximately 1000 proposals per-image since the default batch size for FPN is 2.
20
+ POST_NMS_TOPK_TRAIN: 1000
21
+ POST_NMS_TOPK_TEST: 1000
22
+
23
+ DENSEPOSE_ON: True
24
+ ROI_HEADS:
25
+ NAME: "DensePoseROIHeads"
26
+ IN_FEATURES: ["p2", "p3", "p4", "p5"]
27
+ NUM_CLASSES: 1
28
+ ROI_BOX_HEAD:
29
+ NAME: "FastRCNNConvFCHead"
30
+ NUM_FC: 2
31
+ POOLER_RESOLUTION: 7
32
+ POOLER_SAMPLING_RATIO: 2
33
+ POOLER_TYPE: "ROIAlign"
34
+ ROI_DENSEPOSE_HEAD:
35
+ NAME: "DensePoseV1ConvXHead"
36
+ POOLER_TYPE: "ROIAlign"
37
+ NUM_COARSE_SEGM_CHANNELS: 2
38
+ PREDICTOR_NAME: "DensePoseEmbeddingPredictor"
39
+ LOSS_NAME: "DensePoseCseLoss"
40
+ CSE:
41
+ # embedding loss, possible values:
42
+ # - "EmbeddingLoss"
43
+ # - "SoftEmbeddingLoss"
44
+ EMBED_LOSS_NAME: "EmbeddingLoss"
45
+ SOLVER:
46
+ IMS_PER_BATCH: 16
47
+ BASE_LR: 0.01
48
+ STEPS: (60000, 80000)
49
+ MAX_ITER: 90000
50
+ WARMUP_FACTOR: 0.1
51
+ CLIP_GRADIENTS:
52
+ CLIP_TYPE: norm
53
+ CLIP_VALUE: 1.0
54
+ ENABLED: true
55
+ NORM_TYPE: 2.0
56
+ INPUT:
57
+ MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
58
+ DENSEPOSE_EVALUATION:
59
+ TYPE: cse
60
+ STORAGE: file
densepose_rcnn_R_50_FPN_DL_s1x.yaml ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ CSE:
9
+ EMBED_LOSS_NAME: "EmbeddingLoss"
10
+ SOLVER:
11
+ MAX_ITER: 130000
12
+ STEPS: (100000, 120000)
densepose_rcnn_R_50_FPN_DL_soft_s1x.yaml ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ CSE:
9
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
10
+ SOLVER:
11
+ MAX_ITER: 130000
12
+ STEPS: (100000, 120000)
densepose_rcnn_R_50_FPN_s1x.yaml ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseV1ConvXHead"
8
+ CSE:
9
+ EMBED_LOSS_NAME: "EmbeddingLoss"
10
+ SOLVER:
11
+ MAX_ITER: 130000
12
+ STEPS: (100000, 120000)
densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_16k.yaml ADDED
@@ -0,0 +1,133 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_HEADS:
7
+ NUM_CLASSES: 1
8
+ ROI_DENSEPOSE_HEAD:
9
+ NAME: "DensePoseV1ConvXHead"
10
+ COARSE_SEGM_TRAINED_BY_MASKS: True
11
+ CSE:
12
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
13
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
14
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
15
+ EMBEDDERS:
16
+ "cat_7466":
17
+ TYPE: vertex_feature
18
+ NUM_VERTICES: 7466
19
+ FEATURE_DIM: 256
20
+ FEATURES_TRAINABLE: False
21
+ IS_TRAINABLE: True
22
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
23
+ "dog_7466":
24
+ TYPE: vertex_feature
25
+ NUM_VERTICES: 7466
26
+ FEATURE_DIM: 256
27
+ FEATURES_TRAINABLE: False
28
+ IS_TRAINABLE: True
29
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
30
+ "sheep_5004":
31
+ TYPE: vertex_feature
32
+ NUM_VERTICES: 5004
33
+ FEATURE_DIM: 256
34
+ FEATURES_TRAINABLE: False
35
+ IS_TRAINABLE: True
36
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
37
+ "horse_5004":
38
+ TYPE: vertex_feature
39
+ NUM_VERTICES: 5004
40
+ FEATURE_DIM: 256
41
+ FEATURES_TRAINABLE: False
42
+ IS_TRAINABLE: True
43
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
44
+ "zebra_5002":
45
+ TYPE: vertex_feature
46
+ NUM_VERTICES: 5002
47
+ FEATURE_DIM: 256
48
+ FEATURES_TRAINABLE: False
49
+ IS_TRAINABLE: True
50
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
51
+ "giraffe_5002":
52
+ TYPE: vertex_feature
53
+ NUM_VERTICES: 5002
54
+ FEATURE_DIM: 256
55
+ FEATURES_TRAINABLE: False
56
+ IS_TRAINABLE: True
57
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
58
+ "elephant_5002":
59
+ TYPE: vertex_feature
60
+ NUM_VERTICES: 5002
61
+ FEATURE_DIM: 256
62
+ FEATURES_TRAINABLE: False
63
+ IS_TRAINABLE: True
64
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
65
+ "cow_5002":
66
+ TYPE: vertex_feature
67
+ NUM_VERTICES: 5002
68
+ FEATURE_DIM: 256
69
+ FEATURES_TRAINABLE: False
70
+ IS_TRAINABLE: True
71
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
72
+ "bear_4936":
73
+ TYPE: vertex_feature
74
+ NUM_VERTICES: 4936
75
+ FEATURE_DIM: 256
76
+ FEATURES_TRAINABLE: False
77
+ IS_TRAINABLE: True
78
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
79
+ DATASETS:
80
+ TRAIN:
81
+ - "densepose_lvis_v1_ds2_train_v1"
82
+ TEST:
83
+ - "densepose_lvis_v1_ds2_val_v1"
84
+ WHITELISTED_CATEGORIES:
85
+ "densepose_lvis_v1_ds2_train_v1":
86
+ - 943 # sheep
87
+ - 1202 # zebra
88
+ - 569 # horse
89
+ - 496 # giraffe
90
+ - 422 # elephant
91
+ - 80 # cow
92
+ - 76 # bear
93
+ - 225 # cat
94
+ - 378 # dog
95
+ "densepose_lvis_v1_ds2_val_v1":
96
+ - 943 # sheep
97
+ - 1202 # zebra
98
+ - 569 # horse
99
+ - 496 # giraffe
100
+ - 422 # elephant
101
+ - 80 # cow
102
+ - 76 # bear
103
+ - 225 # cat
104
+ - 378 # dog
105
+ CATEGORY_MAPS:
106
+ "densepose_lvis_v1_ds2_train_v1":
107
+ "1202": 943 # zebra -> sheep
108
+ "569": 943 # horse -> sheep
109
+ "496": 943 # giraffe -> sheep
110
+ "422": 943 # elephant -> sheep
111
+ "80": 943 # cow -> sheep
112
+ "76": 943 # bear -> sheep
113
+ "225": 943 # cat -> sheep
114
+ "378": 943 # dog -> sheep
115
+ "densepose_lvis_v1_ds2_val_v1":
116
+ "1202": 943 # zebra -> sheep
117
+ "569": 943 # horse -> sheep
118
+ "496": 943 # giraffe -> sheep
119
+ "422": 943 # elephant -> sheep
120
+ "80": 943 # cow -> sheep
121
+ "76": 943 # bear -> sheep
122
+ "225": 943 # cat -> sheep
123
+ "378": 943 # dog -> sheep
124
+ CLASS_TO_MESH_NAME_MAPPING:
125
+ # Note: different classes are mapped to a single class
126
+ # mesh is chosen based on GT data, so this is just some
127
+ # value which has no particular meaning
128
+ "0": "sheep_5004"
129
+ SOLVER:
130
+ MAX_ITER: 16000
131
+ STEPS: (12000, 14000)
132
+ DENSEPOSE_EVALUATION:
133
+ EVALUATE_MESH_ALIGNMENT: True
densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_4k.yaml ADDED
@@ -0,0 +1,133 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_HEADS:
7
+ NUM_CLASSES: 1
8
+ ROI_DENSEPOSE_HEAD:
9
+ NAME: "DensePoseV1ConvXHead"
10
+ COARSE_SEGM_TRAINED_BY_MASKS: True
11
+ CSE:
12
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
13
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
14
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
15
+ EMBEDDERS:
16
+ "cat_5001":
17
+ TYPE: vertex_feature
18
+ NUM_VERTICES: 5001
19
+ FEATURE_DIM: 256
20
+ FEATURES_TRAINABLE: False
21
+ IS_TRAINABLE: True
22
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_5001_256.pkl"
23
+ "dog_5002":
24
+ TYPE: vertex_feature
25
+ NUM_VERTICES: 5002
26
+ FEATURE_DIM: 256
27
+ FEATURES_TRAINABLE: False
28
+ IS_TRAINABLE: True
29
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_5002_256.pkl"
30
+ "sheep_5004":
31
+ TYPE: vertex_feature
32
+ NUM_VERTICES: 5004
33
+ FEATURE_DIM: 256
34
+ FEATURES_TRAINABLE: False
35
+ IS_TRAINABLE: True
36
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
37
+ "horse_5004":
38
+ TYPE: vertex_feature
39
+ NUM_VERTICES: 5004
40
+ FEATURE_DIM: 256
41
+ FEATURES_TRAINABLE: False
42
+ IS_TRAINABLE: True
43
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
44
+ "zebra_5002":
45
+ TYPE: vertex_feature
46
+ NUM_VERTICES: 5002
47
+ FEATURE_DIM: 256
48
+ FEATURES_TRAINABLE: False
49
+ IS_TRAINABLE: True
50
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
51
+ "giraffe_5002":
52
+ TYPE: vertex_feature
53
+ NUM_VERTICES: 5002
54
+ FEATURE_DIM: 256
55
+ FEATURES_TRAINABLE: False
56
+ IS_TRAINABLE: True
57
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
58
+ "elephant_5002":
59
+ TYPE: vertex_feature
60
+ NUM_VERTICES: 5002
61
+ FEATURE_DIM: 256
62
+ FEATURES_TRAINABLE: False
63
+ IS_TRAINABLE: True
64
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
65
+ "cow_5002":
66
+ TYPE: vertex_feature
67
+ NUM_VERTICES: 5002
68
+ FEATURE_DIM: 256
69
+ FEATURES_TRAINABLE: False
70
+ IS_TRAINABLE: True
71
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
72
+ "bear_4936":
73
+ TYPE: vertex_feature
74
+ NUM_VERTICES: 4936
75
+ FEATURE_DIM: 256
76
+ FEATURES_TRAINABLE: False
77
+ IS_TRAINABLE: True
78
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
79
+ DATASETS:
80
+ TRAIN:
81
+ - "densepose_lvis_v1_ds1_train_v1"
82
+ TEST:
83
+ - "densepose_lvis_v1_ds1_val_v1"
84
+ WHITELISTED_CATEGORIES:
85
+ "densepose_lvis_v1_ds1_train_v1":
86
+ - 943 # sheep
87
+ - 1202 # zebra
88
+ - 569 # horse
89
+ - 496 # giraffe
90
+ - 422 # elephant
91
+ - 80 # cow
92
+ - 76 # bear
93
+ - 225 # cat
94
+ - 378 # dog
95
+ "densepose_lvis_v1_ds1_val_v1":
96
+ - 943 # sheep
97
+ - 1202 # zebra
98
+ - 569 # horse
99
+ - 496 # giraffe
100
+ - 422 # elephant
101
+ - 80 # cow
102
+ - 76 # bear
103
+ - 225 # cat
104
+ - 378 # dog
105
+ CATEGORY_MAPS:
106
+ "densepose_lvis_v1_ds1_train_v1":
107
+ "1202": 943 # zebra -> sheep
108
+ "569": 943 # horse -> sheep
109
+ "496": 943 # giraffe -> sheep
110
+ "422": 943 # elephant -> sheep
111
+ "80": 943 # cow -> sheep
112
+ "76": 943 # bear -> sheep
113
+ "225": 943 # cat -> sheep
114
+ "378": 943 # dog -> sheep
115
+ "densepose_lvis_v1_ds1_val_v1":
116
+ "1202": 943 # zebra -> sheep
117
+ "569": 943 # horse -> sheep
118
+ "496": 943 # giraffe -> sheep
119
+ "422": 943 # elephant -> sheep
120
+ "80": 943 # cow -> sheep
121
+ "76": 943 # bear -> sheep
122
+ "225": 943 # cat -> sheep
123
+ "378": 943 # dog -> sheep
124
+ CLASS_TO_MESH_NAME_MAPPING:
125
+ # Note: different classes are mapped to a single class
126
+ # mesh is chosen based on GT data, so this is just some
127
+ # value which has no particular meaning
128
+ "0": "sheep_5004"
129
+ SOLVER:
130
+ MAX_ITER: 4000
131
+ STEPS: (3000, 3500)
132
+ DENSEPOSE_EVALUATION:
133
+ EVALUATE_MESH_ALIGNMENT: True
densepose_rcnn_R_50_FPN_soft_animals_finetune_16k.yaml ADDED
@@ -0,0 +1,119 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_HEADS:
7
+ NUM_CLASSES: 9
8
+ ROI_DENSEPOSE_HEAD:
9
+ NAME: "DensePoseV1ConvXHead"
10
+ COARSE_SEGM_TRAINED_BY_MASKS: True
11
+ CSE:
12
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
13
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
14
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
15
+ EMBEDDERS:
16
+ "cat_7466":
17
+ TYPE: vertex_feature
18
+ NUM_VERTICES: 7466
19
+ FEATURE_DIM: 256
20
+ FEATURES_TRAINABLE: False
21
+ IS_TRAINABLE: True
22
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
23
+ "dog_7466":
24
+ TYPE: vertex_feature
25
+ NUM_VERTICES: 7466
26
+ FEATURE_DIM: 256
27
+ FEATURES_TRAINABLE: False
28
+ IS_TRAINABLE: True
29
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
30
+ "sheep_5004":
31
+ TYPE: vertex_feature
32
+ NUM_VERTICES: 5004
33
+ FEATURE_DIM: 256
34
+ FEATURES_TRAINABLE: False
35
+ IS_TRAINABLE: True
36
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
37
+ "horse_5004":
38
+ TYPE: vertex_feature
39
+ NUM_VERTICES: 5004
40
+ FEATURE_DIM: 256
41
+ FEATURES_TRAINABLE: False
42
+ IS_TRAINABLE: True
43
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
44
+ "zebra_5002":
45
+ TYPE: vertex_feature
46
+ NUM_VERTICES: 5002
47
+ FEATURE_DIM: 256
48
+ FEATURES_TRAINABLE: False
49
+ IS_TRAINABLE: True
50
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
51
+ "giraffe_5002":
52
+ TYPE: vertex_feature
53
+ NUM_VERTICES: 5002
54
+ FEATURE_DIM: 256
55
+ FEATURES_TRAINABLE: False
56
+ IS_TRAINABLE: True
57
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
58
+ "elephant_5002":
59
+ TYPE: vertex_feature
60
+ NUM_VERTICES: 5002
61
+ FEATURE_DIM: 256
62
+ FEATURES_TRAINABLE: False
63
+ IS_TRAINABLE: True
64
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
65
+ "cow_5002":
66
+ TYPE: vertex_feature
67
+ NUM_VERTICES: 5002
68
+ FEATURE_DIM: 256
69
+ FEATURES_TRAINABLE: False
70
+ IS_TRAINABLE: True
71
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
72
+ "bear_4936":
73
+ TYPE: vertex_feature
74
+ NUM_VERTICES: 4936
75
+ FEATURE_DIM: 256
76
+ FEATURES_TRAINABLE: False
77
+ IS_TRAINABLE: True
78
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
79
+ DATASETS:
80
+ TRAIN:
81
+ - "densepose_lvis_v1_ds2_train_v1"
82
+ TEST:
83
+ - "densepose_lvis_v1_ds2_val_v1"
84
+ WHITELISTED_CATEGORIES:
85
+ "densepose_lvis_v1_ds2_train_v1":
86
+ - 943 # sheep
87
+ - 1202 # zebra
88
+ - 569 # horse
89
+ - 496 # giraffe
90
+ - 422 # elephant
91
+ - 80 # cow
92
+ - 76 # bear
93
+ - 225 # cat
94
+ - 378 # dog
95
+ "densepose_lvis_v1_ds2_val_v1":
96
+ - 943 # sheep
97
+ - 1202 # zebra
98
+ - 569 # horse
99
+ - 496 # giraffe
100
+ - 422 # elephant
101
+ - 80 # cow
102
+ - 76 # bear
103
+ - 225 # cat
104
+ - 378 # dog
105
+ CLASS_TO_MESH_NAME_MAPPING:
106
+ "0": "bear_4936"
107
+ "1": "cow_5002"
108
+ "2": "cat_7466"
109
+ "3": "dog_7466"
110
+ "4": "elephant_5002"
111
+ "5": "giraffe_5002"
112
+ "6": "horse_5004"
113
+ "7": "sheep_5004"
114
+ "8": "zebra_5002"
115
+ SOLVER:
116
+ MAX_ITER: 16000
117
+ STEPS: (12000, 14000)
118
+ DENSEPOSE_EVALUATION:
119
+ EVALUATE_MESH_ALIGNMENT: True
densepose_rcnn_R_50_FPN_soft_animals_finetune_4k.yaml ADDED
@@ -0,0 +1,119 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_HEADS:
7
+ NUM_CLASSES: 9
8
+ ROI_DENSEPOSE_HEAD:
9
+ NAME: "DensePoseV1ConvXHead"
10
+ COARSE_SEGM_TRAINED_BY_MASKS: True
11
+ CSE:
12
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
13
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
14
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
15
+ EMBEDDERS:
16
+ "cat_5001":
17
+ TYPE: vertex_feature
18
+ NUM_VERTICES: 5001
19
+ FEATURE_DIM: 256
20
+ FEATURES_TRAINABLE: False
21
+ IS_TRAINABLE: True
22
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_5001_256.pkl"
23
+ "dog_5002":
24
+ TYPE: vertex_feature
25
+ NUM_VERTICES: 5002
26
+ FEATURE_DIM: 256
27
+ FEATURES_TRAINABLE: False
28
+ IS_TRAINABLE: True
29
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_5002_256.pkl"
30
+ "sheep_5004":
31
+ TYPE: vertex_feature
32
+ NUM_VERTICES: 5004
33
+ FEATURE_DIM: 256
34
+ FEATURES_TRAINABLE: False
35
+ IS_TRAINABLE: True
36
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
37
+ "horse_5004":
38
+ TYPE: vertex_feature
39
+ NUM_VERTICES: 5004
40
+ FEATURE_DIM: 256
41
+ FEATURES_TRAINABLE: False
42
+ IS_TRAINABLE: True
43
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
44
+ "zebra_5002":
45
+ TYPE: vertex_feature
46
+ NUM_VERTICES: 5002
47
+ FEATURE_DIM: 256
48
+ FEATURES_TRAINABLE: False
49
+ IS_TRAINABLE: True
50
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
51
+ "giraffe_5002":
52
+ TYPE: vertex_feature
53
+ NUM_VERTICES: 5002
54
+ FEATURE_DIM: 256
55
+ FEATURES_TRAINABLE: False
56
+ IS_TRAINABLE: True
57
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
58
+ "elephant_5002":
59
+ TYPE: vertex_feature
60
+ NUM_VERTICES: 5002
61
+ FEATURE_DIM: 256
62
+ FEATURES_TRAINABLE: False
63
+ IS_TRAINABLE: True
64
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
65
+ "cow_5002":
66
+ TYPE: vertex_feature
67
+ NUM_VERTICES: 5002
68
+ FEATURE_DIM: 256
69
+ FEATURES_TRAINABLE: False
70
+ IS_TRAINABLE: True
71
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
72
+ "bear_4936":
73
+ TYPE: vertex_feature
74
+ NUM_VERTICES: 4936
75
+ FEATURE_DIM: 256
76
+ FEATURES_TRAINABLE: False
77
+ IS_TRAINABLE: True
78
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
79
+ DATASETS:
80
+ TRAIN:
81
+ - "densepose_lvis_v1_ds1_train_v1"
82
+ TEST:
83
+ - "densepose_lvis_v1_ds1_val_v1"
84
+ WHITELISTED_CATEGORIES:
85
+ "densepose_lvis_v1_ds1_train_v1":
86
+ - 943 # sheep
87
+ - 1202 # zebra
88
+ - 569 # horse
89
+ - 496 # giraffe
90
+ - 422 # elephant
91
+ - 80 # cow
92
+ - 76 # bear
93
+ - 225 # cat
94
+ - 378 # dog
95
+ "densepose_lvis_v1_ds1_val_v1":
96
+ - 943 # sheep
97
+ - 1202 # zebra
98
+ - 569 # horse
99
+ - 496 # giraffe
100
+ - 422 # elephant
101
+ - 80 # cow
102
+ - 76 # bear
103
+ - 225 # cat
104
+ - 378 # dog
105
+ CLASS_TO_MESH_NAME_MAPPING:
106
+ "0": "bear_4936"
107
+ "1": "cow_5002"
108
+ "2": "cat_5001"
109
+ "3": "dog_5002"
110
+ "4": "elephant_5002"
111
+ "5": "giraffe_5002"
112
+ "6": "horse_5004"
113
+ "7": "sheep_5004"
114
+ "8": "zebra_5002"
115
+ SOLVER:
116
+ MAX_ITER: 4000
117
+ STEPS: (3000, 3500)
118
+ DENSEPOSE_EVALUATION:
119
+ EVALUATE_MESH_ALIGNMENT: True