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  1. assets/teaser.png +3 -0
  2. assets/teaser2.png +3 -0
  3. ckpt/densepose/model_final_162be9.pkl +3 -0
  4. ckpt/humanparsing/parsing_atr.onnx +3 -0
  5. ckpt/humanparsing/parsing_lip.onnx +3 -0
  6. ckpt/image_encoder/config.json +3 -0
  7. ckpt/image_encoder/model.safetensors +3 -0
  8. ckpt/ip_adapter/ip-adapter-plus_sdxl_vit-h.bin +3 -0
  9. ckpt/openpose/.DS_Store +0 -0
  10. ckpt/openpose/ckpts/body_pose_model.pth +3 -0
  11. configs/Base-DensePose-RCNN-FPN.yaml +48 -0
  12. configs/HRNet/densepose_rcnn_HRFPN_HRNet_w32_s1x.yaml +16 -0
  13. configs/HRNet/densepose_rcnn_HRFPN_HRNet_w40_s1x.yaml +23 -0
  14. configs/HRNet/densepose_rcnn_HRFPN_HRNet_w48_s1x.yaml +23 -0
  15. configs/cse/Base-DensePose-RCNN-FPN-Human.yaml +20 -0
  16. configs/cse/Base-DensePose-RCNN-FPN.yaml +60 -0
  17. configs/cse/densepose_rcnn_R_101_FPN_DL_s1x.yaml +12 -0
  18. configs/cse/densepose_rcnn_R_101_FPN_DL_soft_s1x.yaml +12 -0
  19. configs/cse/densepose_rcnn_R_101_FPN_s1x.yaml +12 -0
  20. configs/cse/densepose_rcnn_R_101_FPN_soft_s1x.yaml +12 -0
  21. configs/cse/densepose_rcnn_R_50_FPN_DL_s1x.yaml +12 -0
  22. configs/cse/densepose_rcnn_R_50_FPN_DL_soft_s1x.yaml +12 -0
  23. configs/cse/densepose_rcnn_R_50_FPN_s1x.yaml +12 -0
  24. configs/cse/densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_16k.yaml +133 -0
  25. configs/cse/densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_4k.yaml +133 -0
  26. configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_16k.yaml +119 -0
  27. configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_i2m_16k.yaml +121 -0
  28. configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_m2m_16k.yaml +138 -0
  29. configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_16k.yaml +119 -0
  30. configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_4k.yaml +119 -0
  31. configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k.yaml +118 -0
  32. configs/cse/densepose_rcnn_R_50_FPN_soft_chimps_finetune_4k.yaml +29 -0
  33. configs/cse/densepose_rcnn_R_50_FPN_soft_s1x.yaml +12 -0
  34. configs/densepose_rcnn_R_101_FPN_DL_WC1M_s1x.yaml +18 -0
  35. configs/densepose_rcnn_R_101_FPN_DL_WC1_s1x.yaml +16 -0
  36. configs/densepose_rcnn_R_101_FPN_DL_WC2M_s1x.yaml +18 -0
  37. configs/densepose_rcnn_R_101_FPN_DL_WC2_s1x.yaml +16 -0
  38. configs/densepose_rcnn_R_101_FPN_DL_s1x.yaml +10 -0
  39. configs/densepose_rcnn_R_101_FPN_WC1M_s1x.yaml +18 -0
  40. configs/densepose_rcnn_R_101_FPN_WC1_s1x.yaml +16 -0
  41. configs/densepose_rcnn_R_101_FPN_WC2M_s1x.yaml +18 -0
  42. configs/densepose_rcnn_R_101_FPN_WC2_s1x.yaml +16 -0
  43. configs/densepose_rcnn_R_101_FPN_s1x.yaml +8 -0
  44. configs/densepose_rcnn_R_101_FPN_s1x_legacy.yaml +17 -0
  45. configs/densepose_rcnn_R_50_FPN_DL_WC1M_s1x.yaml +18 -0
  46. configs/densepose_rcnn_R_50_FPN_DL_WC1_s1x.yaml +16 -0
  47. configs/densepose_rcnn_R_50_FPN_DL_WC2M_s1x.yaml +18 -0
  48. configs/densepose_rcnn_R_50_FPN_DL_WC2_s1x.yaml +16 -0
  49. configs/densepose_rcnn_R_50_FPN_DL_s1x.yaml +10 -0
  50. configs/densepose_rcnn_R_50_FPN_WC1M_s1x.yaml +20 -0
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ckpt/openpose/.DS_Store ADDED
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ckpt/openpose/ckpts/body_pose_model.pth ADDED
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configs/Base-DensePose-RCNN-FPN.yaml ADDED
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+ 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"]
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+ 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
+ DATASETS:
39
+ TRAIN: ("densepose_coco_2014_train", "densepose_coco_2014_valminusminival")
40
+ TEST: ("densepose_coco_2014_minival",)
41
+ SOLVER:
42
+ IMS_PER_BATCH: 16
43
+ BASE_LR: 0.01
44
+ STEPS: (60000, 80000)
45
+ MAX_ITER: 90000
46
+ WARMUP_FACTOR: 0.1
47
+ INPUT:
48
+ MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
configs/HRNet/densepose_rcnn_HRFPN_HRNet_w32_s1x.yaml ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ _BASE_: "../Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "https://1drv.ms/u/s!Aus8VCZ_C_33dYBMemi9xOUFR0w"
4
+ BACKBONE:
5
+ NAME: "build_hrfpn_backbone"
6
+ RPN:
7
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
8
+ ROI_HEADS:
9
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
10
+ SOLVER:
11
+ MAX_ITER: 130000
12
+ STEPS: (100000, 120000)
13
+ CLIP_GRADIENTS:
14
+ ENABLED: True
15
+ CLIP_TYPE: "norm"
16
+ BASE_LR: 0.03
configs/HRNet/densepose_rcnn_HRFPN_HRNet_w40_s1x.yaml ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "../Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "https://1drv.ms/u/s!Aus8VCZ_C_33ck0gvo5jfoWBOPo"
4
+ BACKBONE:
5
+ NAME: "build_hrfpn_backbone"
6
+ RPN:
7
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
8
+ ROI_HEADS:
9
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
10
+ HRNET:
11
+ STAGE2:
12
+ NUM_CHANNELS: [40, 80]
13
+ STAGE3:
14
+ NUM_CHANNELS: [40, 80, 160]
15
+ STAGE4:
16
+ NUM_CHANNELS: [40, 80, 160, 320]
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+ SOLVER:
18
+ MAX_ITER: 130000
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+ STEPS: (100000, 120000)
20
+ CLIP_GRADIENTS:
21
+ ENABLED: True
22
+ CLIP_TYPE: "norm"
23
+ BASE_LR: 0.03
configs/HRNet/densepose_rcnn_HRFPN_HRNet_w48_s1x.yaml ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ _BASE_: "../Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "https://1drv.ms/u/s!Aus8VCZ_C_33dKvqI6pBZlifgJk"
4
+ BACKBONE:
5
+ NAME: "build_hrfpn_backbone"
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+ RPN:
7
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
8
+ ROI_HEADS:
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+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
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+ HRNET:
11
+ STAGE2:
12
+ NUM_CHANNELS: [48, 96]
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+ STAGE3:
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+ NUM_CHANNELS: [48, 96, 192]
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+ STAGE4:
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+ NUM_CHANNELS: [48, 96, 192, 384]
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+ SOLVER:
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+ MAX_ITER: 130000
19
+ STEPS: (100000, 120000)
20
+ CLIP_GRADIENTS:
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+ ENABLED: True
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+ CLIP_TYPE: "norm"
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+ BASE_LR: 0.03
configs/cse/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"
configs/cse/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
configs/cse/densepose_rcnn_R_101_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-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ CSE:
9
+ EMBED_LOSS_NAME: "EmbeddingLoss"
10
+ SOLVER:
11
+ MAX_ITER: 130000
12
+ STEPS: (100000, 120000)
configs/cse/densepose_rcnn_R_101_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-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ CSE:
9
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
10
+ SOLVER:
11
+ MAX_ITER: 130000
12
+ STEPS: (100000, 120000)
configs/cse/densepose_rcnn_R_101_FPN_s1x.yaml ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseV1ConvXHead"
8
+ CSE:
9
+ EMBED_LOSS_NAME: "EmbeddingLoss"
10
+ SOLVER:
11
+ MAX_ITER: 130000
12
+ STEPS: (100000, 120000)
configs/cse/densepose_rcnn_R_101_FPN_soft_s1x.yaml ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseV1ConvXHead"
8
+ CSE:
9
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
10
+ SOLVER:
11
+ MAX_ITER: 130000
12
+ STEPS: (100000, 120000)
configs/cse/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)
configs/cse/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)
configs/cse/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)
configs/cse/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
configs/cse/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
configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_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_animals_finetune_maskonly_24k/270668502/model_final_21b1d2.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
configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_i2m_16k.yaml ADDED
@@ -0,0 +1,121 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k/270668502/model_final_21b1d2.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
+ PIX_TO_SHAPE_CYCLE_LOSS:
16
+ ENABLED: True
17
+ EMBEDDERS:
18
+ "cat_7466":
19
+ TYPE: vertex_feature
20
+ NUM_VERTICES: 7466
21
+ FEATURE_DIM: 256
22
+ FEATURES_TRAINABLE: False
23
+ IS_TRAINABLE: True
24
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
25
+ "dog_7466":
26
+ TYPE: vertex_feature
27
+ NUM_VERTICES: 7466
28
+ FEATURE_DIM: 256
29
+ FEATURES_TRAINABLE: False
30
+ IS_TRAINABLE: True
31
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
32
+ "sheep_5004":
33
+ TYPE: vertex_feature
34
+ NUM_VERTICES: 5004
35
+ FEATURE_DIM: 256
36
+ FEATURES_TRAINABLE: False
37
+ IS_TRAINABLE: True
38
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
39
+ "horse_5004":
40
+ TYPE: vertex_feature
41
+ NUM_VERTICES: 5004
42
+ FEATURE_DIM: 256
43
+ FEATURES_TRAINABLE: False
44
+ IS_TRAINABLE: True
45
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
46
+ "zebra_5002":
47
+ TYPE: vertex_feature
48
+ NUM_VERTICES: 5002
49
+ FEATURE_DIM: 256
50
+ FEATURES_TRAINABLE: False
51
+ IS_TRAINABLE: True
52
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
53
+ "giraffe_5002":
54
+ TYPE: vertex_feature
55
+ NUM_VERTICES: 5002
56
+ FEATURE_DIM: 256
57
+ FEATURES_TRAINABLE: False
58
+ IS_TRAINABLE: True
59
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
60
+ "elephant_5002":
61
+ TYPE: vertex_feature
62
+ NUM_VERTICES: 5002
63
+ FEATURE_DIM: 256
64
+ FEATURES_TRAINABLE: False
65
+ IS_TRAINABLE: True
66
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
67
+ "cow_5002":
68
+ TYPE: vertex_feature
69
+ NUM_VERTICES: 5002
70
+ FEATURE_DIM: 256
71
+ FEATURES_TRAINABLE: False
72
+ IS_TRAINABLE: True
73
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
74
+ "bear_4936":
75
+ TYPE: vertex_feature
76
+ NUM_VERTICES: 4936
77
+ FEATURE_DIM: 256
78
+ FEATURES_TRAINABLE: False
79
+ IS_TRAINABLE: True
80
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
81
+ DATASETS:
82
+ TRAIN:
83
+ - "densepose_lvis_v1_ds2_train_v1"
84
+ TEST:
85
+ - "densepose_lvis_v1_ds2_val_v1"
86
+ WHITELISTED_CATEGORIES:
87
+ "densepose_lvis_v1_ds2_train_v1":
88
+ - 943 # sheep
89
+ - 1202 # zebra
90
+ - 569 # horse
91
+ - 496 # giraffe
92
+ - 422 # elephant
93
+ - 80 # cow
94
+ - 76 # bear
95
+ - 225 # cat
96
+ - 378 # dog
97
+ "densepose_lvis_v1_ds2_val_v1":
98
+ - 943 # sheep
99
+ - 1202 # zebra
100
+ - 569 # horse
101
+ - 496 # giraffe
102
+ - 422 # elephant
103
+ - 80 # cow
104
+ - 76 # bear
105
+ - 225 # cat
106
+ - 378 # dog
107
+ CLASS_TO_MESH_NAME_MAPPING:
108
+ "0": "bear_4936"
109
+ "1": "cow_5002"
110
+ "2": "cat_7466"
111
+ "3": "dog_7466"
112
+ "4": "elephant_5002"
113
+ "5": "giraffe_5002"
114
+ "6": "horse_5004"
115
+ "7": "sheep_5004"
116
+ "8": "zebra_5002"
117
+ SOLVER:
118
+ MAX_ITER: 16000
119
+ STEPS: (12000, 14000)
120
+ DENSEPOSE_EVALUATION:
121
+ EVALUATE_MESH_ALIGNMENT: True
configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_m2m_16k.yaml ADDED
@@ -0,0 +1,138 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k/267687159/model_final_354e61.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
+ SHAPE_TO_SHAPE_CYCLE_LOSS:
16
+ ENABLED: True
17
+ EMBEDDERS:
18
+ "cat_7466":
19
+ TYPE: vertex_feature
20
+ NUM_VERTICES: 7466
21
+ FEATURE_DIM: 256
22
+ FEATURES_TRAINABLE: False
23
+ IS_TRAINABLE: True
24
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
25
+ "dog_7466":
26
+ TYPE: vertex_feature
27
+ NUM_VERTICES: 7466
28
+ FEATURE_DIM: 256
29
+ FEATURES_TRAINABLE: False
30
+ IS_TRAINABLE: True
31
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
32
+ "sheep_5004":
33
+ TYPE: vertex_feature
34
+ NUM_VERTICES: 5004
35
+ FEATURE_DIM: 256
36
+ FEATURES_TRAINABLE: False
37
+ IS_TRAINABLE: True
38
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
39
+ "horse_5004":
40
+ TYPE: vertex_feature
41
+ NUM_VERTICES: 5004
42
+ FEATURE_DIM: 256
43
+ FEATURES_TRAINABLE: False
44
+ IS_TRAINABLE: True
45
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
46
+ "zebra_5002":
47
+ TYPE: vertex_feature
48
+ NUM_VERTICES: 5002
49
+ FEATURE_DIM: 256
50
+ FEATURES_TRAINABLE: False
51
+ IS_TRAINABLE: True
52
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
53
+ "giraffe_5002":
54
+ TYPE: vertex_feature
55
+ NUM_VERTICES: 5002
56
+ FEATURE_DIM: 256
57
+ FEATURES_TRAINABLE: False
58
+ IS_TRAINABLE: True
59
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
60
+ "elephant_5002":
61
+ TYPE: vertex_feature
62
+ NUM_VERTICES: 5002
63
+ FEATURE_DIM: 256
64
+ FEATURES_TRAINABLE: False
65
+ IS_TRAINABLE: True
66
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
67
+ "cow_5002":
68
+ TYPE: vertex_feature
69
+ NUM_VERTICES: 5002
70
+ FEATURE_DIM: 256
71
+ FEATURES_TRAINABLE: False
72
+ IS_TRAINABLE: True
73
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
74
+ "bear_4936":
75
+ TYPE: vertex_feature
76
+ NUM_VERTICES: 4936
77
+ FEATURE_DIM: 256
78
+ FEATURES_TRAINABLE: False
79
+ IS_TRAINABLE: True
80
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
81
+ "smpl_27554":
82
+ TYPE: vertex_feature
83
+ NUM_VERTICES: 27554
84
+ FEATURE_DIM: 256
85
+ FEATURES_TRAINABLE: False
86
+ IS_TRAINABLE: True
87
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_smpl_27554_256.pkl"
88
+ DATASETS:
89
+ TRAIN:
90
+ - "densepose_lvis_v1_ds2_train_v1"
91
+ TEST:
92
+ - "densepose_lvis_v1_ds2_val_v1"
93
+ WHITELISTED_CATEGORIES:
94
+ "densepose_lvis_v1_ds2_train_v1":
95
+ - 943 # sheep
96
+ - 1202 # zebra
97
+ - 569 # horse
98
+ - 496 # giraffe
99
+ - 422 # elephant
100
+ - 80 # cow
101
+ - 76 # bear
102
+ - 225 # cat
103
+ - 378 # dog
104
+ "densepose_lvis_v1_ds2_val_v1":
105
+ - 943 # sheep
106
+ - 1202 # zebra
107
+ - 569 # horse
108
+ - 496 # giraffe
109
+ - 422 # elephant
110
+ - 80 # cow
111
+ - 76 # bear
112
+ - 225 # cat
113
+ - 378 # dog
114
+ CLASS_TO_MESH_NAME_MAPPING:
115
+ "0": "bear_4936"
116
+ "1": "cow_5002"
117
+ "2": "cat_7466"
118
+ "3": "dog_7466"
119
+ "4": "elephant_5002"
120
+ "5": "giraffe_5002"
121
+ "6": "horse_5004"
122
+ "7": "sheep_5004"
123
+ "8": "zebra_5002"
124
+ SOLVER:
125
+ MAX_ITER: 16000
126
+ STEPS: (12000, 14000)
127
+ DENSEPOSE_EVALUATION:
128
+ EVALUATE_MESH_ALIGNMENT: True
129
+ MESH_ALIGNMENT_MESH_NAMES:
130
+ - bear_4936
131
+ - cow_5002
132
+ - cat_7466
133
+ - dog_7466
134
+ - elephant_5002
135
+ - giraffe_5002
136
+ - horse_5004
137
+ - sheep_5004
138
+ - zebra_5002
configs/cse/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
configs/cse/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
configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k.yaml ADDED
@@ -0,0 +1,118 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ EMBED_LOSS_WEIGHT: 0.0
14
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
15
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
16
+ EMBEDDERS:
17
+ "cat_7466":
18
+ TYPE: vertex_feature
19
+ NUM_VERTICES: 7466
20
+ FEATURE_DIM: 256
21
+ FEATURES_TRAINABLE: False
22
+ IS_TRAINABLE: True
23
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
24
+ "dog_7466":
25
+ TYPE: vertex_feature
26
+ NUM_VERTICES: 7466
27
+ FEATURE_DIM: 256
28
+ FEATURES_TRAINABLE: False
29
+ IS_TRAINABLE: True
30
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
31
+ "sheep_5004":
32
+ TYPE: vertex_feature
33
+ NUM_VERTICES: 5004
34
+ FEATURE_DIM: 256
35
+ FEATURES_TRAINABLE: False
36
+ IS_TRAINABLE: True
37
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
38
+ "horse_5004":
39
+ TYPE: vertex_feature
40
+ NUM_VERTICES: 5004
41
+ FEATURE_DIM: 256
42
+ FEATURES_TRAINABLE: False
43
+ IS_TRAINABLE: True
44
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
45
+ "zebra_5002":
46
+ TYPE: vertex_feature
47
+ NUM_VERTICES: 5002
48
+ FEATURE_DIM: 256
49
+ FEATURES_TRAINABLE: False
50
+ IS_TRAINABLE: True
51
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
52
+ "giraffe_5002":
53
+ TYPE: vertex_feature
54
+ NUM_VERTICES: 5002
55
+ FEATURE_DIM: 256
56
+ FEATURES_TRAINABLE: False
57
+ IS_TRAINABLE: True
58
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
59
+ "elephant_5002":
60
+ TYPE: vertex_feature
61
+ NUM_VERTICES: 5002
62
+ FEATURE_DIM: 256
63
+ FEATURES_TRAINABLE: False
64
+ IS_TRAINABLE: True
65
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
66
+ "cow_5002":
67
+ TYPE: vertex_feature
68
+ NUM_VERTICES: 5002
69
+ FEATURE_DIM: 256
70
+ FEATURES_TRAINABLE: False
71
+ IS_TRAINABLE: True
72
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
73
+ "bear_4936":
74
+ TYPE: vertex_feature
75
+ NUM_VERTICES: 4936
76
+ FEATURE_DIM: 256
77
+ FEATURES_TRAINABLE: False
78
+ IS_TRAINABLE: True
79
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
80
+ DATASETS:
81
+ TRAIN:
82
+ - "densepose_lvis_v1_ds2_train_v1"
83
+ TEST:
84
+ - "densepose_lvis_v1_ds2_val_v1"
85
+ WHITELISTED_CATEGORIES:
86
+ "densepose_lvis_v1_ds2_train_v1":
87
+ - 943 # sheep
88
+ - 1202 # zebra
89
+ - 569 # horse
90
+ - 496 # giraffe
91
+ - 422 # elephant
92
+ - 80 # cow
93
+ - 76 # bear
94
+ - 225 # cat
95
+ - 378 # dog
96
+ "densepose_lvis_v1_ds2_val_v1":
97
+ - 943 # sheep
98
+ - 1202 # zebra
99
+ - 569 # horse
100
+ - 496 # giraffe
101
+ - 422 # elephant
102
+ - 80 # cow
103
+ - 76 # bear
104
+ - 225 # cat
105
+ - 378 # dog
106
+ CLASS_TO_MESH_NAME_MAPPING:
107
+ "0": "bear_4936"
108
+ "1": "cow_5002"
109
+ "2": "cat_7466"
110
+ "3": "dog_7466"
111
+ "4": "elephant_5002"
112
+ "5": "giraffe_5002"
113
+ "6": "horse_5004"
114
+ "7": "sheep_5004"
115
+ "8": "zebra_5002"
116
+ SOLVER:
117
+ MAX_ITER: 24000
118
+ STEPS: (20000, 22000)
configs/cse/densepose_rcnn_R_50_FPN_soft_chimps_finetune_4k.yaml ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseV1ConvXHead"
8
+ CSE:
9
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
10
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
11
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
12
+ EMBEDDERS:
13
+ "chimp_5029":
14
+ TYPE: vertex_feature
15
+ NUM_VERTICES: 5029
16
+ FEATURE_DIM: 256
17
+ FEATURES_TRAINABLE: False
18
+ IS_TRAINABLE: True
19
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_chimp_5029_256.pkl"
20
+ DATASETS:
21
+ TRAIN:
22
+ - "densepose_chimps_cse_train"
23
+ TEST:
24
+ - "densepose_chimps_cse_val"
25
+ CLASS_TO_MESH_NAME_MAPPING:
26
+ "0": "chimp_5029"
27
+ SOLVER:
28
+ MAX_ITER: 4000
29
+ STEPS: (3000, 3500)
configs/cse/densepose_rcnn_R_50_FPN_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: "DensePoseV1ConvXHead"
8
+ CSE:
9
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
10
+ SOLVER:
11
+ MAX_ITER: 130000
12
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_101_FPN_DL_WC1M_s1x.yaml ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ UV_CONFIDENCE:
9
+ ENABLED: True
10
+ TYPE: "iid_iso"
11
+ SEGM_CONFIDENCE:
12
+ ENABLED: True
13
+ POINT_REGRESSION_WEIGHTS: 0.0005
14
+ SOLVER:
15
+ CLIP_GRADIENTS:
16
+ ENABLED: True
17
+ MAX_ITER: 130000
18
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_101_FPN_DL_WC1_s1x.yaml ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ UV_CONFIDENCE:
9
+ ENABLED: True
10
+ TYPE: "iid_iso"
11
+ POINT_REGRESSION_WEIGHTS: 0.0005
12
+ SOLVER:
13
+ CLIP_GRADIENTS:
14
+ ENABLED: True
15
+ MAX_ITER: 130000
16
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_101_FPN_DL_WC2M_s1x.yaml ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ UV_CONFIDENCE:
9
+ ENABLED: True
10
+ TYPE: "indep_aniso"
11
+ SEGM_CONFIDENCE:
12
+ ENABLED: True
13
+ POINT_REGRESSION_WEIGHTS: 0.0005
14
+ SOLVER:
15
+ CLIP_GRADIENTS:
16
+ ENABLED: True
17
+ MAX_ITER: 130000
18
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_101_FPN_DL_WC2_s1x.yaml ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ UV_CONFIDENCE:
9
+ ENABLED: True
10
+ TYPE: "indep_aniso"
11
+ POINT_REGRESSION_WEIGHTS: 0.0005
12
+ SOLVER:
13
+ CLIP_GRADIENTS:
14
+ ENABLED: True
15
+ MAX_ITER: 130000
16
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_101_FPN_DL_s1x.yaml ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ SOLVER:
9
+ MAX_ITER: 130000
10
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_101_FPN_WC1M_s1x.yaml ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ UV_CONFIDENCE:
8
+ ENABLED: True
9
+ TYPE: "iid_iso"
10
+ SEGM_CONFIDENCE:
11
+ ENABLED: True
12
+ POINT_REGRESSION_WEIGHTS: 0.0005
13
+ SOLVER:
14
+ CLIP_GRADIENTS:
15
+ ENABLED: True
16
+ MAX_ITER: 130000
17
+ STEPS: (100000, 120000)
18
+ WARMUP_FACTOR: 0.025
configs/densepose_rcnn_R_101_FPN_WC1_s1x.yaml ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ UV_CONFIDENCE:
8
+ ENABLED: True
9
+ TYPE: "iid_iso"
10
+ POINT_REGRESSION_WEIGHTS: 0.0005
11
+ SOLVER:
12
+ CLIP_GRADIENTS:
13
+ ENABLED: True
14
+ MAX_ITER: 130000
15
+ STEPS: (100000, 120000)
16
+ WARMUP_FACTOR: 0.025
configs/densepose_rcnn_R_101_FPN_WC2M_s1x.yaml ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ UV_CONFIDENCE:
8
+ ENABLED: True
9
+ TYPE: "indep_aniso"
10
+ SEGM_CONFIDENCE:
11
+ ENABLED: True
12
+ POINT_REGRESSION_WEIGHTS: 0.0005
13
+ SOLVER:
14
+ CLIP_GRADIENTS:
15
+ ENABLED: True
16
+ MAX_ITER: 130000
17
+ STEPS: (100000, 120000)
18
+ WARMUP_FACTOR: 0.025
configs/densepose_rcnn_R_101_FPN_WC2_s1x.yaml ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ UV_CONFIDENCE:
8
+ ENABLED: True
9
+ TYPE: "indep_aniso"
10
+ POINT_REGRESSION_WEIGHTS: 0.0005
11
+ SOLVER:
12
+ CLIP_GRADIENTS:
13
+ ENABLED: True
14
+ MAX_ITER: 130000
15
+ STEPS: (100000, 120000)
16
+ WARMUP_FACTOR: 0.025
configs/densepose_rcnn_R_101_FPN_s1x.yaml ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ SOLVER:
7
+ MAX_ITER: 130000
8
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_101_FPN_s1x_legacy.yaml ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
4
+ RESNETS:
5
+ DEPTH: 101
6
+ ROI_DENSEPOSE_HEAD:
7
+ NUM_COARSE_SEGM_CHANNELS: 15
8
+ POOLER_RESOLUTION: 14
9
+ HEATMAP_SIZE: 56
10
+ INDEX_WEIGHTS: 2.0
11
+ PART_WEIGHTS: 0.3
12
+ POINT_REGRESSION_WEIGHTS: 0.1
13
+ DECODER_ON: False
14
+ SOLVER:
15
+ BASE_LR: 0.002
16
+ MAX_ITER: 130000
17
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_50_FPN_DL_WC1M_s1x.yaml ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ UV_CONFIDENCE:
9
+ ENABLED: True
10
+ TYPE: "iid_iso"
11
+ SEGM_CONFIDENCE:
12
+ ENABLED: True
13
+ POINT_REGRESSION_WEIGHTS: 0.0005
14
+ SOLVER:
15
+ CLIP_GRADIENTS:
16
+ ENABLED: True
17
+ MAX_ITER: 130000
18
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_50_FPN_DL_WC1_s1x.yaml ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ UV_CONFIDENCE:
9
+ ENABLED: True
10
+ TYPE: "iid_iso"
11
+ POINT_REGRESSION_WEIGHTS: 0.0005
12
+ SOLVER:
13
+ CLIP_GRADIENTS:
14
+ ENABLED: True
15
+ MAX_ITER: 130000
16
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_50_FPN_DL_WC2M_s1x.yaml ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ UV_CONFIDENCE:
9
+ ENABLED: True
10
+ TYPE: "indep_aniso"
11
+ SEGM_CONFIDENCE:
12
+ ENABLED: True
13
+ POINT_REGRESSION_WEIGHTS: 0.0005
14
+ SOLVER:
15
+ CLIP_GRADIENTS:
16
+ ENABLED: True
17
+ MAX_ITER: 130000
18
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_50_FPN_DL_WC2_s1x.yaml ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ UV_CONFIDENCE:
9
+ ENABLED: True
10
+ TYPE: "indep_aniso"
11
+ POINT_REGRESSION_WEIGHTS: 0.0005
12
+ SOLVER:
13
+ CLIP_GRADIENTS:
14
+ ENABLED: True
15
+ MAX_ITER: 130000
16
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_50_FPN_DL_s1x.yaml ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_DENSEPOSE_HEAD:
7
+ NAME: "DensePoseDeepLabHead"
8
+ SOLVER:
9
+ MAX_ITER: 130000
10
+ STEPS: (100000, 120000)
configs/densepose_rcnn_R_50_FPN_WC1M_s1x.yaml ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ _BASE_: "Base-DensePose-RCNN-FPN.yaml"
2
+ MODEL:
3
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
4
+ RESNETS:
5
+ DEPTH: 50
6
+ ROI_DENSEPOSE_HEAD:
7
+ UV_CONFIDENCE:
8
+ ENABLED: True
9
+ TYPE: "iid_iso"
10
+ SEGM_CONFIDENCE:
11
+ ENABLED: True
12
+ POINT_REGRESSION_WEIGHTS: 0.0005
13
+ SOLVER:
14
+ CLIP_GRADIENTS:
15
+ ENABLED: True
16
+ CLIP_TYPE: norm
17
+ CLIP_VALUE: 100.0
18
+ MAX_ITER: 130000
19
+ STEPS: (100000, 120000)
20
+ WARMUP_FACTOR: 0.025