diff --git a/configs/Base-DensePose-RCNN-FPN.yaml b/configs/Base-DensePose-RCNN-FPN.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..1d9366853474f792ce1ac51a698ce5ee187c6ead
--- /dev/null
+++ b/configs/Base-DensePose-RCNN-FPN.yaml
@@ -0,0 +1,48 @@
+VERSION: 2
+MODEL:
+ META_ARCHITECTURE: "GeneralizedRCNN"
+ BACKBONE:
+ NAME: "build_resnet_fpn_backbone"
+ RESNETS:
+ OUT_FEATURES: ["res2", "res3", "res4", "res5"]
+ FPN:
+ IN_FEATURES: ["res2", "res3", "res4", "res5"]
+ ANCHOR_GENERATOR:
+ SIZES: [[32], [64], [128], [256], [512]] # One size for each in feature map
+ ASPECT_RATIOS: [[0.5, 1.0, 2.0]] # Three aspect ratios (same for all in feature maps)
+ RPN:
+ IN_FEATURES: ["p2", "p3", "p4", "p5", "p6"]
+ PRE_NMS_TOPK_TRAIN: 2000 # Per FPN level
+ PRE_NMS_TOPK_TEST: 1000 # Per FPN level
+ # Detectron1 uses 2000 proposals per-batch,
+ # (See "modeling/rpn/rpn_outputs.py" for details of this legacy issue)
+ # which is approximately 1000 proposals per-image since the default batch size for FPN is 2.
+ POST_NMS_TOPK_TRAIN: 1000
+ POST_NMS_TOPK_TEST: 1000
+
+ DENSEPOSE_ON: True
+ ROI_HEADS:
+ NAME: "DensePoseROIHeads"
+ IN_FEATURES: ["p2", "p3", "p4", "p5"]
+ NUM_CLASSES: 1
+ ROI_BOX_HEAD:
+ NAME: "FastRCNNConvFCHead"
+ NUM_FC: 2
+ POOLER_RESOLUTION: 7
+ POOLER_SAMPLING_RATIO: 2
+ POOLER_TYPE: "ROIAlign"
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ POOLER_TYPE: "ROIAlign"
+ NUM_COARSE_SEGM_CHANNELS: 2
+DATASETS:
+ TRAIN: ("densepose_coco_2014_train", "densepose_coco_2014_valminusminival")
+ TEST: ("densepose_coco_2014_minival",)
+SOLVER:
+ IMS_PER_BATCH: 16
+ BASE_LR: 0.01
+ STEPS: (60000, 80000)
+ MAX_ITER: 90000
+ WARMUP_FACTOR: 0.1
+INPUT:
+ MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
diff --git a/configs/HRNet/densepose_rcnn_HRFPN_HRNet_w32_s1x.yaml b/configs/HRNet/densepose_rcnn_HRFPN_HRNet_w32_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..33454378f985f98283411b0ac40c0bafd7152c99
--- /dev/null
+++ b/configs/HRNet/densepose_rcnn_HRFPN_HRNet_w32_s1x.yaml
@@ -0,0 +1,16 @@
+_BASE_: "../Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://1drv.ms/u/s!Aus8VCZ_C_33dYBMemi9xOUFR0w"
+ BACKBONE:
+ NAME: "build_hrfpn_backbone"
+ RPN:
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
+ ROI_HEADS:
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ CLIP_GRADIENTS:
+ ENABLED: True
+ CLIP_TYPE: "norm"
+ BASE_LR: 0.03
diff --git a/configs/HRNet/densepose_rcnn_HRFPN_HRNet_w40_s1x.yaml b/configs/HRNet/densepose_rcnn_HRFPN_HRNet_w40_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..07bd4ff6624d5c793920e980e5597acc653b547a
--- /dev/null
+++ b/configs/HRNet/densepose_rcnn_HRFPN_HRNet_w40_s1x.yaml
@@ -0,0 +1,23 @@
+_BASE_: "../Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://1drv.ms/u/s!Aus8VCZ_C_33ck0gvo5jfoWBOPo"
+ BACKBONE:
+ NAME: "build_hrfpn_backbone"
+ RPN:
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
+ ROI_HEADS:
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
+ HRNET:
+ STAGE2:
+ NUM_CHANNELS: [40, 80]
+ STAGE3:
+ NUM_CHANNELS: [40, 80, 160]
+ STAGE4:
+ NUM_CHANNELS: [40, 80, 160, 320]
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ CLIP_GRADIENTS:
+ ENABLED: True
+ CLIP_TYPE: "norm"
+ BASE_LR: 0.03
diff --git a/configs/HRNet/densepose_rcnn_HRFPN_HRNet_w48_s1x.yaml b/configs/HRNet/densepose_rcnn_HRFPN_HRNet_w48_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6dee8a08cdb8ea320f515f96860ea483258afb35
--- /dev/null
+++ b/configs/HRNet/densepose_rcnn_HRFPN_HRNet_w48_s1x.yaml
@@ -0,0 +1,23 @@
+_BASE_: "../Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://1drv.ms/u/s!Aus8VCZ_C_33dKvqI6pBZlifgJk"
+ BACKBONE:
+ NAME: "build_hrfpn_backbone"
+ RPN:
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
+ ROI_HEADS:
+ IN_FEATURES: ['p1', 'p2', 'p3', 'p4', 'p5']
+ HRNET:
+ STAGE2:
+ NUM_CHANNELS: [48, 96]
+ STAGE3:
+ NUM_CHANNELS: [48, 96, 192]
+ STAGE4:
+ NUM_CHANNELS: [48, 96, 192, 384]
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ CLIP_GRADIENTS:
+ ENABLED: True
+ CLIP_TYPE: "norm"
+ BASE_LR: 0.03
diff --git a/configs/cse/Base-DensePose-RCNN-FPN-Human.yaml b/configs/cse/Base-DensePose-RCNN-FPN-Human.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..fc879eb7c3be1b712f98868bbecd231de8ecf99f
--- /dev/null
+++ b/configs/cse/Base-DensePose-RCNN-FPN-Human.yaml
@@ -0,0 +1,20 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ ROI_DENSEPOSE_HEAD:
+ CSE:
+ EMBEDDERS:
+ "smpl_27554":
+ TYPE: vertex_feature
+ NUM_VERTICES: 27554
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_smpl_27554_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_coco_2014_train_cse"
+ - "densepose_coco_2014_valminusminival_cse"
+ TEST:
+ - "densepose_coco_2014_minival_cse"
+ CLASS_TO_MESH_NAME_MAPPING:
+ "0": "smpl_27554"
diff --git a/configs/cse/Base-DensePose-RCNN-FPN.yaml b/configs/cse/Base-DensePose-RCNN-FPN.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f6dd98c6dd8dca52135ab46116cb5b6f3e5cbea7
--- /dev/null
+++ b/configs/cse/Base-DensePose-RCNN-FPN.yaml
@@ -0,0 +1,60 @@
+VERSION: 2
+MODEL:
+ META_ARCHITECTURE: "GeneralizedRCNN"
+ BACKBONE:
+ NAME: "build_resnet_fpn_backbone"
+ RESNETS:
+ OUT_FEATURES: ["res2", "res3", "res4", "res5"]
+ FPN:
+ IN_FEATURES: ["res2", "res3", "res4", "res5"]
+ ANCHOR_GENERATOR:
+ SIZES: [[32], [64], [128], [256], [512]] # One size for each in feature map
+ ASPECT_RATIOS: [[0.5, 1.0, 2.0]] # Three aspect ratios (same for all in feature maps)
+ RPN:
+ IN_FEATURES: ["p2", "p3", "p4", "p5", "p6"]
+ PRE_NMS_TOPK_TRAIN: 2000 # Per FPN level
+ PRE_NMS_TOPK_TEST: 1000 # Per FPN level
+ # Detectron1 uses 2000 proposals per-batch,
+ # (See "modeling/rpn/rpn_outputs.py" for details of this legacy issue)
+ # which is approximately 1000 proposals per-image since the default batch size for FPN is 2.
+ POST_NMS_TOPK_TRAIN: 1000
+ POST_NMS_TOPK_TEST: 1000
+
+ DENSEPOSE_ON: True
+ ROI_HEADS:
+ NAME: "DensePoseROIHeads"
+ IN_FEATURES: ["p2", "p3", "p4", "p5"]
+ NUM_CLASSES: 1
+ ROI_BOX_HEAD:
+ NAME: "FastRCNNConvFCHead"
+ NUM_FC: 2
+ POOLER_RESOLUTION: 7
+ POOLER_SAMPLING_RATIO: 2
+ POOLER_TYPE: "ROIAlign"
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ POOLER_TYPE: "ROIAlign"
+ NUM_COARSE_SEGM_CHANNELS: 2
+ PREDICTOR_NAME: "DensePoseEmbeddingPredictor"
+ LOSS_NAME: "DensePoseCseLoss"
+ CSE:
+ # embedding loss, possible values:
+ # - "EmbeddingLoss"
+ # - "SoftEmbeddingLoss"
+ EMBED_LOSS_NAME: "EmbeddingLoss"
+SOLVER:
+ IMS_PER_BATCH: 16
+ BASE_LR: 0.01
+ STEPS: (60000, 80000)
+ MAX_ITER: 90000
+ WARMUP_FACTOR: 0.1
+ CLIP_GRADIENTS:
+ CLIP_TYPE: norm
+ CLIP_VALUE: 1.0
+ ENABLED: true
+ NORM_TYPE: 2.0
+INPUT:
+ MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
+DENSEPOSE_EVALUATION:
+ TYPE: cse
+ STORAGE: file
diff --git a/configs/cse/densepose_rcnn_R_101_FPN_DL_s1x.yaml b/configs/cse/densepose_rcnn_R_101_FPN_DL_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..3e7ef66029ecf2f9b15ab8dd113e79f92d7c559b
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_101_FPN_DL_s1x.yaml
@@ -0,0 +1,12 @@
+_BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ CSE:
+ EMBED_LOSS_NAME: "EmbeddingLoss"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/cse/densepose_rcnn_R_101_FPN_DL_soft_s1x.yaml b/configs/cse/densepose_rcnn_R_101_FPN_DL_soft_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..0bacd245d7fd986cb08bd2dce14f486121bc6194
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_101_FPN_DL_soft_s1x.yaml
@@ -0,0 +1,12 @@
+_BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/cse/densepose_rcnn_R_101_FPN_s1x.yaml b/configs/cse/densepose_rcnn_R_101_FPN_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..51caee49855275b77686a3701838589de66d74e4
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_101_FPN_s1x.yaml
@@ -0,0 +1,12 @@
+_BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ CSE:
+ EMBED_LOSS_NAME: "EmbeddingLoss"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/cse/densepose_rcnn_R_101_FPN_soft_s1x.yaml b/configs/cse/densepose_rcnn_R_101_FPN_soft_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..b86327b5a9bed08cf9b7bc402f459fc64d7160a4
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_101_FPN_soft_s1x.yaml
@@ -0,0 +1,12 @@
+_BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_DL_s1x.yaml b/configs/cse/densepose_rcnn_R_50_FPN_DL_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..bde88f9050f4a2ca19f7acabeef4bc93ce1f9741
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_DL_s1x.yaml
@@ -0,0 +1,12 @@
+_BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ CSE:
+ EMBED_LOSS_NAME: "EmbeddingLoss"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_DL_soft_s1x.yaml b/configs/cse/densepose_rcnn_R_50_FPN_DL_soft_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d3bab3b25a188d222aa45ff31ff51021d6b5d35c
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_DL_soft_s1x.yaml
@@ -0,0 +1,12 @@
+_BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_s1x.yaml b/configs/cse/densepose_rcnn_R_50_FPN_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d87fc3a1522d6e98fc5d053f2bc197ef9ac9c947
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_s1x.yaml
@@ -0,0 +1,12 @@
+_BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ CSE:
+ EMBED_LOSS_NAME: "EmbeddingLoss"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_16k.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_16k.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..4cd9254aa46e903da311eb41c9dfcfa44fa59b5f
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_16k.yaml
@@ -0,0 +1,133 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_HEADS:
+ NUM_CLASSES: 1
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
+ EMBEDDERS:
+ "cat_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
+ "dog_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
+ "sheep_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
+ "horse_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
+ "zebra_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
+ "giraffe_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
+ "elephant_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
+ "cow_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
+ "bear_4936":
+ TYPE: vertex_feature
+ NUM_VERTICES: 4936
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_lvis_v1_ds2_train_v1"
+ TEST:
+ - "densepose_lvis_v1_ds2_val_v1"
+ WHITELISTED_CATEGORIES:
+ "densepose_lvis_v1_ds2_train_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_ds2_val_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ CATEGORY_MAPS:
+ "densepose_lvis_v1_ds2_train_v1":
+ "1202": 943 # zebra -> sheep
+ "569": 943 # horse -> sheep
+ "496": 943 # giraffe -> sheep
+ "422": 943 # elephant -> sheep
+ "80": 943 # cow -> sheep
+ "76": 943 # bear -> sheep
+ "225": 943 # cat -> sheep
+ "378": 943 # dog -> sheep
+ "densepose_lvis_v1_ds2_val_v1":
+ "1202": 943 # zebra -> sheep
+ "569": 943 # horse -> sheep
+ "496": 943 # giraffe -> sheep
+ "422": 943 # elephant -> sheep
+ "80": 943 # cow -> sheep
+ "76": 943 # bear -> sheep
+ "225": 943 # cat -> sheep
+ "378": 943 # dog -> sheep
+ CLASS_TO_MESH_NAME_MAPPING:
+ # Note: different classes are mapped to a single class
+ # mesh is chosen based on GT data, so this is just some
+ # value which has no particular meaning
+ "0": "sheep_5004"
+SOLVER:
+ MAX_ITER: 16000
+ STEPS: (12000, 14000)
+DENSEPOSE_EVALUATION:
+ EVALUATE_MESH_ALIGNMENT: True
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_4k.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_4k.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..b207e63d7bfa228a9205e6eee99f5181422c9213
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_CA_finetune_4k.yaml
@@ -0,0 +1,133 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_HEADS:
+ NUM_CLASSES: 1
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
+ EMBEDDERS:
+ "cat_5001":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5001
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_5001_256.pkl"
+ "dog_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_5002_256.pkl"
+ "sheep_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
+ "horse_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
+ "zebra_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
+ "giraffe_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
+ "elephant_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
+ "cow_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
+ "bear_4936":
+ TYPE: vertex_feature
+ NUM_VERTICES: 4936
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_lvis_v1_ds1_train_v1"
+ TEST:
+ - "densepose_lvis_v1_ds1_val_v1"
+ WHITELISTED_CATEGORIES:
+ "densepose_lvis_v1_ds1_train_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_ds1_val_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ CATEGORY_MAPS:
+ "densepose_lvis_v1_ds1_train_v1":
+ "1202": 943 # zebra -> sheep
+ "569": 943 # horse -> sheep
+ "496": 943 # giraffe -> sheep
+ "422": 943 # elephant -> sheep
+ "80": 943 # cow -> sheep
+ "76": 943 # bear -> sheep
+ "225": 943 # cat -> sheep
+ "378": 943 # dog -> sheep
+ "densepose_lvis_v1_ds1_val_v1":
+ "1202": 943 # zebra -> sheep
+ "569": 943 # horse -> sheep
+ "496": 943 # giraffe -> sheep
+ "422": 943 # elephant -> sheep
+ "80": 943 # cow -> sheep
+ "76": 943 # bear -> sheep
+ "225": 943 # cat -> sheep
+ "378": 943 # dog -> sheep
+ CLASS_TO_MESH_NAME_MAPPING:
+ # Note: different classes are mapped to a single class
+ # mesh is chosen based on GT data, so this is just some
+ # value which has no particular meaning
+ "0": "sheep_5004"
+SOLVER:
+ MAX_ITER: 4000
+ STEPS: (3000, 3500)
+DENSEPOSE_EVALUATION:
+ EVALUATE_MESH_ALIGNMENT: True
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_16k.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_16k.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..a3f49d47fee9418cee3f8b8945abeb9cb4ca868c
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_16k.yaml
@@ -0,0 +1,119 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k/270668502/model_final_21b1d2.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_HEADS:
+ NUM_CLASSES: 9
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
+ EMBEDDERS:
+ "cat_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
+ "dog_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
+ "sheep_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
+ "horse_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
+ "zebra_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
+ "giraffe_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
+ "elephant_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
+ "cow_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
+ "bear_4936":
+ TYPE: vertex_feature
+ NUM_VERTICES: 4936
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_lvis_v1_ds2_train_v1"
+ TEST:
+ - "densepose_lvis_v1_ds2_val_v1"
+ WHITELISTED_CATEGORIES:
+ "densepose_lvis_v1_ds2_train_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_ds2_val_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ CLASS_TO_MESH_NAME_MAPPING:
+ "0": "bear_4936"
+ "1": "cow_5002"
+ "2": "cat_7466"
+ "3": "dog_7466"
+ "4": "elephant_5002"
+ "5": "giraffe_5002"
+ "6": "horse_5004"
+ "7": "sheep_5004"
+ "8": "zebra_5002"
+SOLVER:
+ MAX_ITER: 16000
+ STEPS: (12000, 14000)
+DENSEPOSE_EVALUATION:
+ EVALUATE_MESH_ALIGNMENT: True
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_i2m_16k.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_i2m_16k.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..7addb590c9cced44af123850bc25d7dada492e31
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_i2m_16k.yaml
@@ -0,0 +1,121 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k/270668502/model_final_21b1d2.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_HEADS:
+ NUM_CLASSES: 9
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
+ PIX_TO_SHAPE_CYCLE_LOSS:
+ ENABLED: True
+ EMBEDDERS:
+ "cat_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
+ "dog_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
+ "sheep_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
+ "horse_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
+ "zebra_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
+ "giraffe_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
+ "elephant_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
+ "cow_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
+ "bear_4936":
+ TYPE: vertex_feature
+ NUM_VERTICES: 4936
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_lvis_v1_ds2_train_v1"
+ TEST:
+ - "densepose_lvis_v1_ds2_val_v1"
+ WHITELISTED_CATEGORIES:
+ "densepose_lvis_v1_ds2_train_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_ds2_val_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ CLASS_TO_MESH_NAME_MAPPING:
+ "0": "bear_4936"
+ "1": "cow_5002"
+ "2": "cat_7466"
+ "3": "dog_7466"
+ "4": "elephant_5002"
+ "5": "giraffe_5002"
+ "6": "horse_5004"
+ "7": "sheep_5004"
+ "8": "zebra_5002"
+SOLVER:
+ MAX_ITER: 16000
+ STEPS: (12000, 14000)
+DENSEPOSE_EVALUATION:
+ EVALUATE_MESH_ALIGNMENT: True
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_m2m_16k.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_m2m_16k.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..1c96d46d28d685a4977b0d8e27de005fcb63d544
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_I0_finetune_m2m_16k.yaml
@@ -0,0 +1,138 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k/267687159/model_final_354e61.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_HEADS:
+ NUM_CLASSES: 9
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
+ SHAPE_TO_SHAPE_CYCLE_LOSS:
+ ENABLED: True
+ EMBEDDERS:
+ "cat_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
+ "dog_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
+ "sheep_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
+ "horse_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
+ "zebra_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
+ "giraffe_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
+ "elephant_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
+ "cow_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
+ "bear_4936":
+ TYPE: vertex_feature
+ NUM_VERTICES: 4936
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
+ "smpl_27554":
+ TYPE: vertex_feature
+ NUM_VERTICES: 27554
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_smpl_27554_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_lvis_v1_ds2_train_v1"
+ TEST:
+ - "densepose_lvis_v1_ds2_val_v1"
+ WHITELISTED_CATEGORIES:
+ "densepose_lvis_v1_ds2_train_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_ds2_val_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ CLASS_TO_MESH_NAME_MAPPING:
+ "0": "bear_4936"
+ "1": "cow_5002"
+ "2": "cat_7466"
+ "3": "dog_7466"
+ "4": "elephant_5002"
+ "5": "giraffe_5002"
+ "6": "horse_5004"
+ "7": "sheep_5004"
+ "8": "zebra_5002"
+SOLVER:
+ MAX_ITER: 16000
+ STEPS: (12000, 14000)
+DENSEPOSE_EVALUATION:
+ EVALUATE_MESH_ALIGNMENT: True
+ MESH_ALIGNMENT_MESH_NAMES:
+ - bear_4936
+ - cow_5002
+ - cat_7466
+ - dog_7466
+ - elephant_5002
+ - giraffe_5002
+ - horse_5004
+ - sheep_5004
+ - zebra_5002
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_16k.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_16k.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..a459b886df95ac84b15f28e19e873fa4534b974a
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_16k.yaml
@@ -0,0 +1,119 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_HEADS:
+ NUM_CLASSES: 9
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
+ EMBEDDERS:
+ "cat_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
+ "dog_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
+ "sheep_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
+ "horse_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
+ "zebra_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
+ "giraffe_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
+ "elephant_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
+ "cow_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
+ "bear_4936":
+ TYPE: vertex_feature
+ NUM_VERTICES: 4936
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_lvis_v1_ds2_train_v1"
+ TEST:
+ - "densepose_lvis_v1_ds2_val_v1"
+ WHITELISTED_CATEGORIES:
+ "densepose_lvis_v1_ds2_train_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_ds2_val_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ CLASS_TO_MESH_NAME_MAPPING:
+ "0": "bear_4936"
+ "1": "cow_5002"
+ "2": "cat_7466"
+ "3": "dog_7466"
+ "4": "elephant_5002"
+ "5": "giraffe_5002"
+ "6": "horse_5004"
+ "7": "sheep_5004"
+ "8": "zebra_5002"
+SOLVER:
+ MAX_ITER: 16000
+ STEPS: (12000, 14000)
+DENSEPOSE_EVALUATION:
+ EVALUATE_MESH_ALIGNMENT: True
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_4k.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_4k.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..36748658a2bb7de8f04ea6e67d7dcbb9d6158f2f
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_4k.yaml
@@ -0,0 +1,119 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_HEADS:
+ NUM_CLASSES: 9
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
+ EMBEDDERS:
+ "cat_5001":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5001
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_5001_256.pkl"
+ "dog_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_5002_256.pkl"
+ "sheep_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
+ "horse_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
+ "zebra_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
+ "giraffe_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
+ "elephant_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
+ "cow_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
+ "bear_4936":
+ TYPE: vertex_feature
+ NUM_VERTICES: 4936
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_lvis_v1_ds1_train_v1"
+ TEST:
+ - "densepose_lvis_v1_ds1_val_v1"
+ WHITELISTED_CATEGORIES:
+ "densepose_lvis_v1_ds1_train_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_ds1_val_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ CLASS_TO_MESH_NAME_MAPPING:
+ "0": "bear_4936"
+ "1": "cow_5002"
+ "2": "cat_5001"
+ "3": "dog_5002"
+ "4": "elephant_5002"
+ "5": "giraffe_5002"
+ "6": "horse_5004"
+ "7": "sheep_5004"
+ "8": "zebra_5002"
+SOLVER:
+ MAX_ITER: 4000
+ STEPS: (3000, 3500)
+DENSEPOSE_EVALUATION:
+ EVALUATE_MESH_ALIGNMENT: True
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..03f4d507272b06770def6859558cada8f9038582
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_maskonly_24k.yaml
@@ -0,0 +1,118 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_HEADS:
+ NUM_CLASSES: 9
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBED_LOSS_WEIGHT: 0.0
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
+ EMBEDDERS:
+ "cat_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_7466_256.pkl"
+ "dog_7466":
+ TYPE: vertex_feature
+ NUM_VERTICES: 7466
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_7466_256.pkl"
+ "sheep_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
+ "horse_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
+ "zebra_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
+ "giraffe_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
+ "elephant_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
+ "cow_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
+ "bear_4936":
+ TYPE: vertex_feature
+ NUM_VERTICES: 4936
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_lvis_v1_ds2_train_v1"
+ TEST:
+ - "densepose_lvis_v1_ds2_val_v1"
+ WHITELISTED_CATEGORIES:
+ "densepose_lvis_v1_ds2_train_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_ds2_val_v1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ CLASS_TO_MESH_NAME_MAPPING:
+ "0": "bear_4936"
+ "1": "cow_5002"
+ "2": "cat_7466"
+ "3": "dog_7466"
+ "4": "elephant_5002"
+ "5": "giraffe_5002"
+ "6": "horse_5004"
+ "7": "sheep_5004"
+ "8": "zebra_5002"
+SOLVER:
+ MAX_ITER: 24000
+ STEPS: (20000, 22000)
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_chimps_finetune_4k.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_chimps_finetune_4k.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8311cccbede5c449c172c2a2b47cee70840e71e2
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_chimps_finetune_4k.yaml
@@ -0,0 +1,29 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_s1x/250533982/model_final_2c4512.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ GEODESIC_DIST_GAUSS_SIGMA: 0.1
+ EMBEDDERS:
+ "chimp_5029":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5029
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_chimp_5029_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_chimps_cse_train"
+ TEST:
+ - "densepose_chimps_cse_val"
+ CLASS_TO_MESH_NAME_MAPPING:
+ "0": "chimp_5029"
+SOLVER:
+ MAX_ITER: 4000
+ STEPS: (3000, 3500)
diff --git a/configs/cse/densepose_rcnn_R_50_FPN_soft_s1x.yaml b/configs/cse/densepose_rcnn_R_50_FPN_soft_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6238b1e026bd9fcf91634caffc7233c50e7fde51
--- /dev/null
+++ b/configs/cse/densepose_rcnn_R_50_FPN_soft_s1x.yaml
@@ -0,0 +1,12 @@
+_BASE_: "Base-DensePose-RCNN-FPN-Human.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_101_FPN_DL_WC1M_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_DL_WC1M_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e9838e958e6d2cf4acbae2fdbe89e735c727f06e
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_DL_WC1M_s1x.yaml
@@ -0,0 +1,18 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_101_FPN_DL_WC1_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_DL_WC1_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..23e048fabf55bec75e616c5c3234dc14a88aae7f
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_DL_WC1_s1x.yaml
@@ -0,0 +1,16 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_101_FPN_DL_WC2M_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_DL_WC2M_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8fe902cf4632865fa968a271f5f38dcd9251249f
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_DL_WC2M_s1x.yaml
@@ -0,0 +1,18 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "indep_aniso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_101_FPN_DL_WC2_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_DL_WC2_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..3788a4fb3dfee8e12233516362c6491fb680b31a
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_DL_WC2_s1x.yaml
@@ -0,0 +1,16 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "indep_aniso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_101_FPN_DL_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_DL_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..17c6e7d498924ca8a43ff05de0bed71b59b39d9b
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_DL_s1x.yaml
@@ -0,0 +1,10 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_101_FPN_WC1M_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_WC1M_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ad74310cda71d707eddb99c17a47ff7732d5a22c
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_WC1M_s1x.yaml
@@ -0,0 +1,18 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/densepose_rcnn_R_101_FPN_WC1_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_WC1_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..b91094e445fa7ae11d7efacd8e7d53f04991dd04
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_WC1_s1x.yaml
@@ -0,0 +1,16 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/densepose_rcnn_R_101_FPN_WC2M_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_WC2M_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..4547bd172e67fa95e26ceaa72eaa323f7e238cad
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_WC2M_s1x.yaml
@@ -0,0 +1,18 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "indep_aniso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/densepose_rcnn_R_101_FPN_WC2_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_WC2_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..41e14ebaf62de6e8b46c1f8bc87fcdf85daf4dc0
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_WC2_s1x.yaml
@@ -0,0 +1,16 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "indep_aniso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/densepose_rcnn_R_101_FPN_s1x.yaml b/configs/densepose_rcnn_R_101_FPN_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..b3a8436aec504b4c14d9f9fff2907f54b722860d
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_s1x.yaml
@@ -0,0 +1,8 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_101_FPN_s1x_legacy.yaml b/configs/densepose_rcnn_R_101_FPN_s1x_legacy.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..907e66fba785aa2c6706cc30021e654716a2fdcc
--- /dev/null
+++ b/configs/densepose_rcnn_R_101_FPN_s1x_legacy.yaml
@@ -0,0 +1,17 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
+ RESNETS:
+ DEPTH: 101
+ ROI_DENSEPOSE_HEAD:
+ NUM_COARSE_SEGM_CHANNELS: 15
+ POOLER_RESOLUTION: 14
+ HEATMAP_SIZE: 56
+ INDEX_WEIGHTS: 2.0
+ PART_WEIGHTS: 0.3
+ POINT_REGRESSION_WEIGHTS: 0.1
+ DECODER_ON: False
+SOLVER:
+ BASE_LR: 0.002
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_50_FPN_DL_WC1M_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_DL_WC1M_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..09270ef9d95c2f4dc1dfb6782e15f01374bb2faf
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_DL_WC1M_s1x.yaml
@@ -0,0 +1,18 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_50_FPN_DL_WC1_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_DL_WC1_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..498c834de22809c35b006adba44e95aece403a92
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_DL_WC1_s1x.yaml
@@ -0,0 +1,16 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_50_FPN_DL_WC2M_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_DL_WC2M_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..cacee6c0fe3476b0706ba77225a67609f9a67a88
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_DL_WC2M_s1x.yaml
@@ -0,0 +1,18 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "indep_aniso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_50_FPN_DL_WC2_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_DL_WC2_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..1432ed59d082f47a8896e10c638bfe57176dad99
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_DL_WC2_s1x.yaml
@@ -0,0 +1,16 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "indep_aniso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_50_FPN_DL_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_DL_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d81a769457396d20fc30e1671903ad284de536f2
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_DL_s1x.yaml
@@ -0,0 +1,10 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_50_FPN_WC1M_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_WC1M_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..1c3e77676e4fa09cbed781f06cc2c8067051937f
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_WC1M_s1x.yaml
@@ -0,0 +1,20 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ CLIP_TYPE: norm
+ CLIP_VALUE: 100.0
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/densepose_rcnn_R_50_FPN_WC1_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_WC1_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5580d5459b098d59acbeb59e6172e91bf292d860
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_WC1_s1x.yaml
@@ -0,0 +1,16 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/densepose_rcnn_R_50_FPN_WC2M_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_WC2M_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..611c404cb2660a1bcc71098df9042363697ca0ce
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_WC2M_s1x.yaml
@@ -0,0 +1,18 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "indep_aniso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/densepose_rcnn_R_50_FPN_WC2_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_WC2_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5a2d3e51fea69af9a555103f40f52d07a7b73e9e
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_WC2_s1x.yaml
@@ -0,0 +1,16 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "indep_aniso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/densepose_rcnn_R_50_FPN_s1x.yaml b/configs/densepose_rcnn_R_50_FPN_s1x.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..72f64518b9914dfdbf01d426e04cda9e74574032
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_s1x.yaml
@@ -0,0 +1,8 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+SOLVER:
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/densepose_rcnn_R_50_FPN_s1x_legacy.yaml b/configs/densepose_rcnn_R_50_FPN_s1x_legacy.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5d025103fa374e7007b52a98abe6aa3d2f754763
--- /dev/null
+++ b/configs/densepose_rcnn_R_50_FPN_s1x_legacy.yaml
@@ -0,0 +1,17 @@
+_BASE_: "Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ NUM_COARSE_SEGM_CHANNELS: 15
+ POOLER_RESOLUTION: 14
+ HEATMAP_SIZE: 56
+ INDEX_WEIGHTS: 2.0
+ PART_WEIGHTS: 0.3
+ POINT_REGRESSION_WEIGHTS: 0.1
+ DECODER_ON: False
+SOLVER:
+ BASE_LR: 0.002
+ MAX_ITER: 130000
+ STEPS: (100000, 120000)
diff --git a/configs/evolution/Base-RCNN-FPN-Atop10P_CA.yaml b/configs/evolution/Base-RCNN-FPN-Atop10P_CA.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..3dcb98804478318a532432205b6d25b7cd26777b
--- /dev/null
+++ b/configs/evolution/Base-RCNN-FPN-Atop10P_CA.yaml
@@ -0,0 +1,91 @@
+MODEL:
+ META_ARCHITECTURE: "GeneralizedRCNN"
+ BACKBONE:
+ NAME: "build_resnet_fpn_backbone"
+ RESNETS:
+ OUT_FEATURES: ["res2", "res3", "res4", "res5"]
+ FPN:
+ IN_FEATURES: ["res2", "res3", "res4", "res5"]
+ ANCHOR_GENERATOR:
+ SIZES: [[32], [64], [128], [256], [512]] # One size for each in feature map
+ ASPECT_RATIOS: [[0.5, 1.0, 2.0]] # Three aspect ratios (same for all in feature maps)
+ RPN:
+ IN_FEATURES: ["p2", "p3", "p4", "p5", "p6"]
+ PRE_NMS_TOPK_TRAIN: 2000 # Per FPN level
+ PRE_NMS_TOPK_TEST: 1000 # Per FPN level
+ # Detectron1 uses 2000 proposals per-batch,
+ # (See "modeling/rpn/rpn_outputs.py" for details of this legacy issue)
+ # which is approximately 1000 proposals per-image since the default batch size for FPN is 2.
+ POST_NMS_TOPK_TRAIN: 1000
+ POST_NMS_TOPK_TEST: 1000
+ ROI_HEADS:
+ NAME: "StandardROIHeads"
+ IN_FEATURES: ["p2", "p3", "p4", "p5"]
+ NUM_CLASSES: 1
+ ROI_BOX_HEAD:
+ NAME: "FastRCNNConvFCHead"
+ NUM_FC: 2
+ POOLER_RESOLUTION: 7
+ ROI_MASK_HEAD:
+ NAME: "MaskRCNNConvUpsampleHead"
+ NUM_CONV: 4
+ POOLER_RESOLUTION: 14
+DATASETS:
+ TRAIN: ("base_coco_2017_train", "densepose_coco_2014_train")
+ TEST: ("densepose_chimps",)
+ CATEGORY_MAPS:
+ "base_coco_2017_train":
+ "16": 1 # bird -> person
+ "17": 1 # cat -> person
+ "18": 1 # dog -> person
+ "19": 1 # horse -> person
+ "20": 1 # sheep -> person
+ "21": 1 # cow -> person
+ "22": 1 # elephant -> person
+ "23": 1 # bear -> person
+ "24": 1 # zebra -> person
+ "25": 1 # girafe -> person
+ "base_coco_2017_val":
+ "16": 1 # bird -> person
+ "17": 1 # cat -> person
+ "18": 1 # dog -> person
+ "19": 1 # horse -> person
+ "20": 1 # sheep -> person
+ "21": 1 # cow -> person
+ "22": 1 # elephant -> person
+ "23": 1 # bear -> person
+ "24": 1 # zebra -> person
+ "25": 1 # girafe -> person
+ WHITELISTED_CATEGORIES:
+ "base_coco_2017_train":
+ - 1 # person
+ - 16 # bird
+ - 17 # cat
+ - 18 # dog
+ - 19 # horse
+ - 20 # sheep
+ - 21 # cow
+ - 22 # elephant
+ - 23 # bear
+ - 24 # zebra
+ - 25 # girafe
+ "base_coco_2017_val":
+ - 1 # person
+ - 16 # bird
+ - 17 # cat
+ - 18 # dog
+ - 19 # horse
+ - 20 # sheep
+ - 21 # cow
+ - 22 # elephant
+ - 23 # bear
+ - 24 # zebra
+ - 25 # girafe
+SOLVER:
+ IMS_PER_BATCH: 16
+ BASE_LR: 0.02
+ STEPS: (60000, 80000)
+ MAX_ITER: 90000
+INPUT:
+ MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800)
+VERSION: 2
diff --git a/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA.yaml b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..b136301bd97193137196b505815ffb208d2c410d
--- /dev/null
+++ b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA.yaml
@@ -0,0 +1,28 @@
+_BASE_: "Base-RCNN-FPN-Atop10P_CA.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ DENSEPOSE_ON: True
+ ROI_HEADS:
+ NAME: "DensePoseROIHeads"
+ IN_FEATURES: ["p2", "p3", "p4", "p5"]
+ NUM_CLASSES: 1
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+ POOLER_TYPE: "ROIAlign"
+ NUM_COARSE_SEGM_CHANNELS: 2
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+ INDEX_WEIGHTS: 1.0
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ WARMUP_FACTOR: 0.025
+ MAX_ITER: 270000
+ STEPS: (210000, 250000)
diff --git a/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_coarsesegm.yaml b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_coarsesegm.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c07653e23a1d9999d2e2aeb7a2c363b15acaacf2
--- /dev/null
+++ b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_coarsesegm.yaml
@@ -0,0 +1,56 @@
+_BASE_: "Base-RCNN-FPN-Atop10P_CA.yaml"
+MODEL:
+ WEIGHTS: https://dl.fbaipublicfiles.com/densepose/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA/217578784/model_final_9fe1cc.pkl
+ RESNETS:
+ DEPTH: 50
+ DENSEPOSE_ON: True
+ ROI_HEADS:
+ NAME: "DensePoseROIHeads"
+ IN_FEATURES: ["p2", "p3", "p4", "p5"]
+ NUM_CLASSES: 1
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+ POOLER_TYPE: "ROIAlign"
+ NUM_COARSE_SEGM_CHANNELS: 2
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+BOOTSTRAP_DATASETS:
+ - DATASET: "chimpnsee"
+ RATIO: 1.0
+ IMAGE_LOADER:
+ TYPE: "video_keyframe"
+ SELECT:
+ STRATEGY: "random_k"
+ NUM_IMAGES: 4
+ TRANSFORM:
+ TYPE: "resize"
+ MIN_SIZE: 800
+ MAX_SIZE: 1333
+ BATCH_SIZE: 8
+ NUM_WORKERS: 1
+ INFERENCE:
+ INPUT_BATCH_SIZE: 1
+ OUTPUT_BATCH_SIZE: 1
+ DATA_SAMPLER:
+ # supported types:
+ # densepose_uniform
+ # densepose_UV_confidence
+ # densepose_fine_segm_confidence
+ # densepose_coarse_segm_confidence
+ TYPE: "densepose_coarse_segm_confidence"
+ COUNT_PER_CLASS: 8
+ FILTER:
+ TYPE: "detection_score"
+ MIN_VALUE: 0.8
+BOOTSTRAP_MODEL:
+ WEIGHTS: https://dl.fbaipublicfiles.com/densepose/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA/217578784/model_final_9fe1cc.pkl
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 270000
+ STEPS: (210000, 250000)
diff --git a/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_finesegm.yaml b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_finesegm.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..0f24376b0da6ffed21336b5277112f66b525dee3
--- /dev/null
+++ b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_finesegm.yaml
@@ -0,0 +1,56 @@
+_BASE_: "Base-RCNN-FPN-Atop10P_CA.yaml"
+MODEL:
+ WEIGHTS: https://dl.fbaipublicfiles.com/densepose/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA/217578784/model_final_9fe1cc.pkl
+ RESNETS:
+ DEPTH: 50
+ DENSEPOSE_ON: True
+ ROI_HEADS:
+ NAME: "DensePoseROIHeads"
+ IN_FEATURES: ["p2", "p3", "p4", "p5"]
+ NUM_CLASSES: 1
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+ POOLER_TYPE: "ROIAlign"
+ NUM_COARSE_SEGM_CHANNELS: 2
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+BOOTSTRAP_DATASETS:
+ - DATASET: "chimpnsee"
+ RATIO: 1.0
+ IMAGE_LOADER:
+ TYPE: "video_keyframe"
+ SELECT:
+ STRATEGY: "random_k"
+ NUM_IMAGES: 4
+ TRANSFORM:
+ TYPE: "resize"
+ MIN_SIZE: 800
+ MAX_SIZE: 1333
+ BATCH_SIZE: 8
+ NUM_WORKERS: 1
+ INFERENCE:
+ INPUT_BATCH_SIZE: 1
+ OUTPUT_BATCH_SIZE: 1
+ DATA_SAMPLER:
+ # supported types:
+ # densepose_uniform
+ # densepose_UV_confidence
+ # densepose_fine_segm_confidence
+ # densepose_coarse_segm_confidence
+ TYPE: "densepose_fine_segm_confidence"
+ COUNT_PER_CLASS: 8
+ FILTER:
+ TYPE: "detection_score"
+ MIN_VALUE: 0.8
+BOOTSTRAP_MODEL:
+ WEIGHTS: https://dl.fbaipublicfiles.com/densepose/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA/217578784/model_final_9fe1cc.pkl
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 270000
+ STEPS: (210000, 250000)
diff --git a/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_uniform.yaml b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_uniform.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..33dd093f00b3d4c2c5943ef29200b6834c2181b3
--- /dev/null
+++ b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_uniform.yaml
@@ -0,0 +1,56 @@
+_BASE_: "Base-RCNN-FPN-Atop10P_CA.yaml"
+MODEL:
+ WEIGHTS: https://dl.fbaipublicfiles.com/densepose/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA/217578784/model_final_9fe1cc.pkl
+ RESNETS:
+ DEPTH: 50
+ DENSEPOSE_ON: True
+ ROI_HEADS:
+ NAME: "DensePoseROIHeads"
+ IN_FEATURES: ["p2", "p3", "p4", "p5"]
+ NUM_CLASSES: 1
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+ POOLER_TYPE: "ROIAlign"
+ NUM_COARSE_SEGM_CHANNELS: 2
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+BOOTSTRAP_DATASETS:
+ - DATASET: "chimpnsee"
+ RATIO: 1.0
+ IMAGE_LOADER:
+ TYPE: "video_keyframe"
+ SELECT:
+ STRATEGY: "random_k"
+ NUM_IMAGES: 4
+ TRANSFORM:
+ TYPE: "resize"
+ MIN_SIZE: 800
+ MAX_SIZE: 1333
+ BATCH_SIZE: 8
+ NUM_WORKERS: 1
+ INFERENCE:
+ INPUT_BATCH_SIZE: 1
+ OUTPUT_BATCH_SIZE: 1
+ DATA_SAMPLER:
+ # supported types:
+ # densepose_uniform
+ # densepose_UV_confidence
+ # densepose_fine_segm_confidence
+ # densepose_coarse_segm_confidence
+ TYPE: "densepose_uniform"
+ COUNT_PER_CLASS: 8
+ FILTER:
+ TYPE: "detection_score"
+ MIN_VALUE: 0.8
+BOOTSTRAP_MODEL:
+ WEIGHTS: https://dl.fbaipublicfiles.com/densepose/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA/217578784/model_final_9fe1cc.pkl
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 270000
+ STEPS: (210000, 250000)
diff --git a/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_uv.yaml b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_uv.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..66af1c5fdf287f63bcc2669cf07b863e5873079f
--- /dev/null
+++ b/configs/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA_B_uv.yaml
@@ -0,0 +1,56 @@
+_BASE_: "Base-RCNN-FPN-Atop10P_CA.yaml"
+MODEL:
+ WEIGHTS: https://dl.fbaipublicfiles.com/densepose/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA/217578784/model_final_9fe1cc.pkl
+ RESNETS:
+ DEPTH: 50
+ DENSEPOSE_ON: True
+ ROI_HEADS:
+ NAME: "DensePoseROIHeads"
+ IN_FEATURES: ["p2", "p3", "p4", "p5"]
+ NUM_CLASSES: 1
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ SEGM_CONFIDENCE:
+ ENABLED: True
+ POINT_REGRESSION_WEIGHTS: 0.0005
+ POOLER_TYPE: "ROIAlign"
+ NUM_COARSE_SEGM_CHANNELS: 2
+ COARSE_SEGM_TRAINED_BY_MASKS: True
+BOOTSTRAP_DATASETS:
+ - DATASET: "chimpnsee"
+ RATIO: 1.0
+ IMAGE_LOADER:
+ TYPE: "video_keyframe"
+ SELECT:
+ STRATEGY: "random_k"
+ NUM_IMAGES: 4
+ TRANSFORM:
+ TYPE: "resize"
+ MIN_SIZE: 800
+ MAX_SIZE: 1333
+ BATCH_SIZE: 8
+ NUM_WORKERS: 1
+ INFERENCE:
+ INPUT_BATCH_SIZE: 1
+ OUTPUT_BATCH_SIZE: 1
+ DATA_SAMPLER:
+ # supported types:
+ # densepose_uniform
+ # densepose_UV_confidence
+ # densepose_fine_segm_confidence
+ # densepose_coarse_segm_confidence
+ TYPE: "densepose_UV_confidence"
+ COUNT_PER_CLASS: 8
+ FILTER:
+ TYPE: "detection_score"
+ MIN_VALUE: 0.8
+BOOTSTRAP_MODEL:
+ WEIGHTS: https://dl.fbaipublicfiles.com/densepose/evolution/densepose_R_50_FPN_DL_WC1M_3x_Atop10P_CA/217578784/model_final_9fe1cc.pkl
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 270000
+ STEPS: (210000, 250000)
diff --git a/configs/quick_schedules/cse/densepose_rcnn_R_50_FPN_DL_instant_test.yaml b/configs/quick_schedules/cse/densepose_rcnn_R_50_FPN_DL_instant_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..684e72637e35f6cd12c665be57ffbfa49266c50f
--- /dev/null
+++ b/configs/quick_schedules/cse/densepose_rcnn_R_50_FPN_DL_instant_test.yaml
@@ -0,0 +1,11 @@
+_BASE_: "../../cse/Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+DATASETS:
+ TRAIN: ("densepose_coco_2014_minival_100_cse",)
+ TEST: ("densepose_coco_2014_minival_100_cse",)
+SOLVER:
+ MAX_ITER: 40
+ STEPS: (30,)
diff --git a/configs/quick_schedules/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_instant_test.yaml b/configs/quick_schedules/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_instant_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..958a4525e1e8a88cf25a0de24ac9ba7c87f0a802
--- /dev/null
+++ b/configs/quick_schedules/cse/densepose_rcnn_R_50_FPN_soft_animals_finetune_instant_test.yaml
@@ -0,0 +1,126 @@
+_BASE_: "../../cse/Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_HEADS:
+ NUM_CLASSES: 9
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseV1ConvXHead"
+ CSE:
+ EMBED_LOSS_NAME: "SoftEmbeddingLoss"
+ EMBEDDING_DIST_GAUSS_SIGMA: 0.1
+ EMBEDDERS:
+ "cat_5001":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5001
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cat_5001_256.pkl"
+ "dog_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_dog_5002_256.pkl"
+ "sheep_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_sheep_5004_256.pkl"
+ "horse_5004":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5004
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_horse_5004_256.pkl"
+ "zebra_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_zebra_5002_256.pkl"
+ "giraffe_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_giraffe_5002_256.pkl"
+ "elephant_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_elephant_5002_256.pkl"
+ "cow_5002":
+ TYPE: vertex_feature
+ NUM_VERTICES: 5002
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_cow_5002_256.pkl"
+ "bear_4936":
+ TYPE: vertex_feature
+ NUM_VERTICES: 4936
+ FEATURE_DIM: 256
+ FEATURES_TRAINABLE: False
+ IS_TRAINABLE: True
+ INIT_FILE: "https://dl.fbaipublicfiles.com/densepose/data/cse/lbo/phi_bear_4936_256.pkl"
+DATASETS:
+ TRAIN:
+ - "densepose_lvis_v1_train1"
+ - "densepose_lvis_v1_train2"
+ TEST:
+ - "densepose_lvis_v1_val_animals_100"
+ WHITELISTED_CATEGORIES:
+ "densepose_lvis_v1_train1":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_train2":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ "densepose_lvis_v1_val_animals_100":
+ - 943 # sheep
+ - 1202 # zebra
+ - 569 # horse
+ - 496 # giraffe
+ - 422 # elephant
+ - 80 # cow
+ - 76 # bear
+ - 225 # cat
+ - 378 # dog
+ CLASS_TO_MESH_NAME_MAPPING:
+ "0": "bear_4936"
+ "1": "cow_5002"
+ "2": "cat_5001"
+ "3": "dog_5002"
+ "4": "elephant_5002"
+ "5": "giraffe_5002"
+ "6": "horse_5004"
+ "7": "sheep_5004"
+ "8": "zebra_5002"
+SOLVER:
+ MAX_ITER: 40
+ STEPS: (30,)
diff --git a/configs/quick_schedules/densepose_rcnn_HRFPN_HRNet_w32_instant_test.yaml b/configs/quick_schedules/densepose_rcnn_HRFPN_HRNet_w32_instant_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ab67e44beae1e1638dcef8bad2c7190508b3fccf
--- /dev/null
+++ b/configs/quick_schedules/densepose_rcnn_HRFPN_HRNet_w32_instant_test.yaml
@@ -0,0 +1,8 @@
+_BASE_: "../HRNet/densepose_rcnn_HRFPN_HRNet_w32_s1x.yaml"
+DATASETS:
+ TRAIN: ("densepose_coco_2014_minival_100",)
+ TEST: ("densepose_coco_2014_minival_100",)
+SOLVER:
+ MAX_ITER: 40
+ STEPS: (30,)
+ IMS_PER_BATCH: 2
diff --git a/configs/quick_schedules/densepose_rcnn_R_50_FPN_DL_instant_test.yaml b/configs/quick_schedules/densepose_rcnn_R_50_FPN_DL_instant_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e90d0985f7b6d94caf277db51c30a39d16596406
--- /dev/null
+++ b/configs/quick_schedules/densepose_rcnn_R_50_FPN_DL_instant_test.yaml
@@ -0,0 +1,11 @@
+_BASE_: "../Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ ROI_DENSEPOSE_HEAD:
+ NAME: "DensePoseDeepLabHead"
+DATASETS:
+ TRAIN: ("densepose_coco_2014_minival_100",)
+ TEST: ("densepose_coco_2014_minival_100",)
+SOLVER:
+ MAX_ITER: 40
+ STEPS: (30,)
diff --git a/configs/quick_schedules/densepose_rcnn_R_50_FPN_TTA_inference_acc_test.yaml b/configs/quick_schedules/densepose_rcnn_R_50_FPN_TTA_inference_acc_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..368a8e09546ead073fd786df729ca6e795c1ee5a
--- /dev/null
+++ b/configs/quick_schedules/densepose_rcnn_R_50_FPN_TTA_inference_acc_test.yaml
@@ -0,0 +1,13 @@
+_BASE_: "../densepose_rcnn_R_50_FPN_s1x.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/densepose_rcnn_R_50_FPN_s1x/165712039/model_final_162be9.pkl"
+DATASETS:
+ TRAIN: ()
+ TEST: ("densepose_coco_2014_minival_100",)
+TEST:
+ AUG:
+ ENABLED: True
+ MIN_SIZES: (400, 500, 600, 700, 800, 900, 1000, 1100, 1200)
+ MAX_SIZE: 4000
+ FLIP: True
+ EXPECTED_RESULTS: [["bbox_TTA", "AP", 61.74, 0.03], ["densepose_gps_TTA", "AP", 60.22, 0.03], ["densepose_gpsm_TTA", "AP", 63.59, 0.03]]
diff --git a/configs/quick_schedules/densepose_rcnn_R_50_FPN_WC1_instant_test.yaml b/configs/quick_schedules/densepose_rcnn_R_50_FPN_WC1_instant_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..847ef30358eda34e394d19f8960e8699869ff146
--- /dev/null
+++ b/configs/quick_schedules/densepose_rcnn_R_50_FPN_WC1_instant_test.yaml
@@ -0,0 +1,19 @@
+_BASE_: "../Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "iid_iso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+DATASETS:
+ TRAIN: ("densepose_coco_2014_minival_100",)
+ TEST: ("densepose_coco_2014_minival_100",)
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 40
+ STEPS: (30,)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/quick_schedules/densepose_rcnn_R_50_FPN_WC2_instant_test.yaml b/configs/quick_schedules/densepose_rcnn_R_50_FPN_WC2_instant_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..7f93da9d4b73b2eea7d2c1f3c44b79d311ce4a1d
--- /dev/null
+++ b/configs/quick_schedules/densepose_rcnn_R_50_FPN_WC2_instant_test.yaml
@@ -0,0 +1,19 @@
+_BASE_: "../Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ RESNETS:
+ DEPTH: 50
+ ROI_DENSEPOSE_HEAD:
+ UV_CONFIDENCE:
+ ENABLED: True
+ TYPE: "indep_aniso"
+ POINT_REGRESSION_WEIGHTS: 0.0005
+DATASETS:
+ TRAIN: ("densepose_coco_2014_minival_100",)
+ TEST: ("densepose_coco_2014_minival_100",)
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ MAX_ITER: 40
+ STEPS: (30,)
+ WARMUP_FACTOR: 0.025
diff --git a/configs/quick_schedules/densepose_rcnn_R_50_FPN_inference_acc_test.yaml b/configs/quick_schedules/densepose_rcnn_R_50_FPN_inference_acc_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..06ebd5ec2d24f1da144a2c020f353434b90870b3
--- /dev/null
+++ b/configs/quick_schedules/densepose_rcnn_R_50_FPN_inference_acc_test.yaml
@@ -0,0 +1,8 @@
+_BASE_: "../densepose_rcnn_R_50_FPN_s1x.yaml"
+MODEL:
+ WEIGHTS: "https://dl.fbaipublicfiles.com/densepose/densepose_rcnn_R_50_FPN_s1x/165712039/model_final_162be9.pkl"
+DATASETS:
+ TRAIN: ()
+ TEST: ("densepose_coco_2014_minival_100",)
+TEST:
+ EXPECTED_RESULTS: [["bbox", "AP", 59.27, 0.025], ["densepose_gps", "AP", 60.11, 0.02], ["densepose_gpsm", "AP", 64.09, 0.02]]
diff --git a/configs/quick_schedules/densepose_rcnn_R_50_FPN_instant_test.yaml b/configs/quick_schedules/densepose_rcnn_R_50_FPN_instant_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6cfedeae69315e6d19f1b0866d860c9084ed1eef
--- /dev/null
+++ b/configs/quick_schedules/densepose_rcnn_R_50_FPN_instant_test.yaml
@@ -0,0 +1,9 @@
+_BASE_: "../Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+DATASETS:
+ TRAIN: ("densepose_coco_2014_minival_100",)
+ TEST: ("densepose_coco_2014_minival_100",)
+SOLVER:
+ MAX_ITER: 40
+ STEPS: (30,)
diff --git a/configs/quick_schedules/densepose_rcnn_R_50_FPN_training_acc_test.yaml b/configs/quick_schedules/densepose_rcnn_R_50_FPN_training_acc_test.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f9f3ce222239d9e114c303bee9dd1c01215e69ae
--- /dev/null
+++ b/configs/quick_schedules/densepose_rcnn_R_50_FPN_training_acc_test.yaml
@@ -0,0 +1,18 @@
+_BASE_: "../Base-DensePose-RCNN-FPN.yaml"
+MODEL:
+ WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
+ ROI_HEADS:
+ NUM_CLASSES: 1
+DATASETS:
+ TRAIN: ("densepose_coco_2014_minival",)
+ TEST: ("densepose_coco_2014_minival",)
+SOLVER:
+ CLIP_GRADIENTS:
+ ENABLED: True
+ CLIP_TYPE: norm
+ CLIP_VALUE: 1.0
+ MAX_ITER: 6000
+ STEPS: (5500, 5800)
+TEST:
+ EXPECTED_RESULTS: [["bbox", "AP", 76.2477, 1.0], ["densepose_gps", "AP", 79.6090, 1.5], ["densepose_gpsm", "AP", 80.0061, 1.5]]
+