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]] +