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_BASE_: "../Base-RCNN-FPN.yaml"
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MODEL:
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KEYPOINT_ON: True
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ROI_HEADS:
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NUM_CLASSES: 1
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ROI_BOX_HEAD:
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SMOOTH_L1_BETA: 0.5 # Keypoint AP degrades (though box AP improves) when using plain L1 loss
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RPN:
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# Detectron1 uses 2000 proposals per-batch, but this option is per-image in detectron2.
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# 1000 proposals per-image is found to hurt box AP.
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# Therefore we increase it to 1500 per-image.
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POST_NMS_TOPK_TRAIN: 1500
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DATASETS:
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TRAIN: ("keypoints_coco_2017_train",)
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TEST: ("keypoints_coco_2017_val",)
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_BASE_: "Base-Keypoint-RCNN-FPN.yaml"
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MODEL:
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WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl"
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RESNETS:
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DEPTH: 101
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SOLVER:
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STEPS: (210000, 250000)
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MAX_ITER: 270000
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_BASE_: "Base-Keypoint-RCNN-FPN.yaml"
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MODEL:
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WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
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RESNETS:
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DEPTH: 50
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_BASE_: "Base-Keypoint-RCNN-FPN.yaml"
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MODEL:
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WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
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RESNETS:
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DEPTH: 50
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SOLVER:
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STEPS: (210000, 250000)
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MAX_ITER: 270000
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_BASE_: "Base-Keypoint-RCNN-FPN.yaml"
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MODEL:
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WEIGHTS: "detectron2://ImageNetPretrained/FAIR/X-101-32x8d.pkl"
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PIXEL_STD: [57.375, 57.120, 58.395]
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RESNETS:
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STRIDE_IN_1X1: False # this is a C2 model
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NUM_GROUPS: 32
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WIDTH_PER_GROUP: 8
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DEPTH: 101
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SOLVER:
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STEPS: (210000, 250000)
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MAX_ITER: 270000
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