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VERSION: 2
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MODEL:
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META_ARCHITECTURE: "GeneralizedRCNN"
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BACKBONE:
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NAME: "build_resnet_fpn_backbone"
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RESNETS:
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OUT_FEATURES: ["res2", "res3", "res4", "res5"]
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FPN:
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IN_FEATURES: ["res2", "res3", "res4", "res5"]
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ANCHOR_GENERATOR:
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SIZES: [[32], [64], [128], [256], [512]]
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ASPECT_RATIOS: [[0.5, 1.0, 2.0]]
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RPN:
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IN_FEATURES: ["p2", "p3", "p4", "p5", "p6"]
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PRE_NMS_TOPK_TRAIN: 2000
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PRE_NMS_TOPK_TEST: 1000
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POST_NMS_TOPK_TRAIN: 1000
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POST_NMS_TOPK_TEST: 1000
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DENSEPOSE_ON: True
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ROI_HEADS:
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NAME: "DensePoseROIHeads"
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IN_FEATURES: ["p2", "p3", "p4", "p5"]
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NUM_CLASSES: 1
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ROI_BOX_HEAD:
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NAME: "FastRCNNConvFCHead"
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NUM_FC: 2
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POOLER_RESOLUTION: 7
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POOLER_SAMPLING_RATIO: 2
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POOLER_TYPE: "ROIAlign"
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ROI_DENSEPOSE_HEAD:
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NAME: "DensePoseV1ConvXHead"
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POOLER_TYPE: "ROIAlign"
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NUM_COARSE_SEGM_CHANNELS: 2
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DATASETS:
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TRAIN: ("densepose_coco_2014_train", "densepose_coco_2014_valminusminival")
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TEST: ("densepose_coco_2014_minival",)
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SOLVER:
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IMS_PER_BATCH: 16
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BASE_LR: 0.01
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STEPS: (60000, 80000)
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MAX_ITER: 90000
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WARMUP_FACTOR: 0.1
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INPUT:
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MIN_SIZE_TRAIN: (640, 672, 704, 736, 768, 800) |