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| # -*- coding: utf-8 -*- | |
| # Copyright (c) Facebook, Inc. and its affiliates. | |
| from detectron2.config import CfgNode as CN | |
| def add_tensormask_config(cfg): | |
| """ | |
| Add config for TensorMask. | |
| """ | |
| cfg.MODEL.TENSOR_MASK = CN() | |
| # Anchor parameters | |
| cfg.MODEL.TENSOR_MASK.IN_FEATURES = ["p2", "p3", "p4", "p5", "p6", "p7"] | |
| # Convolutions to use in the towers | |
| cfg.MODEL.TENSOR_MASK.NUM_CONVS = 4 | |
| # Number of foreground classes. | |
| cfg.MODEL.TENSOR_MASK.NUM_CLASSES = 80 | |
| # Channel size for the classification tower | |
| cfg.MODEL.TENSOR_MASK.CLS_CHANNELS = 256 | |
| cfg.MODEL.TENSOR_MASK.SCORE_THRESH_TEST = 0.05 | |
| # Only the top (1000 * #levels) candidate boxes across all levels are | |
| # considered jointly during test (to improve speed) | |
| cfg.MODEL.TENSOR_MASK.TOPK_CANDIDATES_TEST = 6000 | |
| cfg.MODEL.TENSOR_MASK.NMS_THRESH_TEST = 0.5 | |
| # Box parameters | |
| # Channel size for the box tower | |
| cfg.MODEL.TENSOR_MASK.BBOX_CHANNELS = 128 | |
| # Weights on (dx, dy, dw, dh) | |
| cfg.MODEL.TENSOR_MASK.BBOX_REG_WEIGHTS = (1.5, 1.5, 0.75, 0.75) | |
| # Loss parameters | |
| cfg.MODEL.TENSOR_MASK.FOCAL_LOSS_GAMMA = 3.0 | |
| cfg.MODEL.TENSOR_MASK.FOCAL_LOSS_ALPHA = 0.3 | |
| # Mask parameters | |
| # Channel size for the mask tower | |
| cfg.MODEL.TENSOR_MASK.MASK_CHANNELS = 128 | |
| # Mask loss weight | |
| cfg.MODEL.TENSOR_MASK.MASK_LOSS_WEIGHT = 2.0 | |
| # weight on positive pixels within the mask | |
| cfg.MODEL.TENSOR_MASK.POSITIVE_WEIGHT = 1.5 | |
| # Whether to predict in the aligned representation | |
| cfg.MODEL.TENSOR_MASK.ALIGNED_ON = False | |
| # Whether to use the bipyramid architecture | |
| cfg.MODEL.TENSOR_MASK.BIPYRAMID_ON = False | |