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from typing import Any, Tuple |
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from detectron2.structures import BitMasks, Boxes |
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from .base import BaseConverter |
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ImageSizeType = Tuple[int, int] |
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class ToMaskConverter(BaseConverter): |
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""" |
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Converts various DensePose predictor outputs to masks |
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in bit mask format (see `BitMasks`). Each DensePose predictor output type |
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has to register its convertion strategy. |
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""" |
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registry = {} |
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dst_type = BitMasks |
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@classmethod |
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def convert( |
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cls, |
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densepose_predictor_outputs: Any, |
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boxes: Boxes, |
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image_size_hw: ImageSizeType, |
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*args, |
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**kwargs |
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) -> BitMasks: |
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""" |
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Convert DensePose predictor outputs to BitMasks using some registered |
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converter. Does recursive lookup for base classes, so there's no need |
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for explicit registration for derived classes. |
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Args: |
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densepose_predictor_outputs: DensePose predictor output to be |
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converted to BitMasks |
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boxes (Boxes): bounding boxes that correspond to the DensePose |
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predictor outputs |
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image_size_hw (tuple [int, int]): image height and width |
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Return: |
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An instance of `BitMasks`. If no suitable converter was found, raises KeyError |
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""" |
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return super(ToMaskConverter, cls).convert( |
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densepose_predictor_outputs, boxes, image_size_hw, *args, **kwargs |
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) |
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