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from typing import Dict, List, Optional, Tuple, Union |
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import torch |
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from mmengine.structures import InstanceData |
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from mmdet3d.structures import Det3DDataSample |
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class NeRFDet3DDataSample(Det3DDataSample): |
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"""A data structure interface inheirted from Det3DDataSample. Some new |
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attributes are added to match the NeRF-Det project. |
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The attributes added in ``NeRFDet3DDataSample`` are divided into two parts: |
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- ``gt_nerf_images`` (InstanceData): Ground truth of the images which |
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will be used in the NeRF branch. |
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- ``gt_nerf_depths`` (InstanceData): Ground truth of the depth images |
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which will be used in the NeRF branch if needed. |
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For more details and examples, please refer to the 'Det3DDataSample' file. |
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""" |
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@property |
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def gt_nerf_images(self) -> InstanceData: |
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return self._gt_nerf_images |
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@gt_nerf_images.setter |
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def gt_nerf_images(self, value: InstanceData) -> None: |
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self.set_field(value, '_gt_nerf_images', dtype=InstanceData) |
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@gt_nerf_images.deleter |
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def gt_nerf_images(self) -> None: |
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del self._gt_nerf_images |
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@property |
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def gt_nerf_depths(self) -> InstanceData: |
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return self._gt_nerf_depths |
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@gt_nerf_depths.setter |
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def gt_nerf_depths(self, value: InstanceData) -> None: |
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self.set_field(value, '_gt_nerf_depths', dtype=InstanceData) |
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@gt_nerf_depths.deleter |
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def gt_nerf_depths(self) -> None: |
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del self._gt_nerf_depths |
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SampleList = List[NeRFDet3DDataSample] |
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OptSampleList = Optional[SampleList] |
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ForwardResults = Union[Dict[str, torch.Tensor], List[NeRFDet3DDataSample], |
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Tuple[torch.Tensor], torch.Tensor] |
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