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73 lines
1.7 KiB
Python
73 lines
1.7 KiB
Python
"""
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Dataset input structures.
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"""
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from dataclasses import dataclass
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from typing import List, Optional
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import torch
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from torchtyping import TensorType
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@dataclass
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class PointCloud:
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"""_summary_"""
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xyz = None
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rgb = None
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@dataclass
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class Semantics:
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"""_summary_"""
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stuff_classes: List[str] = None
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stuff_filenames: List[str] = None
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thing_classes: List[str] = None
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thing_filenames: List[str] = None
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@dataclass
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class SceneBounds:
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"""Data to represent the scene bounds.
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aabb: axis-aligned bounding box
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aabb[0] is the minimum (x,y,z) point. aabb[1] is the maximum (x,y,z) point.
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"""
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aabb: TensorType[2, 3] = None
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@dataclass
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class DatasetInputs:
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"""Dataset inputs for the image dataset and the ray generator.
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Args:
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image_filenames: Filenames for the images.
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...
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"""
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image_filenames: List[str]
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downscale_factor: int = 1
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intrinsics: torch.tensor = None
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camera_to_world: torch.tensor = None
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mask_filenames: List[str] = None
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depth_filenames: List[str] = None
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scene_bounds: SceneBounds = SceneBounds()
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semantics: Semantics = Semantics()
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point_cloud: PointCloud = PointCloud()
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alpha_color: Optional[TensorType[3]] = None
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def check_inputs(self):
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"""Check the inputs to make sure everything is okay."""
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assert self.intrinsics.dtype == torch.float32
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assert self.camera_to_world.dtype == torch.float32
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def save_to_folder_name(self, data_directory: str):
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"""Save the dataset inputs."""
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raise NotImplementedError
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def load_from_folder_name(self, data_directory: str):
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"""Load the saved dataset inputs."""
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raise NotImplementedError
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