mirror of
https://github.com/facebookresearch/pytorch3d.git
synced 2025-08-03 12:22:49 +08:00
34bbb3ad32
Summary: Applies new import merging and sorting from µsort v1.0. When merging imports, µsort will make a best-effort to move associated comments to match merged elements, but there are known limitations due to the diynamic nature of Python and developer tooling. These changes should not produce any dangerous runtime changes, but may require touch-ups to satisfy linters and other tooling. Note that µsort uses case-insensitive, lexicographical sorting, which results in a different ordering compared to isort. This provides a more consistent sorting order, matching the case-insensitive order used when sorting import statements by module name, and ensures that "frog", "FROG", and "Frog" always sort next to each other. For details on µsort's sorting and merging semantics, see the user guide: https://usort.readthedocs.io/en/stable/guide.html#sorting Reviewed By: bottler Differential Revision: D35553814 fbshipit-source-id: be49bdb6a4c25264ff8d4db3a601f18736d17be1
94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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import contextlib
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import pathlib
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import warnings
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from typing import ContextManager, IO, Optional, Union
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import numpy as np
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import torch
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from iopath.common.file_io import PathManager
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from PIL import Image
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from ..common.datatypes import Device
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@contextlib.contextmanager
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def nullcontext(x):
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"""
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This is just like contextlib.nullcontext but also works in Python 3.6.
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"""
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yield x
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PathOrStr = Union[pathlib.Path, str]
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def _open_file(f, path_manager: PathManager, mode: str = "r") -> ContextManager[IO]:
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if isinstance(f, str):
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f = path_manager.open(f, mode)
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return contextlib.closing(f)
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elif isinstance(f, pathlib.Path):
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f = f.open(mode)
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return contextlib.closing(f)
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else:
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return nullcontext(f)
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def _make_tensor(
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data, cols: int, dtype: torch.dtype, device: Device = "cpu"
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) -> torch.Tensor:
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"""
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Return a 2D tensor with the specified cols and dtype filled with data,
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even when data is empty.
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"""
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if not len(data):
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return torch.zeros((0, cols), dtype=dtype, device=device)
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return torch.tensor(data, dtype=dtype, device=device)
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def _check_faces_indices(
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faces_indices: torch.Tensor, max_index: int, pad_value: Optional[int] = None
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) -> torch.Tensor:
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if pad_value is None:
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mask = torch.ones(faces_indices.shape[:-1]).bool() # Keep all faces
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else:
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# pyre-fixme[16]: `torch.ByteTensor` has no attribute `any`
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mask = faces_indices.ne(pad_value).any(dim=-1)
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if torch.any(faces_indices[mask] >= max_index) or torch.any(
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faces_indices[mask] < 0
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):
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warnings.warn("Faces have invalid indices")
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return faces_indices
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def _read_image(file_name: str, path_manager: PathManager, format=None):
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"""
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Read an image from a file using Pillow.
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Args:
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file_name: image file path.
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path_manager: PathManager for interpreting file_name.
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format: one of ["RGB", "BGR"]
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Returns:
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image: an image of shape (H, W, C).
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"""
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if format not in ["RGB", "BGR"]:
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raise ValueError("format can only be one of [RGB, BGR]; got %s", format)
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with path_manager.open(file_name, "rb") as f:
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# pyre-fixme[6]: Expected `Union[str, typing.BinaryIO]` for 1st param but
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# got `Union[typing.IO[bytes], typing.IO[str]]`.
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image = Image.open(f)
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if format is not None:
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# PIL only supports RGB. First convert to RGB and flip channels
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# below for BGR.
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image = image.convert("RGB")
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image = np.asarray(image).astype(np.float32)
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if format == "BGR":
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image = image[:, :, ::-1]
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return image
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