69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
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# coding=utf-8
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# Copyright 2024 The HuggingFace Inc. team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import functools
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from dataclasses import dataclass
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from .image_processing_utils import BaseImageProcessor
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from .utils.import_utils import is_torchvision_available
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if is_torchvision_available():
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from torchvision.transforms import Compose
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@dataclass(frozen=True)
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class SizeDict:
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"""
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Hashable dictionary to store image size information.
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"""
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height: int = None
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width: int = None
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longest_edge: int = None
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shortest_edge: int = None
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max_height: int = None
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max_width: int = None
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def __getitem__(self, key):
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if hasattr(self, key):
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return getattr(self, key)
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raise KeyError(f"Key {key} not found in SizeDict.")
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class BaseImageProcessorFast(BaseImageProcessor):
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_transform_params = None
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def _build_transforms(self, **kwargs) -> "Compose":
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"""
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Given the input settings e.g. do_resize, build the image transforms.
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"""
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raise NotImplementedError
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def _validate_params(self, **kwargs) -> None:
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for k, v in kwargs.items():
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if k not in self._transform_params:
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raise ValueError(f"Invalid transform parameter {k}={v}.")
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@functools.lru_cache(maxsize=1)
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def get_transforms(self, **kwargs) -> "Compose":
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self._validate_params(**kwargs)
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return self._build_transforms(**kwargs)
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def to_dict(self):
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encoder_dict = super().to_dict()
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encoder_dict.pop("_transform_params", None)
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return encoder_dict
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