wehub-resource-sync
40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
# Copyright (c) 2025 ByteDance Ltd. and/or its affiliates.
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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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from typing import Union
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import torch
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from PIL import Image
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from torchvision.transforms import functional as TVF
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class DivisibleCrop:
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def __init__(self, factor):
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if not isinstance(factor, tuple):
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factor = (factor, factor)
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self.height_factor, self.width_factor = factor[0], factor[1]
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def __call__(self, image: Union[torch.Tensor, Image.Image]):
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if isinstance(image, torch.Tensor):
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height, width = image.shape[-2:]
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elif isinstance(image, Image.Image):
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width, height = image.size
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else:
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raise NotImplementedError
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cropped_height = height - (height % self.height_factor)
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cropped_width = width - (width % self.width_factor)
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image = TVF.center_crop(img=image, output_size=(cropped_height, cropped_width))
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return image
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