55 lines
1.8 KiB
Python
55 lines
1.8 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 InterpolationMode
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from torchvision.transforms import functional as TVF
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class SideResize:
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def __init__(
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self,
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size: int,
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downsample_only: bool = False,
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interpolation: InterpolationMode = InterpolationMode.BICUBIC,
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):
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self.size = size
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self.downsample_only = downsample_only
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self.interpolation = interpolation
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def __call__(self, image: Union[torch.Tensor, Image.Image]):
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"""
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Args:
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image (PIL Image or Tensor): Image to be scaled.
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Returns:
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PIL Image or Tensor: Rescaled image.
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"""
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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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if self.downsample_only and min(width, height) < self.size:
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# keep original height and width for small pictures.
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size = min(width, height)
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else:
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size = self.size
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return TVF.resize(image, size, self.interpolation)
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