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8b306b3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | # Copyright (c) 2025 ByteDance Ltd. and/or its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Union
import torch
from PIL import Image
from torchvision.transforms import functional as TVF
class DivisibleCrop:
def __init__(self, factor):
if not isinstance(factor, tuple):
factor = (factor, factor)
self.height_factor, self.width_factor = factor[0], factor[1]
def __call__(self, image: Union[torch.Tensor, Image.Image]):
if isinstance(image, torch.Tensor):
height, width = image.shape[-2:]
elif isinstance(image, Image.Image):
width, height = image.size
else:
raise NotImplementedError
cropped_height = height - (height % self.height_factor)
cropped_width = width - (width % self.width_factor)
image = TVF.center_crop(img=image, output_size=(cropped_height, cropped_width))
return image
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