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69 lines
3.1 KiB
69 lines
3.1 KiB
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. |
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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 os |
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import os.path as osp |
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import argparse |
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from math import ceil |
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from PIL import Image |
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from utils import Raster, Timer |
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@Timer |
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def split_data(image_path, mask_path, block_size, save_folder): |
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if not osp.exists(save_folder): |
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os.makedirs(save_folder) |
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os.makedirs(osp.join(save_folder, "images")) |
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if mask_path is not None: |
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os.makedirs(osp.join(save_folder, "masks")) |
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image_name = image_path.replace("\\", "/").split("/")[-1].split(".")[0] |
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image = Raster(image_path, to_uint8=True) |
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mask = Raster(mask_path) if mask_path is not None else None |
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if image.width != mask.width or image.height != mask.height: |
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raise ValueError("image's shape must equal mask's shape.") |
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rows = ceil(image.height / block_size) |
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cols = ceil(image.width / block_size) |
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total_number = int(rows * cols) |
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for r in range(rows): |
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for c in range(cols): |
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loc_start = (c * block_size, r * block_size) |
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image_title = Image.fromarray(image.getArray( |
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loc_start, (block_size, block_size))).convert("RGB") |
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image_save_path = osp.join(save_folder, "images", ( |
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image_name + "_" + str(r) + "_" + str(c) + ".jpg")) |
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image_title.save(image_save_path, "JPEG") |
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if mask is not None: |
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mask_title = Image.fromarray(mask.getArray( |
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loc_start, (block_size, block_size))).convert("L") |
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mask_save_path = osp.join(save_folder, "masks", ( |
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image_name + "_" + str(r) + "_" + str(c) + ".png")) |
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mask_title.save(mask_save_path, "PNG") |
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print("-- {:d}/{:d} --".format(int(r * cols + c + 1), total_number)) |
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parser = argparse.ArgumentParser(description="input parameters") |
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parser.add_argument("--image_path", type=str, required=True, \ |
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help="The path of big image data.") |
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parser.add_argument("--mask_path", type=str, default=None, \ |
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help="The path of big image label data.") |
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parser.add_argument("--block_size", type=int, default=512, \ |
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help="The size of image block, `512` is the default.") |
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parser.add_argument("--save_folder", type=str, default="dataset", \ |
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help="The folder path to save the results, `dataset` is the default.") |
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if __name__ == "__main__": |
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args = parser.parse_args() |
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split_data(args.image_path, args.mask_path, args.block_size, args.save_folder)
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