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import os |
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import argparse |
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import skimage.io |
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import skimage.external.tifffile |
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from multiprocess import Pool |
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from functools import partial |
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from tqdm import tqdm |
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import cv2 |
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try: |
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__import__("frame_field_learning.local_utils") |
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except ImportError: |
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print("ERROR: The frame_field_learning package is not installed! " |
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"Execute script setup.sh to install local dependencies such as frame_field_learning in develop mode.") |
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exit() |
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from lydorn_utils import print_utils |
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def get_args(): |
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argparser = argparse.ArgumentParser(description=__doc__) |
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argparser.add_argument( |
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'--filepath', |
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required=True, |
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type=str, |
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nargs='*', |
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help='Path(s) to tiff seg RGB images to convert to single channel segmentation map (only keep the first channel).') |
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argparser.add_argument( |
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'--out_dirpath', |
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type=str, |
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help='Path to the output directory for the converted images.') |
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args = argparser.parse_args() |
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return args |
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def convert_one(filepath, out_dirpath): |
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image = skimage.io.imread(filepath) |
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gray_image = image[:, :, 0] |
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basename = os.path.basename(filepath) |
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name = basename.split(".")[0] |
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out_filepath = os.path.join(out_dirpath, name + ".png") |
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os.makedirs(os.path.dirname(out_filepath), exist_ok=True) |
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cv2.imwrite(out_filepath, gray_image, [cv2.IMWRITE_PNG_COMPRESSION, 9]) |
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def main(): |
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args = get_args() |
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print_utils.print_info(f"INFO: converting {len(args.filepath)} seg images.") |
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pool = Pool() |
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list(tqdm(pool.imap(partial(convert_one, out_dirpath=args.out_dirpath), args.filepath), desc="RGB to Gray", total=len(args.filepath))) |
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if __name__ == '__main__': |
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main() |
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