Mercurial > repos > imgteam > binary2labelimage
comparison 2d_split_binaryimage_by_watershed.py @ 4:984358e43242 draft default tip
planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/binary2labelimage/ commit 00199464fa2aa1928a49e2379edf199c3db91533
| author | imgteam |
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| date | Tue, 14 Nov 2023 08:27:27 +0000 |
| parents | |
| children |
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| 3:9bb446db4a1e | 4:984358e43242 |
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| 1 import argparse | |
| 2 import sys | |
| 3 | |
| 4 import skimage.io | |
| 5 import skimage.util | |
| 6 from scipy import ndimage as ndi | |
| 7 from skimage.feature import peak_local_max | |
| 8 from skimage.morphology import watershed | |
| 9 | |
| 10 | |
| 11 if __name__ == "__main__": | |
| 12 parser = argparse.ArgumentParser(description='Split binaryimage by watershed') | |
| 13 parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file') | |
| 14 parser.add_argument('out_file', type=argparse.FileType('w'), default=sys.stdin, help='out file (TIFF)') | |
| 15 parser.add_argument('min_distance', type=int, default=100, help='Minimum distance to next object') | |
| 16 args = parser.parse_args() | |
| 17 | |
| 18 img_in = skimage.io.imread(args.input_file.name) | |
| 19 distance = ndi.distance_transform_edt(img_in) | |
| 20 local_maxi = peak_local_max(distance, | |
| 21 indices=False, | |
| 22 min_distance=args.min_distance, | |
| 23 labels=img_in) | |
| 24 markers = ndi.label(local_maxi)[0] | |
| 25 res = watershed(-distance, markers, mask=img_in) | |
| 26 | |
| 27 res = skimage.util.img_as_uint(res) | |
| 28 skimage.io.imsave(args.out_file.name, res, plugin="tifffile") |