Mercurial > repos > imgteam > 2d_auto_threshold

comparison auto_threshold.py @ 1:4853fc2b50bf draft

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planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/2d_auto_threshold/ commit 8a2a5763d1ac38b3c7974bd7c2da4d5c1101a0a9
author imgteam
date Tue, 23 Jul 2019 05:09:26 -0400
parents d4da97f51700
children 81f0cbca04a7
comparison
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0:d4da97f51700 1:4853fc2b50bf
1 import argparse 1 import argparse
2 import numpy as np 2 import numpy as np
3 import os 3 import sys
4 import sys
5 import warnings
6 import skimage.io 4 import skimage.io
7 import skimage.filters 5 import skimage.filters
8 import skimage.util 6 import skimage.util
9 7
10 threshOptions = { 8 threshOptions = {
11 'otsu' : lambda img_raw: skimage.filters.threshold_otsu(img_raw), 9 'otsu': lambda img_raw: skimage.filters.threshold_otsu(img_raw),
12 'gaussian_adaptive' : lambda img_raw: skimage.filters.threshold_local(img_raw.reshape(img_raw.shape[0], img_raw.shape[1]), 3, method='gaussian'), # todo reshape 2d 10 'gaussian_adaptive': lambda img_raw: skimage.filters.threshold_local(img_raw, 3, method='gaussian'),
13 'mean_adaptive' : lambda img_raw: skimage.filters.threshold_local(img_raw.reshape(img_raw.shape[0], img_raw.shape[1]), 3, method='mean'), # todo reshape 2d 11 'mean_adaptive': lambda img_raw: skimage.filters.threshold_local(img_raw, 3, method='mean'),
14 'isodata' : lambda img_raw: skimage.filters.threshold_isodata(img_raw), 12 'isodata': lambda img_raw: skimage.filters.threshold_isodata(img_raw),
15 'li' : lambda img_raw: skimage.filters.threshold_li(img_raw), 13 'li': lambda img_raw: skimage.filters.threshold_li(img_raw),
16 'yen' : lambda img_raw: skimage.filters.threshold_yen(img_raw), 14 'yen': lambda img_raw: skimage.filters.threshold_yen(img_raw),
17 } 15 }
18 16
19 if __name__ == "__main__": 17 if __name__ == "__main__":
20 parser = argparse.ArgumentParser(description='Segment Foci') 18 parser = argparse.ArgumentParser(description='Segment Foci')
21 parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file') 19 parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file')
23 parser.add_argument('thresh_type', choices=threshOptions.keys(), help='thresholding method') 21 parser.add_argument('thresh_type', choices=threshOptions.keys(), help='thresholding method')
24 parser.add_argument('dark_background', default=True, type=bool, help='True if background is dark') 22 parser.add_argument('dark_background', default=True, type=bool, help='True if background is dark')
25 args = parser.parse_args() 23 args = parser.parse_args()
26 24
27 img_in = skimage.io.imread(args.input_file.name) 25 img_in = skimage.io.imread(args.input_file.name)
26 img_in = np.reshape(img_in, [img_in.shape[0], img_in.shape[1]])
28 thresh = threshOptions[args.thresh_type](img_in) 27 thresh = threshOptions[args.thresh_type](img_in)
29 28
30 if args.dark_background: 29 if args.dark_background:
31 res = img_in > thresh 30 res = img_in > thresh
32 else: 31 else:
33 res = img_in <= thresh 32 res = img_in <= thresh
34 33
35 with warnings.catch_warnings(): 34 res = skimage.util.img_as_uint(res)
36 warnings.simplefilter("ignore") 35 skimage.io.imsave(args.out_file.name, res, plugin="tifffile")
37 res = skimage.util.img_as_uint(res)
38 skimage.io.imsave(args.out_file.name, res, plugin="tifffile")