comparison slice_image.py @ 0:aacfbd7c4af6 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/slice_image/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581
author imgteam
date Sat, 09 Feb 2019 14:46:50 -0500
parents
children 8856a7c85e4c
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equal deleted inserted replaced
-1:000000000000 0:aacfbd7c4af6
1 import argparse
2 import sys
3 import warnings
4 import numpy as np
5 import random
6 import os.path
7 import skimage.io
8 import skimage.util
9 import skimage.feature
10 from scipy.stats import entropy as scipy_entropy
11
12 def slice_image(input_file, out_folder, label=None, label_out_folder=None, window_size=64,
13 stride=1, bg_thresh=1, limit_slices=False, n_thresh=5000, seed=None):
14 #TODO NOT Implemented:process labels
15 # --> label and label_out_folder useless so far
16
17 # primarily for testing purposes:
18 if seed is not None:
19 random.seed(seed)
20
21 img_raw = skimage.io.imread(input_file)
22 if len(img_raw.shape) == 2:
23 img_raw = np.expand_dims(img_raw, 3)
24
25 with warnings.catch_warnings(): # ignore FutureWarning
26 warnings.simplefilter("ignore")
27 patches_raw = skimage.util.view_as_windows(img_raw, (window_size, window_size, img_raw.shape[2]), step=stride)
28 patches_raw = patches_raw.reshape([-1, window_size, window_size, img_raw.shape[2]])
29
30 new_path = os.path.join(out_folder, "%d.tiff")
31
32 #samples for thresholding the amount of slices
33 sample = random.sample(range(patches_raw.shape[0]), n_thresh)
34
35 for i in range(0, patches_raw.shape[0]):
36 # TODO improve
37 sum_image = np.sum(patches_raw[i], 2)/img_raw.shape[2]
38 total_entr = np.var(sum_image.reshape([-1]))
39
40 if bg_thresh > 0:
41 sum_image = skimage.util.img_as_uint(sum_image)
42 g = skimage.feature.greycomatrix(sum_image, [1,2], [0, np.pi/2], nnormed=True, symmetric=True)
43 hom = np.var(skimage.feature.greycoprops(g, prop='homogeneity'))
44 if hom > bg_thresh: #0.0005
45 continue
46
47 if limit_slices == True:
48 if i in sample:
49 res = skimage.util.img_as_uint(patches_raw[i]) #Attention: precision loss
50 skimage.io.imsave(new_path % i, res, plugin='tifffile')
51 else:
52 res = skimage.util.img_as_uint(patches_raw[i]) #Attention: precision loss
53 skimage.io.imsave(new_path % i, res, plugin='tifffile')
54
55
56 if __name__ == "__main__":
57 parser = argparse.ArgumentParser()
58 parser.add_argument('input_file', type=argparse.FileType('r'), help='input file')
59 parser.add_argument('out_folder', help='out folder')
60 parser.add_argument('--label', dest='label_file', default=None, help='auxiliary label file to split in the same way')
61 parser.add_argument('--label_out_folder', dest='label_out_folder', default=None, help='label out folder')
62 parser.add_argument('--stride', dest='stride', type=int, default=1, help='applied stride')
63 parser.add_argument('--window_size', dest='window_size', type=int, default=64, help='size of resulting patches')
64 parser.add_argument('--bg_thresh', dest='bg_thresh', type=float, default=0, help='skip patches without information using a treshold')
65 parser.add_argument('--limit_slices', dest='limit_slices', type=bool, default=False, help='limit amount of slices')
66 parser.add_argument('--n_thresh', dest='n_thresh', type=int, default=5000, help='amount of slices')
67 parser.add_argument('--seed', dest='seed', type=int, default=None, help='seed for random choice of limited slices')
68 args = parser.parse_args()
69
70 slice_image(args.input_file.name, args.out_folder,
71 label=args.label_file, label_out_folder=args.label_out_folder,
72 stride=args.stride, window_size=args.window_size, bg_thresh=args.bg_thresh,
73 limit_slices=args.limit_slices, n_thresh=args.n_thresh, seed=args.seed)