annotate slice_image.py @ 2:f312d414f234 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/slice_image/ commit 2286a6c9da88596349ed9d967c51541409c0a7bf
author imgteam
date Mon, 13 Nov 2023 22:12:22 +0000
parents 8856a7c85e4c
children 1faa7e3c94ff
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aacfbd7c4af6 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/slice_image/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581
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1 import argparse
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2 import os.path
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3 import random
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4 import warnings
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6 import numpy as np
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7 import skimage.feature
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8 import skimage.io
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9 import skimage.util
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12 def slice_image(input_file, out_folder, label=None, label_out_folder=None, window_size=64,
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13 stride=1, bg_thresh=1, limit_slices=False, n_thresh=5000, seed=None):
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14 # TODO NOT Implemented:process labels
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15 # --> label and label_out_folder useless so far
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17 # primarily for testing purposes:
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18 if seed is not None:
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19 random.seed(seed)
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21 img_raw = skimage.io.imread(input_file)
aacfbd7c4af6 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/slice_image/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581
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22 if len(img_raw.shape) == 2:
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23 img_raw = np.expand_dims(img_raw, 3)
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24
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25 with warnings.catch_warnings(): # ignore FutureWarning
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26 warnings.simplefilter("ignore")
aacfbd7c4af6 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/slice_image/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581
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27 patches_raw = skimage.util.view_as_windows(img_raw, (window_size, window_size, img_raw.shape[2]), step=stride)
aacfbd7c4af6 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/slice_image/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581
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28 patches_raw = patches_raw.reshape([-1, window_size, window_size, img_raw.shape[2]])
aacfbd7c4af6 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/slice_image/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581
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29
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30 new_path = os.path.join(out_folder, "%d.tiff")
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f312d414f234 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/slice_image/ commit 2286a6c9da88596349ed9d967c51541409c0a7bf
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32 # samples for thresholding the amount of slices
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33 sample = random.sample(range(patches_raw.shape[0]), n_thresh)
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35 for i in range(0, patches_raw.shape[0]):
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36 # TODO improve
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37 sum_image = np.sum(patches_raw[i], 2) / img_raw.shape[2]
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39 if bg_thresh > 0:
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40 sum_image = skimage.util.img_as_uint(sum_image)
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41 g = skimage.feature.greycomatrix(sum_image, [1, 2], [0, np.pi / 2], nnormed=True, symmetric=True)
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42 hom = np.var(skimage.feature.greycoprops(g, prop='homogeneity'))
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43 if hom > bg_thresh: # 0.0005
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44 continue
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46 if limit_slices:
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47 if i in sample:
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48 res = skimage.util.img_as_uint(patches_raw[i]) # Attention: precision loss
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49 skimage.io.imsave(new_path % i, res, plugin='tifffile')
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50 else:
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51 res = skimage.util.img_as_uint(patches_raw[i]) # Attention: precision loss
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52 skimage.io.imsave(new_path % i, res, plugin='tifffile')
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53
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55 if __name__ == "__main__":
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56 parser = argparse.ArgumentParser()
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57 parser.add_argument('input_file', type=argparse.FileType('r'), help='input file')
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58 parser.add_argument('out_folder', help='out folder')
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59 parser.add_argument('--label', dest='label_file', default=None, help='auxiliary label file to split in the same way')
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60 parser.add_argument('--label_out_folder', dest='label_out_folder', default=None, help='label out folder')
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61 parser.add_argument('--stride', dest='stride', type=int, default=1, help='applied stride')
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62 parser.add_argument('--window_size', dest='window_size', type=int, default=64, help='size of resulting patches')
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63 parser.add_argument('--bg_thresh', dest='bg_thresh', type=float, default=0, help='skip patches without information using a treshold')
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64 parser.add_argument('--limit_slices', dest='limit_slices', type=bool, default=False, help='limit amount of slices')
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65 parser.add_argument('--n_thresh', dest='n_thresh', type=int, default=5000, help='amount of slices')
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66 parser.add_argument('--seed', dest='seed', type=int, default=None, help='seed for random choice of limited slices')
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67 args = parser.parse_args()
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68
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69 slice_image(args.input_file.name, args.out_folder,
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70 label=args.label_file, label_out_folder=args.label_out_folder,
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71 stride=args.stride, window_size=args.window_size, bg_thresh=args.bg_thresh,
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72 limit_slices=args.limit_slices, n_thresh=args.n_thresh, seed=args.seed)