# HG changeset patch # User imgteam # Date 1699913542 0 # Node ID f312d414f234a167c5d5a86ca24c492817d6f724 # Parent 8856a7c85e4c8cdb4b968b73fe7648469c143d6d planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/slice_image/ commit 2286a6c9da88596349ed9d967c51541409c0a7bf diff -r 8856a7c85e4c -r f312d414f234 slice_image.py --- a/slice_image.py Wed Dec 18 05:03:25 2019 -0500 +++ b/slice_image.py Mon Nov 13 22:12:22 2023 +0000 @@ -1,17 +1,17 @@ import argparse -import sys +import os.path +import random import warnings + import numpy as np -import random -import os.path +import skimage.feature import skimage.io import skimage.util -import skimage.feature -from scipy.stats import entropy as scipy_entropy - -def slice_image(input_file, out_folder, label=None, label_out_folder=None, window_size=64, + + +def slice_image(input_file, out_folder, label=None, label_out_folder=None, window_size=64, stride=1, bg_thresh=1, limit_slices=False, n_thresh=5000, seed=None): - #TODO NOT Implemented:process labels + # TODO NOT Implemented:process labels # --> label and label_out_folder useless so far # primarily for testing purposes: @@ -22,36 +22,35 @@ if len(img_raw.shape) == 2: img_raw = np.expand_dims(img_raw, 3) - with warnings.catch_warnings(): # ignore FutureWarning + with warnings.catch_warnings(): # ignore FutureWarning warnings.simplefilter("ignore") patches_raw = skimage.util.view_as_windows(img_raw, (window_size, window_size, img_raw.shape[2]), step=stride) patches_raw = patches_raw.reshape([-1, window_size, window_size, img_raw.shape[2]]) - new_path = os.path.join(out_folder, "%d.tiff") - - #samples for thresholding the amount of slices + new_path = os.path.join(out_folder, "%d.tiff") + + # samples for thresholding the amount of slices sample = random.sample(range(patches_raw.shape[0]), n_thresh) for i in range(0, patches_raw.shape[0]): # TODO improve - sum_image = np.sum(patches_raw[i], 2)/img_raw.shape[2] - total_entr = np.var(sum_image.reshape([-1])) + sum_image = np.sum(patches_raw[i], 2) / img_raw.shape[2] if bg_thresh > 0: sum_image = skimage.util.img_as_uint(sum_image) - g = skimage.feature.greycomatrix(sum_image, [1,2], [0, np.pi/2], nnormed=True, symmetric=True) + g = skimage.feature.greycomatrix(sum_image, [1, 2], [0, np.pi / 2], nnormed=True, symmetric=True) hom = np.var(skimage.feature.greycoprops(g, prop='homogeneity')) - if hom > bg_thresh: #0.0005 + if hom > bg_thresh: # 0.0005 continue - - if limit_slices == True: + + if limit_slices: if i in sample: - res = skimage.util.img_as_uint(patches_raw[i]) #Attention: precision loss + res = skimage.util.img_as_uint(patches_raw[i]) # Attention: precision loss skimage.io.imsave(new_path % i, res, plugin='tifffile') else: - res = skimage.util.img_as_uint(patches_raw[i]) #Attention: precision loss - skimage.io.imsave(new_path % i, res, plugin='tifffile') - + res = skimage.util.img_as_uint(patches_raw[i]) # Attention: precision loss + skimage.io.imsave(new_path % i, res, plugin='tifffile') + if __name__ == "__main__": parser = argparse.ArgumentParser() @@ -69,5 +68,5 @@ slice_image(args.input_file.name, args.out_folder, label=args.label_file, label_out_folder=args.label_out_folder, - stride=args.stride, window_size=args.window_size, bg_thresh=args.bg_thresh, + stride=args.stride, window_size=args.window_size, bg_thresh=args.bg_thresh, limit_slices=args.limit_slices, n_thresh=args.n_thresh, seed=args.seed) diff -r 8856a7c85e4c -r f312d414f234 slice_image.xml --- a/slice_image.xml Wed Dec 18 05:03:25 2019 -0500 +++ b/slice_image.xml Mon Nov 13 22:12:22 2023 +0000 @@ -1,5 +1,11 @@ - - into smaller patches + + + + operation_3443 + + + galaxy_image_analysis + scikit-image numpy