# HG changeset patch # User imgteam # Date 1699913546 0 # Node ID 9db1c22dbe17794aaaa67b927faffecbdc6df64e # Parent 597b7ef44b05a69b7016ee0a26901bb11b02a52e planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/split_labelmaps/ commit 2286a6c9da88596349ed9d967c51541409c0a7bf diff -r 597b7ef44b05 -r 9db1c22dbe17 split_labelmap.py --- a/split_labelmap.py Sat Feb 09 14:47:34 2019 -0500 +++ b/split_labelmap.py Mon Nov 13 22:12:26 2023 +0000 @@ -1,20 +1,18 @@ +import argparse +import warnings + +import numpy as np +import scipy +import skimage.draw +import skimage.io from imageio import imread as io_imread from skimage.measure import regionprops -import numpy as np -#import matplotlib.pyplot as plt -import scipy -import skimage.io -import skimage.draw -from tifffile import imsave -import os -import argparse -import warnings # split_label_image takes a label image and outputs a similar file with the given name where the labeled # parts of the image that touch (or overlap) are separated by at least 1 pixel (at most 2). -def split_labelmap(labelmap,outputfile): +def split_labelmap(labelmap, outputfile): # Information from the label map. label_img = io_imread(labelmap) @@ -23,17 +21,16 @@ N = len(props) # Creating the backgrounds. - background = np.zeros([xtot,ytot], 'uint8') - overlap = np.zeros([N,xtot,ytot],'uint8') + background = np.zeros([xtot, ytot], 'uint8') + overlap = np.zeros([N, xtot, ytot], 'uint8') compstruct = scipy.ndimage.generate_binary_structure(2, 2) # Mask for image dilation. i = 0 for cell in props: cell_image = cell.image.astype('uint8') - #plt.imshow(cell_image) # Replace the background area corresponding to the bounding box with the image representing the cell. - background[int(cell.bbox[0]):int(cell.bbox[2]),int(cell.bbox[1]):int(cell.bbox[3])] += cell_image + background[int(cell.bbox[0]):int(cell.bbox[2]), int(cell.bbox[1]):int(cell.bbox[3])] += cell_image overlap[i][int(cell.bbox[0]):int(cell.bbox[2]), int(cell.bbox[1]):int(cell.bbox[3])] = cell_image # In the overlap array, dilate the cell in all directions. @@ -45,23 +42,24 @@ if len(props) > 1: # Sum together the overlap. total_overlap = sum(overlap) - + # Wherever the overlap is greater than 1 replace that point with zero in the final image. for x in range(xtot): for y in range(ytot): - if total_overlap[x,y] > 1: - background[x,y] = 0 + if total_overlap[x, y] > 1: + background[x, y] = 0 # Force the image into 8-bit. result = skimage.util.img_as_ubyte(background) # Save image - with warnings.catch_warnings(): + with warnings.catch_warnings(): warnings.simplefilter("ignore") skimage.io.imsave(outputfile, result, plugin="tifffile") return None + # To run from command line. if __name__ == "__main__": parser = argparse.ArgumentParser() diff -r 597b7ef44b05 -r 9db1c22dbe17 split_labelmap.xml --- a/split_labelmap.xml Sat Feb 09 14:47:34 2019 -0500 +++ b/split_labelmap.xml Mon Nov 13 22:12:26 2023 +0000 @@ -1,11 +1,17 @@ - + - + + operation_3443 + + + galaxy_image_analysis + + scikit-image numpy - tifffile + tifffile - +