+
−import argparse
+
−import warnings
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−
+
−import giatools.io
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−import numpy as np
+
−import scipy
+
−import skimage.draw
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−import skimage.io
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−from skimage.measure import regionprops
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−
+
−# 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).
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−
+
−
+
−def split_labelmap(labelmap, outputfile):
+
−
+
−    # Information from the label map.
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−    label_img = giatools.io.imread(labelmap)
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−    xtot, ytot = label_img.shape
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−    props = regionprops(label_img)
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−    N = len(props)
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−
+
−    # Creating the backgrounds.
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−    background = np.zeros([xtot, ytot], 'uint8')
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−    overlap = np.zeros([N, xtot, ytot], 'uint8')
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−    compstruct = scipy.ndimage.generate_binary_structure(2, 2)  # Mask for image dilation.
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−
+
−    i = 0
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−    for cell in props:
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−        cell_image = cell.image.astype('uint8')
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−
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−        # Replace the background area corresponding to the bounding box with the image representing the cell.
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−        background[int(cell.bbox[0]):int(cell.bbox[2]), int(cell.bbox[1]):int(cell.bbox[3])] += cell_image
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−        overlap[i][int(cell.bbox[0]):int(cell.bbox[2]), int(cell.bbox[1]):int(cell.bbox[3])] = cell_image
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−
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−        # In the overlap array, dilate the cell in all directions.
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−        overlap[i] = scipy.ndimage.binary_dilation(
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−            overlap[i], structure=compstruct).astype(overlap[i].dtype)
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−
+
−        i += 1
+
−
+
−    if len(props) > 1:
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−        # Sum together the overlap.
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−        total_overlap = sum(overlap)
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−
+
−        # Wherever the overlap is greater than 1 replace that point with zero in the final image.
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−        for x in range(xtot):
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−            for y in range(ytot):
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−                if total_overlap[x, y] > 1:
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−                    background[x, y] = 0
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−
+
−    # Force the image into 8-bit.
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−    result = skimage.util.img_as_ubyte(background)
+
−
+
−    # Save image
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−    with warnings.catch_warnings():
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−        warnings.simplefilter("ignore")
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−        skimage.io.imsave(outputfile, result, plugin="tifffile")
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−
+
−    return None
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−
+
−
+
−# To run from command line.
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−if __name__ == "__main__":
+
−    parser = argparse.ArgumentParser()
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−    parser.add_argument('labelmap',
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−                        help='Label map image.')
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−    parser.add_argument('outputfile',
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−                        help='Output file. Without extension (although it corrects if you '
+
−                             'add it; will always return a .tif')
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−
+
−    args = parser.parse_args()
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−    split_labelmap(args.labelmap, args.outputfile)