mirror of
https://github.com/wassname/scikit-image.git
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emmanuelle
55f5103dd8
Modified travis_script.sh to account for the new structure of the gallery Added README.txt files in directories of gallery examples Fixed references to gallery images in user guide pages Fixed broken links
60 lines
1.5 KiB
Python
60 lines
1.5 KiB
Python
"""
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===================
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Label image regions
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===================
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This example shows how to segment an image with image labelling. The following
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steps are applied:
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1. Thresholding with automatic Otsu method
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2. Close small holes with binary closing
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3. Remove artifacts touching image border
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4. Measure image regions to filter small objects
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.patches as mpatches
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from skimage import data
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from skimage.filters import threshold_otsu
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from skimage.segmentation import clear_border
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from skimage.measure import label
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from skimage.morphology import closing, square
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from skimage.measure import regionprops
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from skimage.color import label2rgb
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image = data.coins()[50:-50, 50:-50]
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# apply threshold
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thresh = threshold_otsu(image)
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bw = closing(image > thresh, square(3))
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# remove artifacts connected to image border
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cleared = bw.copy()
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clear_border(cleared)
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# label image regions
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label_image = label(cleared)
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borders = np.logical_xor(bw, cleared)
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label_image[borders] = -1
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image_label_overlay = label2rgb(label_image, image=image)
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fig, ax = plt.subplots(ncols=1, nrows=1, figsize=(6, 6))
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ax.imshow(image_label_overlay)
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for region in regionprops(label_image):
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# skip small images
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if region.area < 100:
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continue
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# draw rectangle around segmented coins
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minr, minc, maxr, maxc = region.bbox
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rect = mpatches.Rectangle((minc, minr), maxc - minc, maxr - minr,
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fill=False, edgecolor='red', linewidth=2)
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ax.add_patch(rect)
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plt.show()
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