56 lines
1.6 KiB
Python
56 lines
1.6 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 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, regionprops
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from skimage.morphology import closing, square
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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 = clear_border(bw)
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# label image regions
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label_image = label(cleared)
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# to make the background transparent, pass the value of `bg_label`,
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# and leave `bg_color` as `None` and `kind` as `overlay`
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image_label_overlay = label2rgb(label_image, image=image, bg_label=0)
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fig, ax = plt.subplots(figsize=(10, 6))
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ax.imshow(image_label_overlay)
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for region in regionprops(label_image):
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# take regions with large enough areas
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if region.area >= 100:
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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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ax.set_axis_off()
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plt.tight_layout()
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plt.show()
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