mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-28 03:03:07 +08:00
Johannes Schönberger
65 lines
1.6 KiB
Python
65 lines
1.6 KiB
Python
"""
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=========================
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Measure region properties
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=========================
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This example shows how to measure properties of labelled image regions.
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"""
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import math
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import matplotlib.pyplot as plt
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import numpy as np
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from skimage.draw import ellipse
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from skimage.morphology import label
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from skimage.measure import regionprops
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from scipy.ndimage import geometric_transform
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ANGLE = 0.2
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def rotate(xy):
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x, y = xy
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out_x = math.cos(ANGLE) * x - math.sin(ANGLE) * y
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out_y = math.sin(ANGLE) * x + math.cos(ANGLE) * y
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return (out_x, out_y)
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image = np.zeros((600, 600), 'int')
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rr, cc = ellipse(300, 350, 100, 220)
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image[rr,cc] = 1
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image = geometric_transform(image, rotate)
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label_img = label(image)
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props = regionprops(label_img, [
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'BoundingBox',
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'Centroid',
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'Orientation',
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'MajorAxisLength',
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'MinorAxisLength'
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])
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plt.imshow(image)
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for prop in props:
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x0 = prop['Centroid'][1]
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y0 = prop['Centroid'][0]
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x1 = x0 + math.cos(prop['Orientation']) * 0.5 * prop['MajorAxisLength']
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y1 = y0 - math.sin(prop['Orientation']) * 0.5 * prop['MajorAxisLength']
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x2 = x0 - math.sin(prop['Orientation']) * 0.5 * prop['MinorAxisLength']
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y2 = y0 - math.cos(prop['Orientation']) * 0.5 * prop['MinorAxisLength']
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plt.plot((x0, x1), (y0, y1), '-r', linewidth=2.5)
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plt.plot((x0, x2), (y0, y2), '-r', linewidth=2.5)
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plt.plot(x0, y0, '.g', markersize=15)
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minr, minc, maxr, maxc = prop['BoundingBox']
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bx = (minc, maxc, maxc, minc, minc)
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by = (minr, minr, maxr, maxr, minr)
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plt.plot(bx, by, '-b', linewidth=2.5)
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plt.gray()
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plt.axis((0, 600, 600, 0))
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plt.show()
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