80 lines
2.5 KiB
Python
80 lines
2.5 KiB
Python
"""
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==================================
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Approximate and subdivide polygons
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==================================
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This example shows how to approximate (Douglas-Peucker algorithm) and subdivide
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(B-Splines) polygonal chains.
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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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from skimage.draw import ellipse
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from skimage.measure import find_contours, approximate_polygon, \
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subdivide_polygon
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hand = np.array([[1.64516129, 1.16145833],
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[1.64516129, 1.59375],
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[1.35080645, 1.921875],
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[1.375, 2.18229167],
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[1.68548387, 1.9375],
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[1.60887097, 2.55208333],
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[1.68548387, 2.69791667],
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[1.76209677, 2.56770833],
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[1.83064516, 1.97395833],
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[1.89516129, 2.75],
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[1.9516129, 2.84895833],
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[2.01209677, 2.76041667],
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[1.99193548, 1.99479167],
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[2.11290323, 2.63020833],
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[2.2016129, 2.734375],
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[2.25403226, 2.60416667],
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[2.14919355, 1.953125],
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[2.30645161, 2.36979167],
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[2.39112903, 2.36979167],
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[2.41532258, 2.1875],
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[2.1733871, 1.703125],
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[2.07782258, 1.16666667]])
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# subdivide polygon using 2nd degree B-Splines
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new_hand = hand.copy()
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for _ in range(5):
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new_hand = subdivide_polygon(new_hand, degree=2, preserve_ends=True)
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# approximate subdivided polygon with Douglas-Peucker algorithm
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appr_hand = approximate_polygon(new_hand, tolerance=0.02)
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print("Number of coordinates:", len(hand), len(new_hand), len(appr_hand))
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fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(9, 4))
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ax1.plot(hand[:, 0], hand[:, 1])
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ax1.plot(new_hand[:, 0], new_hand[:, 1])
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ax1.plot(appr_hand[:, 0], appr_hand[:, 1])
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# create two ellipses in image
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img = np.zeros((800, 800), 'int32')
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rr, cc = ellipse(250, 250, 180, 230, img.shape)
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img[rr, cc] = 1
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rr, cc = ellipse(600, 600, 150, 90, img.shape)
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img[rr, cc] = 1
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plt.gray()
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ax2.imshow(img)
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# approximate / simplify coordinates of the two ellipses
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for contour in find_contours(img, 0):
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coords = approximate_polygon(contour, tolerance=2.5)
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ax2.plot(coords[:, 1], coords[:, 0], '-r', linewidth=2)
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coords2 = approximate_polygon(contour, tolerance=39.5)
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ax2.plot(coords2[:, 1], coords2[:, 0], '-g', linewidth=2)
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print("Number of coordinates:", len(contour), len(coords), len(coords2))
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ax2.axis((0, 800, 0, 800))
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plt.show()
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