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69 lines
1.7 KiB
69 lines
1.7 KiB
#!/usr/bin/python |
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''' |
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This example illustrates how to use Hough Transform to find lines |
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''' |
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# Python 2/3 compatibility |
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from __future__ import print_function |
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import cv2 |
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import numpy as np |
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import sys |
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import math |
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from tests_common import NewOpenCVTests |
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def linesDiff(line1, line2): |
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norm1 = cv2.norm(line1 - line2, cv2.NORM_L2) |
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line3 = line1[2:4] + line1[0:2] |
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norm2 = cv2.norm(line3 - line2, cv2.NORM_L2) |
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return min(norm1, norm2) |
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class houghlines_test(NewOpenCVTests): |
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def test_houghlines(self): |
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fn = "/samples/data/pic1.png" |
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src = self.get_sample(fn) |
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dst = cv2.Canny(src, 50, 200) |
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lines = cv2.HoughLinesP(dst, 1, math.pi/180.0, 40, np.array([]), 50, 10)[:,0,:] |
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eps = 5 |
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testLines = [ |
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#rect1 |
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[ 232, 25, 43, 25], |
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[ 43, 129, 232, 129], |
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[ 43, 129, 43, 25], |
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[232, 129, 232, 25], |
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#rect2 |
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[251, 86, 314, 183], |
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[252, 86, 323, 40], |
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[315, 183, 386, 137], |
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[324, 40, 386, 136], |
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#triangle |
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[245, 205, 377, 205], |
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[244, 206, 305, 278], |
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[306, 279, 377, 205], |
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#rect3 |
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[153, 177, 196, 177], |
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[153, 277, 153, 179], |
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[153, 277, 196, 277], |
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[196, 177, 196, 277]] |
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matches_counter = 0 |
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for i in range(len(testLines)): |
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for j in range(len(lines)): |
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if linesDiff(testLines[i], lines[j]) < eps: |
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matches_counter += 1 |
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self.assertGreater(float(matches_counter) / len(testLines), .7) |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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