Open Source Computer Vision Library
https://opencv.org/
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57 lines
1.5 KiB
57 lines
1.5 KiB
#!/usr/bin/python |
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''' |
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This example illustrates how to use cv2.HoughCircles() function. |
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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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from tests_common import NewOpenCVTests |
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class houghcircles_test(NewOpenCVTests): |
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def test_houghcircles(self): |
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fn = "samples/data/board.jpg" |
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src = self.get_sample(fn, 1) |
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img = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) |
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img = cv2.medianBlur(img, 5) |
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circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)[0] |
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testCircles = [[38, 181, 17.6], |
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[99.7, 166, 13.12], |
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[142.7, 160, 13.52], |
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[223.6, 110, 8.62], |
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[79.1, 206.7, 8.62], |
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[47.5, 351.6, 11.64], |
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[189.5, 354.4, 11.64], |
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[189.8, 298.9, 10.64], |
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[189.5, 252.4, 14.62], |
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[252.5, 393.4, 15.62], |
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[602.9, 467.5, 11.42], |
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[222, 210.4, 9.12], |
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[263.1, 216.7, 9.12], |
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[359.8, 222.6, 9.12], |
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[518.9, 120.9, 9.12], |
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[413.8, 113.4, 9.12], |
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[489, 127.2, 9.12], |
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[448.4, 121.3, 9.12], |
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[384.6, 128.9, 8.62]] |
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eps = 7 |
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matches_counter = 0 |
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for i in range(len(testCircles)): |
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for j in range(len(circles)): |
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if cv2.norm(testCircles[i] - circles[j], cv2.NORM_L2) < eps: |
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matches_counter += 1 |
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self.assertGreater(float(matches_counter) / len(testCircles), .5) |
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self.assertLess(float(len(circles) - matches_counter) / len(circles), .7) |