#!/usr/bin/python ''' This example illustrates how to use cv2.HoughCircles() function. ''' # Python 2/3 compatibility from __future__ import print_function import cv2 import numpy as np import sys from numpy import pi, sin, cos from tests_common import NewOpenCVTests def circleApproximation(circle): nPoints = 30 phi = 0 dPhi = 2*pi / nPoints contour = [] for i in range(nPoints): contour.append(([circle[0] + circle[2]*cos(i*dPhi), circle[1] + circle[2]*sin(i*dPhi)])) return np.array(contour).astype(int) def convContoursIntersectiponRate(c1, c2): s1 = cv2.contourArea(c1) s2 = cv2.contourArea(c2) s, _ = cv2.intersectConvexConvex(c1, c2) return 2*s/(s1+s2) class houghcircles_test(NewOpenCVTests): def test_houghcircles(self): fn = "samples/data/board.jpg" src = self.get_sample(fn, 1) img = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) img = cv2.medianBlur(img, 5) circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)[0] testCircles = [[38, 181, 17.6], [99.7, 166, 13.12], [142.7, 160, 13.52], [223.6, 110, 8.62], [79.1, 206.7, 8.62], [47.5, 351.6, 11.64], [189.5, 354.4, 11.64], [189.8, 298.9, 10.64], [189.5, 252.4, 14.62], [252.5, 393.4, 15.62], [602.9, 467.5, 11.42], [222, 210.4, 9.12], [263.1, 216.7, 9.12], [359.8, 222.6, 9.12], [518.9, 120.9, 9.12], [413.8, 113.4, 9.12], [489, 127.2, 9.12], [448.4, 121.3, 9.12], [384.6, 128.9, 8.62]] matches_counter = 0 for i in range(len(testCircles)): for j in range(len(circles)): tstCircle = circleApproximation(testCircles[i]) circle = circleApproximation(circles[j]) if convContoursIntersectiponRate(tstCircle, circle) > 0.6: matches_counter += 1 self.assertGreater(float(matches_counter) / len(testCircles), .5) self.assertLess(float(len(circles) - matches_counter) / len(circles), .75)