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#!/usr/bin/python
'''
This example illustrates how to use cv.HoughCircles() function.
'''
# Python 2/3 compatibility
from __future__ import print_function
import cv2 as cv
import numpy as np
import sys
from numpy import pi, sin, cos
from tests_common import NewOpenCVTests
def circleApproximation(circle):
nPoints = 30
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 = cv.contourArea(c1)
s2 = cv.contourArea(c2)
s, _ = cv.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 = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
img = cv.medianBlur(img, 5)
circles = cv.HoughCircles(img, cv.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)
def test_houghcircles_alt(self):
fn = "samples/data/board.jpg"
src = self.get_sample(fn, 1)
img = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
img = cv.medianBlur(img, 5)
circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT_ALT, 1, 10, np.array([]), 300, 0.9, 1, 30)
self.assertEqual(circles.shape, (1, 18, 3))
circles = circles[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)
if __name__ == '__main__':
NewOpenCVTests.bootstrap()
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