samples/python/snippets/houghcircles.py

An example using the Hough circle detector in python

#!/usr/bin/python
 
'''
This example illustrates how to use cv.HoughCircles() function.
 
Usage:
    houghcircles.py [<image_name>]
    image argument defaults to board.jpg
'''
 
# Python 2/3 compatibility
from __future__ import print_function
 
import numpy as np
import cv2 as cv
 
import sys
 
def main():
    try:
        fn = sys.argv[1]
    except IndexError:
        fn = 'board.jpg'
 
    src = cv.imread(cv.samples.findFile(fn))
    img = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
    img = cv.medianBlur(img, 5)
    cimg = src.copy() # numpy function
 
    circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)
 
    if circles is not None: # Check if circles have been found and only then iterate over these and add them to the image
        circles = np.uint16(np.around(circles))
        _a, b, _c = circles.shape
        for i in range(b):
            cv.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv.LINE_AA)
            cv.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv.LINE_AA)  # draw center of circle
 
        cv.imshow("detected circles", cimg)
 
    cv.imshow("source", src)
    cv.waitKey(0)
    print('Done')
 
 
if __name__ == '__main__':
    print(__doc__)
    main()
    cv.destroyAllWindows()