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#!/usr/bin/python
'''
This example illustrates how to use cv2.HoughCircles() function.
Usage:
houghcircles.py [<image_name>]
image argument defaults to ../data/board.jpg
'''
# Python 2/3 compatibility
from __future__ import print_function
import cv2
import numpy as np
import sys
if __name__ == '__main__':
print(__doc__)
try:
fn = sys.argv[1]
except IndexError:
fn = "../data/board.jpg"
src = cv2.imread(fn, 1)
img = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
img = cv2.medianBlur(img, 5)
cimg = src.copy() # numpy function
circles = cv2.HoughCircles(img, cv2.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
a, b, c = circles.shape
for i in range(b):
cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv2.LINE_AA)
cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv2.LINE_AA) # draw center of circle
cv2.imshow("detected circles", cimg)
cv2.imshow("source", src)
cv2.waitKey(0)
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