text: #!/usr/bin/python
  
  '''
  This example illustrates how to use cv.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 as cv
  import numpy as np
  import sys
  
  if __name__ == '__main__':
      print(__doc__)
  
      try:
          fn = sys.argv[1]
      except IndexError:
          fn = "../data/board.jpg"
  
      src = cv.imread(fn, 1)
      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
          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)
  