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#!/usr/bin/python
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'''
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This example illustrates how to use cv2.HoughCircles() function.
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Usage:
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houghcircles.py [<image_name>]
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image argument defaults to ../data/board.jpg
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'''
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# Python 2/3 compatibility
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from __future__ import print_function
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import cv2
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import numpy as np
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import sys
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if __name__ == '__main__':
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print(__doc__)
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try:
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fn = sys.argv[1]
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except IndexError:
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fn = "../data/board.jpg"
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src = cv2.imread(fn, 1)
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img = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
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img = cv2.medianBlur(img, 5)
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cimg = src.copy() # numpy function
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circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)
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if circles != None: # Check if circles have been found and only then iterate over these and add them to the image
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a, b, c = circles.shape
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for i in range(b):
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cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv2.LINE_AA)
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cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv2.LINE_AA) # draw center of circle
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cv2.imshow("source", src)
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cv2.imshow("detected circles", cimg)
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cv2.waitKey(0)
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