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Open Source Computer Vision Library
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42 lines
1.2 KiB
42 lines
1.2 KiB
#!/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("detected circles", cimg) |
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cv2.imshow("source", src) |
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cv2.waitKey(0)
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