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Removed obsolete python samples #25268 Clean Samples #25006 This PR removes 36 obsolete python samples from the project, as part of an effort to keep the codebase clean and focused on current best practices. Some of these samples will be updated with latest algorithms or will be combined with other existing samples. Removed Samples: > browse.py camshift.py coherence.py color_histogram.py contours.py deconvolution.py dft.py dis_opt_flow.py distrans.py edge.py feature_homography.py find_obj.py fitline.py gabor_threads.py hist.py houghcircles.py houghlines.py inpaint.py kalman.py kmeans.py laplace.py lk_homography.py lk_track.py logpolar.py mosse.py mser.py opt_flow.py plane_ar.py squares.py stitching.py text_skewness_correction.py texture_flow.py turing.py video_threaded.py video_v4l2.py watershed.py These changes aim to improve the repository's clarity and usability by removing examples that are no longer relevant or have been superseded by more up-to-date techniques.
50 lines
1.3 KiB
Python
Executable File
50 lines
1.3 KiB
Python
Executable File
#!/usr/bin/python
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'''
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This example illustrates how to use cv.HoughCircles() function.
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Usage:
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houghcircles.py [<image_name>]
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image argument defaults to 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 numpy as np
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import cv2 as cv
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import sys
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def main():
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try:
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fn = sys.argv[1]
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except IndexError:
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fn = 'board.jpg'
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src = cv.imread(cv.samples.findFile(fn))
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img = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
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img = cv.medianBlur(img, 5)
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cimg = src.copy() # numpy function
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circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)
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if circles is not None: # Check if circles have been found and only then iterate over these and add them to the image
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circles = np.uint16(np.around(circles))
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_a, b, _c = circles.shape
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for i in range(b):
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cv.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv.LINE_AA)
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cv.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv.LINE_AA) # draw center of circle
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cv.imshow("detected circles", cimg)
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cv.imshow("source", src)
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cv.waitKey(0)
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print('Done')
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if __name__ == '__main__':
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print(__doc__)
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main()
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cv.destroyAllWindows()
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