61 lines
1.5 KiB
Python
61 lines
1.5 KiB
Python
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#!/usr/bin/python
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'''
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This example illustrates how to use Hough Transform to find lines
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Usage:
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houghlines.py [<image_name>]
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image argument defaults to pic1.png
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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 as cv
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import numpy as np
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import sys
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import math
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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 = 'pic1.png'
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src = cv.imread(cv.samples.findFile(fn))
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dst = cv.Canny(src, 50, 200)
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cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
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if True: # HoughLinesP
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lines = cv.HoughLinesP(dst, 1, math.pi/180.0, 40, np.array([]), 50, 10)
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a, b, _c = lines.shape
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for i in range(a):
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cv.line(cdst, (lines[i][0][0], lines[i][0][1]), (lines[i][0][2], lines[i][0][3]), (0, 0, 255), 3, cv.LINE_AA)
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else: # HoughLines
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lines = cv.HoughLines(dst, 1, math.pi/180.0, 50, np.array([]), 0, 0)
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if lines is not None:
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a, b, _c = lines.shape
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for i in range(a):
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rho = lines[i][0][0]
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theta = lines[i][0][1]
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a = math.cos(theta)
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b = math.sin(theta)
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x0, y0 = a*rho, b*rho
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pt1 = ( int(x0+1000*(-b)), int(y0+1000*(a)) )
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pt2 = ( int(x0-1000*(-b)), int(y0-1000*(a)) )
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cv.line(cdst, pt1, pt2, (0, 0, 255), 3, cv.LINE_AA)
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cv.imshow("detected lines", cdst)
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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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