samples/python/snippets/houghlines.py

An example using the Hough line detector in python

#!/usr/bin/python
 
'''
This example illustrates how to use Hough Transform to find lines
 
Usage:
    houghlines.py [<image_name>]
    image argument defaults to pic1.png
'''
 
# Python 2/3 compatibility
from __future__ import print_function
 
import cv2 as cv
import numpy as np
 
import sys
import math
 
def main():
    try:
        fn = sys.argv[1]
    except IndexError:
        fn = 'pic1.png'
 
    src = cv.imread(cv.samples.findFile(fn))
    dst = cv.Canny(src, 50, 200)
    cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
 
    if True: # HoughLinesP
        lines = cv.HoughLinesP(dst, 1, math.pi/180.0, 40, np.array([]), 50, 10)
        a, b, _c = lines.shape
        for i in range(a):
            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)
 
    else:    # HoughLines
        lines = cv.HoughLines(dst, 1, math.pi/180.0, 50, np.array([]), 0, 0)
        if lines is not None:
            a, b, _c = lines.shape
            for i in range(a):
                rho = lines[i][0][0]
                theta = lines[i][0][1]
                a = math.cos(theta)
                b = math.sin(theta)
                x0, y0 = a*rho, b*rho
                pt1 = ( int(x0+1000*(-b)), int(y0+1000*(a)) )
                pt2 = ( int(x0-1000*(-b)), int(y0-1000*(a)) )
                cv.line(cdst, pt1, pt2, (0, 0, 255), 3, cv.LINE_AA)
 
    cv.imshow("detected lines", cdst)
 
    cv.imshow("source", src)
    cv.waitKey(0)
    print('Done')
 
 
if __name__ == '__main__':
    print(__doc__)
    main()
    cv.destroyAllWindows()