mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
48 lines
1.4 KiB
48 lines
1.4 KiB
#!/usr/bin/python |
|
''' |
|
This example illustrates how to use Hough Transform to find lines |
|
Usage: ./houghlines.py [<image_name>] |
|
image argument defaults to ../data/pic1.png |
|
''' |
|
# Python 2/3 compatibility |
|
from __future__ import print_function |
|
|
|
import cv2 |
|
import numpy as np |
|
import sys |
|
import math |
|
|
|
if __name__ == '__main__': |
|
|
|
try: |
|
fn = sys.argv[1] |
|
except: |
|
fn = "../data/pic1.png" |
|
print(__doc__) |
|
src = cv2.imread(fn) |
|
dst = cv2.Canny(src, 50, 200) |
|
cdst = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR) |
|
|
|
if True: # HoughLinesP |
|
lines = cv2.HoughLinesP(dst, 1, math.pi/180.0, 40, np.array([]), 50, 10) |
|
a,b,c = lines.shape |
|
for i in range(a): |
|
cv2.line(cdst, (lines[i][0][0], lines[i][0][1]), (lines[i][0][2], lines[i][0][3]), (0, 0, 255), 3, cv2.LINE_AA) |
|
|
|
else: # HoughLines |
|
lines = cv2.HoughLines(dst, 1, math.pi/180.0, 50, np.array([]), 0, 0) |
|
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)) ) |
|
cv2.line(cdst, pt1, pt2, (0, 0, 255), 3, cv2.LINE_AA) |
|
|
|
|
|
cv2.imshow("source", src) |
|
cv2.imshow("detected lines", cdst) |
|
cv2.waitKey(0)
|
|
|