Line Detection In Python OpenCV With HoughLines

In this Python OpenCV article we are going to talk about Line Detection With HoughLines algorithm. so line detection has it own technique that is called the Hough transform, it was invented by Richard Duda and Peter Hart, who extended the work done by Paul Hough in the early 1960s. so now we are using HoughLines and HoughLinesP for detecting lines so the difference is that. HoughLines uses the standard HoughTransForm and HoughLinesP probabilistic Hough Transform.

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So now this is the complete code for Line Detection In Python OpenCV With HoughLines

import cv2
import numpy as np
import math



image1 = cv2.imread('dave2.jpg')
gray=cv2.cvtColor(image1,cv2.COLOR_BGR2GRAY)
canimg = cv2.Canny(gray, 50, 200)

lines= cv2.HoughLines(canimg, 1, np.pi/180.0, 120, np.array([]))


for line in lines:
    rho, theta = line[0]
    a = np.cos(theta)
    b = np.sin(theta)
    x0 = a*rho
    y0 = b*rho
    x1 = int(x0 + 1000*(-b))
    y1 = int(y0 + 1000*(a))
    x2 = int(x0 - 1000*(-b))
    y2 = int(y0 - 1000*(a))

    cv2.line(image1,(x1,y1),(x2,y2),(0,0,255),2)


cv2.imshow('Lines Detected',image1)
cv2.imshow("Canny Detection", canimg)
cv2.waitKey(0)
cv2.destroyAllWindows()

import cv2

import numpy as np

import math

image1 = cv2.imread('dave2.jpg')

gray=cv2.cvtColor(image1,cv2.COLOR_BGR2GRAY)

canimg = cv2.Canny(gray, 50, 200)

lines= cv2.HoughLines(canimg, 1, np.pi/180.0, 120, np.array([]))

for line in lines:

rho, theta = line[0]

a = np.cos(theta)

b = np.sin(theta)

x0 = a*rho

y0 = b*rho

x1 = int(x0 + 1000*(-b))

y1 = int(y0 + 1000*(a))

x2 = int(x0 - 1000*(-b))

y2 = int(y0 - 1000*(a))

cv2.line(image1,(x1,y1),(x2,y2),(0,0,255),2)

cv2.imshow('Lines Detected',image1)

cv2.imshow("Canny Detection", canimg)

cv2.waitKey(0)

cv2.destroyAllWindows()

So at the top these are our imports that we are going to use in this article.

import cv2
import numpy as np
import math

import cv2

import numpy as np

import math

You need to have an image in your directory, iam using this image.

In here we have loaded our image and we have converted the image to gray scale.

image1 = cv2.imread('dave2.jpg')
gray=cv2.cvtColor(image1,cv2.COLOR_BGR2GRAY)

1 2	image1 = cv2.imread('dave2.jpg') gray=cv2.cvtColor(image1,cv2.COLOR_BGR2GRAY)

Also in this line of code we have created our Canny algorithm , you can check this article on Python OpenCV Canny Edge Detection.

canimg = cv2.Canny(gray, 50, 200)

1	canimg = cv2.Canny(gray, 50, 200)

So now this is our HoughLine algorithm for Line Detection.

lines= cv2.HoughLines(canimg, 1, np.pi/180.0, 120, np.array([]))

1	lines= cv2.HoughLines(canimg, 1, np.pi/180.0, 120, np.array([]))

in here the first parameter is the image that we want to process, another parameter is The geometrical representations of the lines, rho and theta, which are usually 1 and np.pi/180.

Also we we want to write color lines on the line this code is for that

for line in lines:
    rho, theta = line[0]
    a = np.cos(theta)
    b = np.sin(theta)
    x0 = a*rho
    y0 = b*rho
    x1 = int(x0 + 1000*(-b))
    y1 = int(y0 + 1000*(a))
    x2 = int(x0 - 1000*(-b))
    y2 = int(y0 - 1000*(a))

    cv2.line(image1,(x1,y1),(x2,y2),(0,0,255),2)