# python lane angle detection

from skimage.transform import (hough_line, hough_line_peaks) import numpy as np import cv2 image = cv2.imread('2.png') # Compute arithmetic mean image = np.mean(image, axis=2) # Perform Hough Transformation to detect lines hspace, angles, distances = hough_line(image) # Find angle angle=[] for _, a , distances in zip(*hough_line_peaks(hspace, angles, distances)): angle.append(a) # Obtain angle for each line angles = [a*180/np.pi for a in angle] # Compute difference between the two lines angle_difference = np.max(angles) - np.min(angles) print(angle_difference)

**Here is what the above code is Doing:**

1. Read the image

2. Compute the arithmetic mean of the image

3. Perform Hough Transformation to detect lines

4. Find the angle of each line

5. Compute the difference between the two lines