import cv2
import numpy as np
# Read image
image = cv2.imread('path/to/image.png')
# Convert image to grayscale
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
# Use canny edge detection
edges = cv2.Canny(gray,50,150,apertureSize=3)
# Apply HoughLinesP method to
# to directly obtain line end points
lines_list =[]
lines = cv2.HoughLinesP(
edges, # Input edge image
1, # Distance resolution in pixels
np.pi/180, # Angle resolution in radians
threshold=100, # Min number of votes for valid line
minLineLength=5, # Min allowed length of line
maxLineGap=10 # Max allowed gap between line for joining them
)
# Iterate over points
for points in lines:
# Extracted points nested in the list
x1,y1,x2,y2=points[0]
# Draw the lines joing the points
# On the original image
cv2.line(image,(x1,y1),(x2,y2),(0,255,0),2)
# Maintain a simples lookup list for points
lines_list.append([(x1,y1),(x2,y2)])
# Save the result image
cv2.imwrite('detectedLines.png',image)