lanedetection.py

import cv2
import numpy as np 

def make_coordinates(image, line_parameters):
    slope, intercept= line_parameters
    y1= image.shape[0]
    y2= int(y1*(3/5))
    x1= int((y1-intercept)/slope)
    x2=int((y2-intercept)/slope)
    return np.array([x1,y1,x2,y2])

def average_slope_intercept(image,lines):
    left_fit=[]
    right_fit=[]
    for line in lines:
        x1,y1,x2,y2= line.reshape(4)
        parameters= np.polyfit((x1,x2),(y1,y2),1)
        slope= parameters[0]
        intercept = parameters[1]
        if slope <0:
            left_fit.append((slope,intercept))
        else:
            right_fit.append((slope,intercept))
    left_fit_average= np.average(left_fit,axis=0)
    right_fit_average=np.average(right_fit,axis=0)
    left_line=make_coordinates(image, left_fit_average)
    right_line=make_coordinates(image, right_fit_average)
    return np.array([left_line,right_line])


def canny(image):
    gray=cv2.cvtColor(image,cv2.COLOR_RGB2GRAY)
    blur=cv2.GaussianBlur(gray,(5,5),0)
    canny=cv2.Canny(blur,50,150)
    return canny

def display_lines(image,lines):
    line_image=np.zeros_like(image)
    if lines is not None:
        for  x1,y1,x2,y2 in lines:
            cv2.line(line_image,(x1,y1),(x2,y2),(255,0,0),10)
    return line_image
    


def region_of_interest(image):
    height =image.shape[0]
    polygons =np.array([[(200,height),(1100,height),(550,250)]])
    mask=np.zeros_like(image)
    cv2.fillPoly(mask, polygons, 255)
    masked_image=cv2.bitwise_and(image,mask)
    return masked_image
# this code can be use for lane detection in image

# image= cv2.imread('testimage2.jpeg')
# lane_image=np.copy(image)
# canny=canny(lane_image)
# cropped_image= region_of_interest(canny)
# lines= cv2.HoughLinesP(cropped_image,2 ,np.pi/180,100,np.array([]),minLineLength=40,maxLineGap=5)
# averaged_lines= average_slope_intercept(lane_image, lines)
# line_image= display_lines(lane_image,averaged_lines)
# combo_image= cv2.addWeighted(lane_image,0.8,line_image,1,1)

cv2.imshow("result",combo_image)
cv2.waitKey(0)

cap= cv2.VideoCapture("test22.mp4")
while(cap.isOpened()):
    _, frame = cap.read()
    canny=canny(frame)
    cropped_image= region_of_interest(canny)
    lines= cv2.HoughLinesP(cropped_image,2 ,np.pi/180,100,np.array([]),minLineLength=40,maxLineGap=5)
    averaged_lines= average_slope_intercept(frame, lines)
    line_image= display_lines(frame,averaged_lines)
    combo_image= cv2.addWeighted(frame,0.8,line_image,1,1)
    cv2.imshow("result",combo_image)
    cv2.waitKey(1)