lanedetect_video_opencv.py

import matplotlib.pylab as plt
import cv2 as cv
import numpy as np


def draw_the_line(img, lines):
    img = np.copy(img)
    blank_image = np.zeros((img.shape[0], img.shape[1], 3), dtype=np.uint8)


    for line in lines:
        for x1, y1, x2, y2 in line:
            cv.line(blank_image, (x1, y1), (x2, y2), (255, 255, 0), thickness=2)
    img = cv.addWeighted(img, 0.8, blank_image, 1, 0.0)
    return img
def region_of_interst(img,vertices):
    mask=np.zeros_like(img)
    #channel_count=img.shape[2]
    match_mask_color=255
    cv.fillPoly(mask,vertices,match_mask_color)
    mask_image=cv.bitwise_and(img,mask)
    return mask_image

def process(image):
    print(image.shape)
    height = image.shape[0]
    width = image.shape[1]
    region_of_interst_vertices = [(0, height), (width / 2, height / 2), (width, height)]
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    canny = cv.Canny(gray, 250, 300)
    cropped = region_of_interst(canny, np.array([region_of_interst_vertices], np.int32))
    line1 = cv.HoughLinesP(cropped, rho=10, theta=np.pi / 60, threshold=100, lines=np.array([]), minLineLength=5,
                           maxLineGap=5)
    image_width_line = draw_the_line(image, line1)
    return image_width_line


cap=cv.VideoCapture('drive.mp4')
while(cap.isOpened()):
    ret,frame=cap.read()
    frame=process(frame)
    cv.imshow('detection',frame)
    if cv.waitKey(1) &0xFF==ord('q'):
        break
cap.release()
cv.destroyAllWindows()