lanes.py

import argparse
import cv2
import numpy as np
import matplotlib.pyplot as plt

def make_coordinates(image, line):

    slope, intercept = line
    y1 = int(image.shape[0])# bottom of the image
    y2 = int(y1*3/5)         # slightly lower than the middle
    x1 = int((y1 - intercept)/slope)
    x2 = int((y2 - intercept)/slope)
    return [[x1, y1, x2, y2]]

def average_slope_intercept(image, lines):
    left_fit = []
    right_fit = []
    if lines is None:
        return None
    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 line in lines:
            x1, y1, x2, y2 = line.reshape(4)
            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

# image = cv2.imread("test_image.jpg")
# lane_image = np.copy(image)
# canny_image = canny(lane_image)
# cropped_image = region_of_interest(canny_image)
# 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)
def run(path): 
    cap = cv2.VideoCapture(path)
    while(cap.isOpened()):
        _, frame = cap.read()
        canny_image = canny(frame)
        cropped_image = region_of_interest(canny_image)
        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)
        if cv2.waitKey(1) == ord("q"):
            break
    cap.release()
    cv2.destroyAllWindows()

if __name__ == '__main__':
    ap = argparse.ArgumentParser()
    ap.add_argument("-s", "--path", required=True, help="path to the video file")
    args = ap.parse_args()
    
    run(args.path)