lane_detector_vid.py

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

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

def region_of_interest(image):
    height = image.shape[0]
    polygons = np.array([[(200, height), (1100, height), (550, 250)]])
    # polygons = np.array([[(300, 575), (970, 570), (680, 380), (600, 380)]]) # america_vid
    mask = np.zeros_like(image)
    cv2.fillPoly(mask, polygons, 255)
    masked_image = cv2.bitwise_and(image, mask)
    return masked_image

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), (128, 0, 128), 10)
    return line_image

def make_coordinates(image, line_parameters):
    slope, intercept = line_parameters
    y1 = image.shape[0]
    y2 = int(y1*(3/5))
    # y1 = int(image.shape[0]*(4/5)) # # america_vid
    # y2 = int(y1*(7/10)) # america_vid
    x1 = int((y1 - intercept)/slope)
    x2 = int((y2 - intercept)/slope)
    return np.array([x1, y1, x2, y2])
    
def averaged_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))
    if len(left_fit) > 0 and len(right_fit) > 0:
        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])
    else:
        exit()

cap = cv2.VideoCapture("swiss_vid.mp4")
# cap = cv2.VideoCapture("america_vid.mp4") # america_vid
while(cap.isOpened()):
    _, frame = cap.read()
    # process frame
    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 = averaged_slope_intercept(frame, lines)
    line_image = display_lines(frame, averaged_lines)
    combo_image = cv2.addWeighted(frame, 0.8, line_image, 1, 1)
    # display frame
    cv2.imshow("result", combo_image)
    if cv2.waitKey(15) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()
'''
plt.imshow(lane_image)
plt.show()
'''