# -*- coding: utf-8 -*-
"""
Created on Tue Jun  2 08:26:16 2020

@author: My Laptop
"""

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

def make_coordinates(image, line_parameters):
    slope, intercept = line_parameters
    y1 = image.shape[0]
    y2 = int(y1 * (4/6))
    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 = []
    if lines is not 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) 
    try:
        left_line = make_coordinates(image, left_fit_average)
        right_line = make_coordinates(image, right_fit_average)

        return np.array([left_line, right_line])
    
    except Exception as e:
        print(e, '\n')
        #print error to console
        return None
    
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 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
    
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 detect_lane(image):
    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)
    overlay_image = cv2.addWeighted(lane_image, 0.8, line_image, 1, 1)
    return overlay_image
    
#image = cv2.imread('lane_input_image.png')
#overlay_image = detect_lane(image)
#cv2.imshow("result", overlay_image)
#cv2.waitKey(0)

video = cv2.VideoCapture("input_video.mp4")
while(video.isOpened()):
    _, frame = video.read()
    overlay_image=detect_lane(frame)
    cv2.imshow("result", overlay_image)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
    
video.release()
cv2.destroyAllWindows()