Road detection and driving

from SinglePic import run_inference
import cv2
import numpy as np


def decodeVid(vidFile):
    video_capture = cv2.VideoCapture(vidFile)
    steering_angle2 = 40  # Initial steering angle for the second line
    steering_angle1 = 135  # Initial steering angle for the first line
    newVd = True
    height, width = 0,0
    center_x1, center_y1 = 0, 0
    center_x2, center_y2 = 0, 0
    x1, y1 = 0, 0
    x2, y2 = 0, 0
    pt = True

    while video_capture.isOpened():
        ret, frame = video_capture.read()
        if not ret:
            break
    
        processed_frame,driveAbleArea,steerin = run_inference(frame)
        
        
        # Adding lines 
        if newVd:
            height, width = processed_frame.shape[:2]
            center_x2 = 400
            center_y2 = 220
            center_x1 = 300
            center_y1 = 220
            newVd = False

        # Define the length of the lines
        line_length = min(height, width) // 2

        # Create a copy of the frame to draw lines on
        frame_with_lines = processed_frame.copy()

        # Calculate the endpoints of the lines based on the steering angles and positions
        angle_radians2 = np.deg2rad(steering_angle2)
        x2 = int(center_x2 + line_length * np.cos(angle_radians2))
        y2 = int(center_y2 + line_length * np.sin(angle_radians2))
        
        angle_radians1 = np.deg2rad(steering_angle1)
        x1 = int(center_x1 + line_length * np.cos(angle_radians1))
        y1 = int(center_y1 + line_length * np.sin(angle_radians1))

        cv2.line(frame_with_lines, (center_x2, center_y2), (x2, y2), (255,0,0), thickness=2)
        cv2.line(frame_with_lines, (center_x1, center_y1), (x1, y1), (255,0,0), thickness=2)
        
        rgb_image = cv2.cvtColor(frame_with_lines,cv2.COLOR_BGR2RGB)

        steering_angle2 += steerin[0]  
        steering_angle1 += steerin[1]

        '''
        for finding cordinates
        if pt:
            
            for i, cor in enumerate(line1_px):
                if i%150 == 0:
                    print(cor)
            pt = False
        '''

        # Display the processed frame with lines 
        cv2.imshow('Processed Frame', rgb_image)

        # Adjust dynamically
        key = cv2.waitKey(1) & 0xFF
        if key == ord('q'):
            break
        elif key == ord('p'):
            print(f"x1 = {x1}\ny1 = {y1}\nx2 = {x2}\ny2 = {y2}")

    # Release the video capture                                                        
    video_capture.release()

    # Close all OpenCV windows
    cv2.destroyAllWindows()

def main():
    decodeVid('dataset\gtaTest.mp4')

if __name__ == "__main__":
    main()