jg.py

import numpy as np
import cv2

video_capture = cv2.VideoCapture(0)
video_capture.set(3, 160)
video_capture.set(4, 120)

while(True):

    # Capture the frames
    ret, crop_img = video_capture.read()

    # Crop the image
    #crop_img = frame[60:120, 0:160]

    # Convert to grayscale
    gray = cv2.cvtColor(crop_img, cv2.COLOR_BGR2GRAY)

    # Gaussian blur
    blur = cv2.GaussianBlur(gray,(5,5),0)

    # Color thresholding
    ret,thresh = cv2.threshold(blur,60,255,cv2.THRESH_BINARY_INV)

    # Find the contours of the frame
    _,contours,hierarchy = cv2.findContours(thresh.copy(), 1, cv2.CHAIN_APPROX_NONE)

    # Find the biggest contour (if detected)
    if len(contours) > 0:
        c = max(contours, key=cv2.contourArea)
        M = cv2.moments(c)
        cx = int(M['m10']/M['m00'])
        cy = int(M['m01']/M['m00'])

        cv2.line(crop_img,(cx,0),(cx,720),(255,0,0),1)
        cv2.line(crop_img,(0,cy),(1280,cy),(255,0,0),1)
        cv2.drawContours(crop_img, contours, -1, (0,255,0), 1)

        if cx >= 120:
            print "Turn Left!"

        if cx < 120 and cx > 50:
            print "On Track!"

        if cx <= 50:
            print "Turn Right"

    else:
        print "I don't see the line"
    
    #Display the resulting frame
    cv2.imshow('frame',crop_img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break