(self, img, rho, theta, threshold,
                    min_line_len, max_line_gap, backoff=0, debug=False)
return masked_lines, lane_info
`img` should be the output of a Canny transform.

        Returns an image with hough lines drawn using the new single line
            for left and right lane line method.
`img` should be the output of a Canny transform.
img should be the output of a Canny transform .
def hough_lines(self, img, rho, theta, threshold,
                    min_line_len, max_line_gap, backoff=0, debug=False):
        """
        `img` should be the output of a Canny transform.

        Returns an image with hough lines drawn using the new single line
            for left and right lane line method.
        """
        lines = cv2.HoughLinesP(img, rho, theta, threshold, np.array(
            []), minLineLength=min_line_len, maxLineGap=max_line_gap)
        masked_lines = np.zeros(img.shape, dtype=np.uint8)
        lane_info = self.draw_lines(
            masked_lines, lines, backoff=backoff, debug=debug)

        return masked_lines, lane_info
def hough_lines ( self , img , rho , theta , threshold , min_line_len , max_line_gap , backoff = 0 , debug = False ) : lines = cv2 . HoughLinesP ( img , rho , theta , threshold , np . array ( [ ] ) , minLineLength = min_line_len , maxLineGap = max_line_gap ) masked_lines = np . zeros ( img . shape , dtype = np . uint8 ) lane_info = self . draw_lines ( masked_lines , lines , backoff = backoff , debug = debug ) return masked_lines , lane_info