opencv binary transformation lane tracking

toBinary.py

# for a given sobel kernel size and threshold values
def toMagSobel(img, sobel_kernel=3, mag_thresh=(0, 255)):
    # Convert to grayscale
    if len(np.shape(img)) > 2:
        gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    else:
        gray = img
    # Take both Sobel x and y gradients
    sobelx = cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=sobel_kernel)
    sobely = cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=sobel_kernel)
    # Calculate the gradient magnitude
    gradmag = np.sqrt(sobelx**2 + sobely**2)
    # Rescale to 8 bit
    scale_factor = np.max(gradmag)/255 
    gradmag = (gradmag/scale_factor).astype(np.uint8) 
    # Create a binary image of ones where threshold is met, zeros otherwise
    binary_output = np.zeros_like(gradmag)
    binary_output[(gradmag >= mag_thresh[0]) & (gradmag <= mag_thresh[1])] = 1

    plt.suptitle('After Binary Mag Sobel', fontsize=14, fontweight='bold')
    plt.imshow(binary_output)
    plt.show()
    # Return the binary image
    return binary_output