前言

執行索伯算子過濾

實作

Sobel Absolute Threshold

# Define a function that applies Sobel x or y, 
# then takes an absolute value and applies a threshold.
def abs_sobel_thresh(img, orient='x', thresh_min=25, thresh_max=255):
    # Apply the following steps to img
    # 1) Convert to grayscale === or LAB L channel
    gray = (cv2.cvtColor(img, cv2.COLOR_RGB2Lab))[:,:,0]
    # 2) Take the derivative in x or y given orient = 'x' or 'y'
    sobel = cv2.Sobel(gray, cv2.CV_64F, orient=='x', orient=='y')
    # 3) Take the absolute value of the derivative or gradient
    abs_sobel = np.absolute(sobel)
    # 4) Scale to 8-bit (0 - 255) then convert to type = np.uint8
    scaled_sobel = np.uint8(255*abs_sobel/np.max(abs_sobel))
    # 5) Create a mask of 1's where the scaled gradient magnitude 
            # is > thresh_min and < thresh_max
    sxbinary = np.zeros_like(scaled_sobel)
    sxbinary[(scaled_sobel >= thresh_min) & (scaled_sobel <= thresh_max)] = 1
    # 6) Return this mask as your binary_output image
    binary_output = sxbinary # Remove this line
    return binary_output

Visualize Sobel absolute threshold

def update(min_thresh, max_thresh):
    exampleImg_sobelAbs = abs_sobel_thresh(exampleImg_unwarp, 'x', min_thresh, max_thresh)
    # Visualize sobel absolute threshold
    f, (ax1, ax2) = plt.subplots(1, 2, figsize=(20,10))
    f.subplots_adjust(hspace = .2, wspace=.05)
    ax1.imshow(exampleImg_unwarp)
    ax1.set_title('Unwarped Image', fontsize=30)
    ax2.imshow(exampleImg_sobelAbs, cmap='gray')
    ax2.set_title('Sobel Absolute', fontsize=30)

interact(update, 
         min_thresh=(0,255), 
         max_thresh=(0,255))

成果