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Sobel算子

x方向和y方向的Sobel算子

清晰度评价（Python实现）

import cv2 as cvimport numpy as npimport matplotlib.pyplot as pltimport mathimg = cv.imread('../images/girl.jpg')# gray_img = cv.cvtColor(img, cv.COLOR_BGR2GRAY)def sum_sobel(src):    """    src: src input image    ddepth: output image depth, -1 mean same as input    dx: order of the derivative x    dy: order of the derivative y    """    dst = cv.Sobel(src, -1, 1, 0)    rows, cols, _ = dst.shape    return math.ceil(sum(cv.sumElems(dst)) / rows / cols)def my_blur(src, n):    dst = src    for _ in range(n):        dst = cv.blur(src, (8, 8))        src = dst    return dstfig, ax = plt.subplots(2, 2, figsize=(5, 5))def plot(src, num, n, index):    title = 'origin' if index == 0 else str(n) + ' times blur'    title = title + '(' + str(num) + ')'    ii = int(index / 2)    jj = int(index % 2)    ax[ii][jj].set_title(title)    ax[ii][jj].imshow(cv.cvtColor(src, cv.COLOR_BGR2RGB))val = sum_sobel(img)plot(img, val, 0, 0)times = [3, 6, 9]for i in range(len(times)):    blur_img = my_blur(img.copy(), i + 1)    val = sum_sobel(blur_img)    plot(blur_img, val, times[i], i + 1)[axi.axis('off') for axi in ax.ravel()]plt.show()

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