当我应用cv2.erode()和不同的kernel值时，我一直在观察结果.在下面的代码中，它是(3, 3)，但它被更改为(1, 3)或(5, 1)等各种方式.这一观察的原因是为了理解kernel.
我在理论上理解.通过实践，我可以看到我得到了什么样的结果.但我想深入一点.
I would like to see what happens every time the pixel targeted by 100 changes.
如果您存储了数千张图像，那也没关系.
如何观察cv2.erode()的中间过程？我要求太多了吗？
image = cv2.imread(file_path, cv2.IMREAD_GRAYSCALE)
_, thresholded_image = cv2.threshold(image, 127, 255, cv2.THRESH_BINARY)
inverted_image = cv2.bitwise_not(thresholded_image)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
eroded_image = cv2.erode(inverted_image, kernel, iterations=5)
cv2.imshow('image', eroded_image)
cv2.waitKey(0)
cv2.destroyAllWindows()