python最大值最小值滤波

import cv2 as cv
import numpy as np
import math
import copy


def spilt(a):
    if a / 2 == 0:
        x1 = x2 = a / 2
    else:
        x1 = math.floor(a / 2)
        x2 = a - x1
    return -x1, x2


def original(i, j, k, a, b, img):
    x1, x2 = spilt(a)
    y1, y2 = spilt(b)
    temp = np.zeros(a * b)
    count = 0
    for m in range(x1, x2):
        for n in range(y1, y2):
            if i + m < 0 or i + m > img.shape[0] - 1 or j + n < 0 or j + n > img.shape[1] - 1:
                temp[count] = img[i, j, k]
            else:
                temp[count] = img[i + m, j + n, k]
            count += 1
    return temp


# 中值滤波
def mid_functin(a, b, img):
    img0 = copy.copy(img)
    for i in range(0, img.shape[0]):
        for j in range(2, img.shape[1]):
            for k in range(img.shape[2]):
                temp = original(i, j, k, a, b, img0)
                img[i, j, k] = np.median(temp)
    return img


# 最大值滤波
def max_functin(a, b, img):
    img0 = copy.copy(img)
    for i in range(0, img.shape[0]):
        for j in range(2, img.shape[1]):
            for k in range(img.shape[2]):
                temp = original(i, j, k, a, b, img0)
                img[i, j, k] = np.max(temp)
    return img


# 最小值滤波
def min_functin(a, b, img):
    img0 = copy.copy(img)
    for i in range(0, img.shape[0]):
        for j in range(2, img.shape[1]):
            for k in range(img.shape[2]):
                temp = original(i, j, k, a, b, img0)
                img[i, j, k] = np.min(temp)
    return img


def main():
    img0 = cv.imread("./output2/2.jpg")

    mid_img = mid_functin(3, 3, copy.copy(img0))
    # max_img = max_functin(3, 3, copy.copy(img0))
    min_img = min_functin(3, 3, copy.copy(img0))

    # cv.imshow("original", img0)
    # cv.imshow("max_img", max_img)
    cv.imshow("min_img", min_img)
    cv.imshow("mid_img", mid_img)

    cv.waitKey(0)
    cv.destroyAllWindows()


if __name__ == "__main__":
    main()