import numpy as np
import cv2

img=cv2.imread('ziliao/image00.JPG',1)
imInfo=img.shape
height=imInfo[0]
width=imInfo[1]

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) 
'''该函数用于颜色的转换，第一个参数为待处理的原图，
第二个参数表示转换的颜色'''

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
dst=np.zeros((height,width,3),np.uint8)
for i in range(4,height-4):
  for j in range(4,width-4):
    array1 = np.zeros(8, np.uint8) #用于存储每个灰度等级的像素个数
    for m in range(-4, 4): #计算8*8小方块中的array1的值
      for n in range(-4,4):
        p1 = int(gray[i + m, j + n] / 32) #除以32得到该点应该位于第几个灰度等级
        array1[p1] = array1[p1] + 1
    currentMax = array1[0]
    l = 0

    for k in range(0,8): #找到像素点最多的那个灰度等级
      if currentMax<array1[k]:
        currentMax = array1[k]
        l = k
     #以下方法是简化处理了，也可以按前文所说的那样求均值处理
    for m in range(-4,4):
      for n in range(-4,4):
        if gray[i+m,j+n]>=(l*32) and gray[i+m,j+n]<=((l+1)*32):
          (b,g,r) = img[i+m,j+n]
    dst[i,j] = (b,g,r)
cv2.imshow('img',img)
cv2.imshow('dst',dst)
cv2.waitKey(0)

import numpy as np
import cv2

img=cv2.imread('ziliao/image00.png',1)
imInfo=img.shape
height=imInfo[0]
width=imInfo[1]

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
dst=np.zeros((height,width,3),np.uint8)
for i in range(4,height-4):
  for j in range(4,width-4):
    array1 = np.zeros(8, np.uint8)
    for m in range(-4, 4):
      for n in range(-4,4):
        p1 = int(gray[i + m, j + n] / 32)
        array1[p1] = array1[p1] + 1
    currentMax = array1[0]
    l = 0

    for k in range(0,8):
      if currentMax<array1[k]:
        currentMax = array1[k]
        l = k
    for m in range(-4,4):
      for n in range(-4,4):
        if gray[i+m,j+n]>=(l*32) and gray[i+m,j+n]<=((l+1)*32):
          (b,g,r) = img[i+m,j+n]
    dst[i,j] = (b,g,r)
cv2.imshow('img',img)
cv2.imshow('dst',dst)
cv2.waitKey(0)