from skimage import img_as_float
import matplotlib.pyplot as plt
from skimage import io
import random
import numpy as np
file_name='D:/Visual Effects/PS Algorithm/4.jpg';
img=io.imread(file_name)
img = img_as_float(img)
img_out = img.copy()
row, col, channel = img.shape
half_patch =10
for i in range(half_patch, row-1-half_patch, half_patch):
  for j in range (half_patch, col-1-half_patch, half_patch):
    k1 = random.random() - 0.5
    k2 = random.random() - 0.5
    m=np.floor(k1*(half_patch*2 + 1))
    n=np.floor(k2*(half_patch*2 + 1))
    h=int((i+m) % row)
    w=int((j+n) % col)
    img_out[i-half_patch:i+half_patch, j-half_patch:j+half_patch, :] =            img[h, w, :]
plt.figure(1)
plt.imshow(img)
plt.axis('off')
plt.figure(2)
plt.imshow(img_out)
plt.axis('off')
plt.show()

% method : 利用邻域的任意一点代替当前邻域所有像素点
%%%% mosaic
clc;
clear all;
addpath('E:\PhotoShop Algortihm\Image Processing\PS Algorithm');
Image=imread('4.jpg');
Image=double(Image);
size_info=size(Image);
height=size_info(1);
width=size_info(2);
N=11;  % 控制邻域大小
Image_out=Image;
for i=1+N:N:height-N
  for j=1+N:N:width-N
    k1=rand()-0.5;
    k2=rand()-0.5;
    m=(k1*(N*2-1));
    n=(k2*(N*2-1));
    h=floor(mod(i+m,height));
    w=floor(mod(j+n,width));
    if w==0;
      w=width;
    end
    if h==0
      h=height;
    end
   Image_out(i-N:i+N,j-N:j+N,1)=Image(h,w,1);
   Image_out(i-N:i+N,j-N:j+N,2)=Image(h,w,2);
   Image_out(i-N:i+N,j-N:j+N,3)=Image(h,w,3);
  end
end
imshow(Image_out/255);