randperm()产生随机的序列

%if filepaths 是一个5*1的结构体，then

cshuffle = randperm(length(filepaths)) %对filepaths进行随机的洗牌，得到了 cshuffle  => [2,5,4,1,3] 洗牌后的序列

MyYuanLaiPic = imread('e:/image/matlab/Cluo.jpg');%读取RGB格式的图像

MyFirstGrayPic = rgb2gray(MyYuanLaiPic);%用已有的函数进行RGB到灰度图像的转换  

[rows , cols , colors] = size(MyYuanLaiPic);%得到原来图像的矩阵的参数

MidGrayPic = zeros(rows , cols);%用得到的参数创建一个全零的矩阵，这个矩阵用来存储用下面的方法产生的灰度图像

MidGrayPic = uint8(MidGrayPic);%将创建的全零矩阵转化为uint8格式，因为用上面的语句创建之后图像是double型的  

for i = :rows

    for j = :cols

        sum = ;

        for k = :colors

            sum = sum + MyYuanLaiPic(i , j , k) / ;%进行转化的关键公式，sum每次都因为后面的数字而不能超过255 

        end

        MidGrayPic(i , j) = sum;

    end

end

imwrite(MidGrayPic , 'E:/image/matlab/Cluo.png' , 'png');  

%显示原来的RGB图像

figure();

imshow(MyYuanLaiPic);  

%显示经过系统函数运算过的灰度图像

figure();

imshow(MyFirstGrayPic);  

%显示转化之后的灰度图像

figure();

imshow(MidGrayPic);

function I = data_augmentation(I, K)

if K ==

    return;

elseif K ==  % flipped

    I = flipud(I);

    return;

elseif K ==  % rotation

    I = rot90(I,);

    return;

elseif K ==  % rotation  & flipped

    I = rot90(I,);

    I = flipud(I);

    return;

elseif K ==  % rotation

    I = rot90(I,);

    return;

elseif K ==  % rotation  & flipped

    I = rot90(I,);

    I = flipud(I);

    return;

elseif K ==  % rotation

    I = rot90(I,);

    return;

elseif K ==  % rotation  & flipped

    I = rot90(I,);

    I = flipud(I);

    return;

end

HR_current  = imresize(HR,nscales(j,i),'bicubic');

%第二个参数为缩放因子，e.g. 0.5、0.8
%第三个参数为缩放method

im2double()将值0~255映射到0~1之间

 for x = +step1 : stride : (hei-patchsize+)

            for y = +step2 : stride : (wid-patchsize+)

                count = count + ;

                subim_label  = HR_current(x : x+patchsize-, y : y+patchsize-,:nch);

                imdb.HRlabels(:, :, :, count) = subim_label;

                if count<=diffPatches   %不够一个patch进行填充

                    imdb.HRlabels(:, :, :, end-count+)   = HR_current(x : x+patchsize-, y : y+patchsize-,:nch);

                end

            end

        end

function [imdb] = generatepatches

%% Note, set your training image set first, large dataset is prefered!

folders    = {'path_of_your_training_dataset'}; % set this first!

stride     = ;  % control the number of image patches

patchsize  = ;

batchSize  = ; % important for BNorm

count      = ;

nch        = ;   %  for grayscale image,  for color image

step1      = ;

step2      = ;

ext               =  {'*.jpg','*.png','*.bmp'};

filepaths         =  [];

for j = :length(folders)

    for i =  : length(ext)

        filepaths = cat(,filepaths, dir(fullfile(folders{j}, ext{i}))); %获取folder获取所有figure

    end

end

cshuffle = randperm(length(filepaths)); % randperm获取filepaths的随机排列

nimages  = round(length(filepaths)); % control the number of image patches 去整数

ns       = ;

nscales  = min(,0.45 + 0.05*randi(,[ns,nimages])); %产生随机矩阵 * all values are less than

naugment = randi(,[,nimages]); %产生一个随机矩阵1*    all values are form  - 

for i =  : nimages

    % HR = imread(fullfile(filepaths(cshuffle(i)).folder,filepaths(cshuffle(i)).name));

    HR = imread(fullfile(folders{},filepaths(cshuffle(i)).name)); %从文件夹里随机读取一张图片

    HR = HR(:,:,); %如果是rgb图就获取一个通道的，如果是gray图则自然为该图像

    HR = data_augmentation(HR, naugment(i)); % 数据增大data_augmentation    data_augmentation(HR, ); 转到data_augmentation.m里面就将图片旋转90度

    disp([i,nimages,round(count/batchSize)])

    for j = : size(nscales,) %  size(nscales,) 为1

        HR_current  = imresize(HR,nscales(j,i),'bicubic'); %对图像进行尺度的缩放

        [hei,wid,~] = size(HR_current); % 得到此时的高和宽

        for x = +step1 : stride : (hei-patchsize+)   % 产生的patch  (hei-patchsize+)这个value是一个临界值，最后放不了一个patch

            for y = +step2 : stride : (wid-patchsize+)

                count=count+;

            end

        end

    end

end

numPatches  = ceil(count/batchSize)*batchSize; %ceil(1.2)=> ceil(0.2)=> 总共有多少个patch

diffPatches = numPatches - count;   % 真实的差了多少个patch

disp([numPatches,numPatches/batchSize,diffPatches]);

disp('-----------------------------');

%------------------------------------------------------------------

%------------------------------------------------------------------

count = ;

imdb.HRlabels  = zeros(patchsize, patchsize, nch, numPatches,'single');  %imdb是一个结构体 ***

for i =  : nimages

    % HR = imread(fullfile(filepaths(cshuffle(i)).folder,filepaths(cshuffle(i)).name));

    HR = imread(fullfile(folders{},filepaths(cshuffle(i)).name)); %从文件夹里随机读取一张图片

    if nch == && size(HR,) ==   %rgb2gray

        HR = rgb2gray(HR);

    end

    HR = data_augmentation(HR, naugment(i));  % 图像旋转操作

    disp([i,nimages,round(count/)])

    for j = : size(nscales,)

        HR_current  = imresize(HR,nscales(j,i),'bicubic'); %图像进行随机的缩放

        [hei,wid,~] = size(HR_current);

        HR_current  = im2single(HR_current);

        for x = +step1 : stride : (hei-patchsize+)

            for y = +step2 : stride : (wid-patchsize+)

                count = count + ;

                subim_label  = HR_current(x : x+patchsize-, y : y+patchsize-,:nch);

                imdb.HRlabels(:, :, :, count) = subim_label;

                if count<=diffPatches   %不够一个patch进行填充

                    imdb.HRlabels(:, :, :, end-count+)   = HR_current(x : x+patchsize-, y : y+patchsize-,:nch);

                end

            end

        end

    end

end

imdb.set    = uint8(ones(,size(imdb.HRlabels,)));

size(A,dims) = value

# 如xx是一个16*401的矩阵，则求到第一维度的大小16

size(xx,1) =>16

#  如xx是一个16*401的矩阵，则求到第二维度的大小401

size(xx,2) =>401