前言
可视化什么的，总是好的
方法一
其实也就是用到了Ruslan Salakhutdinov and Geoff Hinton提供的工具包
% Version 1.000
%
% Code provided by Ruslan Salakhutdinov and Geoff Hinton
%
% Permission is granted for anyone to copy, use, modify, or distribute this
% program and accompanying programs and documents for any purpose, provided
% this copyright notice is retained and prominently displayed, along with
% a note saying that the original programs are available from our
% web page.
% The programs and documents are distributed without any warranty, express or
% implied. As the programs were written for research purposes only, they have
% not been tested to the degree that would be advisable in any important
% application. All use of these programs is entirely at the user's own risk.% This program reads raw MNIST files available at
% http://yann.lecun.com/exdb/mnist/
% and converts them to files in matlab format
% Before using this program you first need to download files:
% train-images-idx3-ubyte.gz train-labels-idx1-ubyte.gz
% t10k-images-idx3-ubyte.gz t10k-labels-idx1-ubyte.gz
% and gunzip them. You need to allocate some space for this. % This program was originally written by Yee Whye Teh % Work with test files first
fprintf(1,'You first need to download files:\n train-images-idx3-ubyte.gz\n train-labels-idx1-ubyte.gz\n t10k-images-idx3-ubyte.gz\n t10k-labels-idx1-ubyte.gz\n from http://yann.lecun.com/exdb/mnist/\n and gunzip them \n');
gunzip train-images-idx3-ubyte.gz
gunzip train-labels-idx1-ubyte.gz
gunzip t10k-images-idx3-ubyte.gz
gunzip t10k-labels-idx1-ubyte.gz
f = fopen('t10k-images-idx3-ubyte','r');
[a,count] = fread(f,4,'int32');g = fopen('t10k-labels-idx1-ubyte','r');
[l,count] = fread(g,2,'int32');fprintf(1,'Starting to convert Test MNIST images (prints 10 dots) \n');
n = 1000;Df = cell(1,10);
for d=0:9,Df{d+1} = fopen(['test' num2str(d) '.ascii'],'w');
end;for i=1:10,%读了10次fprintf('.');rawimages = fread(f,28*28*n,'uchar');rawlabels = fread(g,n,'uchar');rawimages = reshape(rawimages,28*28,n);%每一列就是一张图片，总共1000张for j=1:n,fprintf(Df{rawlabels(j)+1},'%3d ',rawimages(:,j));%把每一行读取进入Df{}文件中去，每一个标签对应每一类图片fprintf(Df{rawlabels(j)+1},'\n'); %读取一列换一行end;
end;fprintf(1,'\n');
for d=0:9,fclose(Df{d+1});D = load(['test' num2str(d) '.ascii'],'-ascii');fprintf('%5d Digits of class %d\n',size(D,1),d);save(['test' num2str(d) '.mat'],'D','-mat');
end;% Work with trainig files second
f = fopen('train-images-idx3-ubyte','r');
[a,count] = fread(f,4,'int32');g = fopen('train-labels-idx1-ubyte','r');
[l,count] = fread(g,2,'int32');fprintf(1,'Starting to convert Training MNIST images (prints 60 dots)\n');
n = 1000;Df = cell(1,10);
for d=0:9,Df{d+1} = fopen(['digit' num2str(d) '.ascii'],'w');
end;for i=1:60,fprintf('.');rawimages = fread(f,28*28*n,'uchar');rawlabels = fread(g,n,'uchar');rawimages = reshape(rawimages,28*28,n);for j=1:n,fprintf(Df{rawlabels(j)+1},'%3d ',rawimages(:,j));fprintf(Df{rawlabels(j)+1},'\n');end;
end;fprintf(1,'\n');
for d=0:9,fclose(Df{d+1});D = load(['digit' num2str(d) '.ascii'],'-ascii');fprintf('%5d Digits of class %d\n',size(D,1),d);save(['digit' num2str(d) '.mat'],'D','-mat');
end;%dos('rm *.ascii');%这个删除命令不好用
dos('del *.ascii')%我们用这个删除命令
mnist压缩包下载：链接：http://pan.baidu.com/s/1qXA3u9m 密码：2gza
显示的时候很简单，上面代码运行以后生成了这几个文件：
随便打开一个，得到一个名称为D的二维矩阵，然后采用如下代码就可显示
imshow(reshape(D(1,:),28,28))
就可以得到显示
方法二
也是比较常见的一个代码，包含分别提取图像和标签的代码，和上述实现差不多，但是封装到函数看起来更加方便
读取图片的代码：loadMNISTImages.m
function images = loadMNISTImages(filename)
%loadMNISTImages returns a 28x28x[number of MNIST images] matrix containing
%the raw MNIST imagesfp = fopen(filename, 'rb');
assert(fp ~= -1, ['Could not open ', filename, '']);magic = fread(fp, 1, 'int32', 0, 'ieee-be');
assert(magic == 2051, ['Bad magic number in ', filename, '']);numImages = fread(fp, 1, 'int32', 0, 'ieee-be');
numRows = fread(fp, 1, 'int32', 0, 'ieee-be');
numCols = fread(fp, 1, 'int32', 0, 'ieee-be');images = fread(fp, inf, 'unsigned char');
images = reshape(images, numCols, numRows, numImages);
images = permute(images,[2 1 3]);fclose(fp);% Reshape to #pixels x #examples
images = reshape(images, size(images, 1) * size(images, 2), size(images, 3));
% Convert to double and rescale to [0,1]
images = double(images) / 255;end
读取标签的代码：loadMNISTLabels.m
function labels = loadMNISTLabels(filename)
%loadMNISTLabels returns a [number of MNIST images]x1 matrix containing
%the labels for the MNIST imagesfp = fopen(filename, 'rb');
assert(fp ~= -1, ['Could not open ', filename, '']);magic = fread(fp, 1, 'int32', 0, 'ieee-be');
assert(magic == 2049, ['Bad magic number in ', filename, '']);numLabels = fread(fp, 1, 'int32', 0, 'ieee-be');labels = fread(fp, inf, 'unsigned char');assert(size(labels,1) == numLabels, 'Mismatch in label count');fclose(fp);enddata = loadMNISTImages('train-images-idx3-ubyte')';
labels = loadMNISTLabels('train-labels-idx1-ubyte');
image=reshape(data(1,:),28,28);
imshow(image)%显示图片
labels(1,1)%查看标签
