caffe（三）：MNIST数据集可视化

前言

在手写字符识别任务中，需要将MNIST数据集打开，可视为png图片，然后重新组装新的测试集和验证集。

代码实现

//author: zhimazhimaheng
//time: 20170719
//E-mail:1439352516@qq.com

#include<fstream>
#include<iostream>
#include"opencv2/core/core.hpp"
#include"opencv2/highgui/highgui.hpp"
#include"opencv2/imgproc/imgproc.hpp"

using namespace std;
using namespace cv;

int ReverseInt(int i)
{
    unsigned char ch1, ch2, ch3, ch4;
    ch1=i & 255;
    ch2=(i>>8)&255;
    ch3=(i>>16)&255;
    ch4=(i>>24)&255;
    return ((int) ch1<<24)+((int)ch2<<16)+((int)ch3<<8)+ch4;
}
void read_Mnist(string filename, vector<Mat> &vec)
{
    ifstream file(filename, ios::binary);
    if(file.is_open())
    {
        int magic_number=0;
        int number_of_images=0;
        int n_rows=0;
        int n_cols=0;
        file.read((char*)&magic_number, sizeof(magic_number));
        magic_number=ReverseInt(magic_number);
        file.read((char*)&number_of_images,sizeof(number_of_images));
        number_of_images=ReverseInt(number_of_images);
        file.read((char*)&n_rows, sizeof(n_rows));
        n_rows=ReverseInt(n_rows);
        file.read((char*)&n_cols, sizeof(n_cols));
        n_cols=ReverseInt(n_cols);
        for(int i=0; i<number_of_images; i++)
        {
            Mat tp=Mat::zeros(n_rows, n_cols, CV_8UC1);
            for(int r=0; r<n_rows; r++)
            {
                for(int c=0; c<n_cols; c++)
                {
                    unsigned char temp=0;
                    file.read((char*) &temp, sizeof(temp));
                    tp.at<uchar>(r,c)=(int)temp;
                }
            }
            vec.push_back(tp);
        }
    }
}
//读取训练与测试标签  
void read_Mnist_Label(string filename, vector<int> &vec)  
{  
    ifstream file (filename, ios::binary);  
    if (file.is_open()) {  
        int magic_number = 0;  
        int number_of_images = 0;  
        int n_rows = 0;  
        int n_cols = 0;  
        file.read((char*) &magic_number, sizeof(magic_number));  
        magic_number = ReverseInt(magic_number);  
        file.read((char*) &number_of_images,sizeof(number_of_images));  
        number_of_images = ReverseInt(number_of_images);  
        for(int i = 0; i < number_of_images; ++i)  
        {  
            unsigned char temp = 0;  
            file.read((char*) &temp, sizeof(temp));  
            vec[i]= (int)temp;  
        }  
    }  
}  
string GetImageName(int number, int arr[])
{
    string str1, str2;
    for(int i=0; i<10; i++)
    {
        if(number==i)
        {
            arr[i]++;
            char ch1[10];
            sprintf(ch1, "%d", arr[i]);
            str1=std::string(ch1);
            if(arr[i]<10)
            {
                str1="0000"+str1;
            }
            else if(arr[i]<100)
            {
                str1="000"+str1;
            }
            else if(arr[i]<1000)
            {
                str1="00"+str1;
            }
            else if(arr[i]<10000)
            {
                str1="0"+str1;
            }
            break;
        }
    }
    char ch2[10];
    sprintf(ch2, "%d", number);
    str2=std::string(ch2);
    str2=str2+"_"+str1;
    return str2;
}
int main()
{
    //测试数据和测试标签  
    //读取测试数据 转换为Mat  
    string filename_test_images = "D:/Mycode/t10k-images-idx3-ubyte/t10k-images.idx3-ubyte";  
    int number_of_test_images = 10000;   //测试数据10000个  
    vector<cv::Mat> vec_test_images;  
    read_Mnist(filename_test_images, vec_test_images);  
    //读取测试标签 转换为vector  
    string filename_test_labels = "D:/Mycode/t10k-labels-idx1-ubyte/t10k-labels.idx1-ubyte";  
    vector<int> vec_test_labels(number_of_test_images);  
    read_Mnist_Label(filename_test_labels, vec_test_labels);  
    if (vec_test_images.size() != vec_test_labels.size()) {  
        std::cout<<"parse MNIST test file error"<<endl;
        return -1;  
    }  
    //保存测试图像  
    int count_digits[10];  
    for (int i = 0; i < 10; i++)  
        count_digits[i] = 0;  
    string save_test_images_path = "D:/Mycode/MNIST/test_images/";   //保存路径  
    for (int i = 0; i < vec_test_images.size(); i++)   
    {  
        int number = vec_test_labels[i];  
        string image_name = GetImageName(number, count_digits);  
        image_name = save_test_images_path + image_name + ".png";

        cv::imwrite(image_name, vec_test_images[i]);  
    }  
//训练数据与训练标签  
    //read MNIST image into OpenCV Mat vector  
    string filename_train_images = "D:/Mycode/train-images-idx3-ubyte/train-images.idx3-ubyte";  
    int number_of_train_images = 60000;  
    vector<cv::Mat> vec_train_images;  
    read_Mnist(filename_train_images, vec_train_images);  
    //read MNIST label into int vector  
    string filename_train_labels = "D:/Mycode/train-labels-idx1-ubyte/train-labels.idx1-ubyte";  
    vector<int> vec_train_labels(number_of_train_images);  
    read_Mnist_Label(filename_train_labels, vec_train_labels);  
    if (vec_train_images.size() != vec_train_labels.size()) {  
        cout<<"parse MNIST train file error"<<endl;  
        return -1;  
    }  
    //save train images  
    for (int i = 0; i < 10; i++)  
        count_digits[i] = 0;  
    string save_train_images_path = "D:/Mycode/MNIST/train_images/"; //保存路径  
    for (int i = 0; i < vec_train_images.size(); i++) {  
        int number = vec_train_labels[i];  
        string image_name = GetImageName(number, count_digits);  
        image_name = save_train_images_path + image_name + ".png";
        cv::imwrite(image_name, vec_train_images[i]);  
    }  
    return 1;  
    }

结果如下所示：