MNIST數(shù)據(jù)庫(kù)介紹：MNIST是一個(gè)手寫數(shù)字?jǐn)?shù)據(jù)庫(kù)，它有60000個(gè)訓(xùn)練樣本集和10000個(gè)測(cè)試樣本集。它是NIST數(shù)據(jù)庫(kù)的一個(gè)子集。

???????? MNIST數(shù)據(jù)庫(kù)官方網(wǎng)址為：http://yann.lecun.com/exdb/mnist/ ，也可以在windows下直接下載，train-images-idx3-ubyte.gz、train-labels-idx1-ubyte.gz等。下載四個(gè)文件，解壓縮。解壓縮后發(fā)現(xiàn)這些文件并不是標(biāo)準(zhǔn)的圖像格式。這些圖像數(shù)據(jù)都保存在二進(jìn)制文件中。每個(gè)樣本圖像的寬高為28*28。

???????? 以下為將其轉(zhuǎn)換成普通的jpg圖像格式的代碼：

#include "funset.hpp"
#include <iostream>
#include <fstream>
#include <vector>
#include <opencv2/opencv.hpp>static 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;
}static void read_Mnist(std::string filename, std::vector<cv::Mat> &vec)
{std::ifstream file(filename, std::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) {cv::Mat tp = cv::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);}}
}static void read_Mnist_Label(std::string filename, std::vector<int> &vec)
{std::ifstream file(filename, std::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;}}
}static std::string GetImageName(int number, int arr[])
{std::string str1, str2;for (int i = 0; i < 10; i++) {if (number == i) {arr[i]++;str1 = std::to_string(arr[i]);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;}}str2 = std::to_string(number) + "_" + str1;return str2;
}int MNISTtoImage()
{// reference: http://eric-yuan.me/cpp-read-mnist/// test images and test labels// read MNIST image into OpenCV Mat vectorstd::string filename_test_images = "E:/GitCode/NN_Test/data/database/MNIST/t10k-images.idx3-ubyte";int number_of_test_images = 10000;std::vector<cv::Mat> vec_test_images;read_Mnist(filename_test_images, vec_test_images);// read MNIST label into int vectorstd::string filename_test_labels = "E:/GitCode/NN_Test/data/database/MNIST/t10k-labels.idx1-ubyte";std::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" << std::endl;return -1;}// save test imagesint count_digits[10];std::fill(&count_digits[0], &count_digits[0] + 10, 0);std::string save_test_images_path = "E:/GitCode/NN_Test/data/tmp/MNIST/test_images/";for (int i = 0; i < vec_test_images.size(); i++) {int number = vec_test_labels[i];std::string image_name = GetImageName(number, count_digits);image_name = save_test_images_path + image_name + ".jpg";cv::imwrite(image_name, vec_test_images[i]);}// train images and train labels// read MNIST image into OpenCV Mat vectorstd::string filename_train_images = "E:/GitCode/NN_Test/data/database/MNIST/train-images.idx3-ubyte";int number_of_train_images = 60000;std::vector<cv::Mat> vec_train_images;read_Mnist(filename_train_images, vec_train_images);// read MNIST label into int vectorstd::string filename_train_labels = "E:/GitCode/NN_Test/data/database/MNIST/train-labels.idx1-ubyte";std::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()) {std::cout << "parse MNIST train file error" << std::endl;return -1;}// save train imagesstd::fill(&count_digits[0], &count_digits[0] + 10, 0);std::string save_train_images_path = "E:/GitCode/NN_Test/data/tmp/MNIST/train_images/";for (int i = 0; i < vec_train_images.size(); i++) {int number = vec_train_labels[i];std::string image_name = GetImageName(number, count_digits);image_name = save_train_images_path + image_name + ".jpg";cv::imwrite(image_name, vec_train_images[i]);}// save big imagsstd::string images_path = "E:/GitCode/NN_Test/data/tmp/MNIST/train_images/";int width = 28 * 20;int height = 28 * 10;cv::Mat dst(height, width, CV_8UC1);for (int i = 0; i < 10; i++) {for (int j = 1; j <= 20; j++) {int x = (j-1) * 28;int y = i * 28;cv::Mat part = dst(cv::Rect(x, y, 28, 28));std::string str = std::to_string(j);if (j < 10)str = "0000" + str;elsestr = "000" + str;str = std::to_string(i) + "_" + str + ".jpg";std::string input_image = images_path + str;cv::Mat src = cv::imread(input_image, 0);if (src.empty()) {fprintf(stderr, "read image error: %s\n", input_image.c_str());return -1;}src.copyTo(part);}}std::string output_image = images_path + "result.png";cv::imwrite(output_image, dst);return 0;
}