使用OpenCV把二进制mnist数据集转换为图片

mnist数据集是以二进制形式保存的，这里借助OpenCV把mnist数据集转换成图片格式。转换程序如下：

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

using namespace cv;
using namespace std;

int main()
{
	//mnist数据存放路径
	string train_test_image[2] = { "D:\Software\Caffe\caffe-master\data\mnist\mnist_train_lmdb\train-images.idx3-ubyte", 
		"D:\Software\Caffe\caffe-master\data\mnist\mnist_test_lmdb\t10k-images.idx3-ubyte" };
	string train_test_label[2] = { "D:\Software\Caffe\caffe-master\data\mnist\mnist_train_lmdb\train-labels.idx1-ubyte",
		"D:\Software\Caffe\caffe-master\data\mnist\mnist_test_lmdb\t10k-labels.idx1-ubyte" };
	int label_num[10] = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };
	//图片保存路径
	string dir[2] = { "D:\Software\Caffe\caffe-master\data\mnist\mnist_train_image\",
		"D:\Software\Caffe\caffe-master\data\mnist\mnist_test_image\" };
	for (int iter = 0; iter < 2; iter++)
	{
		//读取label  
		ifstream fin_label(train_test_label[iter], ios::binary);
		vector<int> label;
		int magic_number;
		fin_label.read((char *)(&magic_number), sizeof(magic_number));
		int number_items;
		fin_label.read((char *)(&number_items), sizeof(number_items));
		while (!fin_label.eof())
		{
			char label_tmp;
			fin_label.read((char *)&label_tmp, sizeof(label_tmp));
			label.push_back(label_tmp);
		}

		//读取图片  
		vector<Mat> image;
		int width = 28, height = 28;
		ifstream fin_image(train_test_image[iter], ios::binary);
		int magic_number1;
		fin_image.read((char *)(&magic_number1), sizeof(magic_number1));
		int number_images;
		fin_image.read((char *)(&number_images), sizeof(number_images));
		int num_rows;
		fin_image.read((char *)(&num_rows), sizeof(num_rows));
		int num_columns;
		fin_image.read((char *)(&num_columns), sizeof(num_columns));
		while (!fin_image.eof())
		{
			unsigned char tmp;
			Mat image_tmp(width, height, CV_8UC1);
			for (int r = 0; r < image_tmp.rows; r++)
			{
				for (int c = 0; c < image_tmp.cols; c++)
				{
					fin_image.read((char *)&tmp, sizeof(tmp));
					image_tmp.at<uchar>(r, c) = tmp;
				}
			}
			image.push_back(image_tmp);
		}

		for (int i = 0; i < label.size(); i++)
		{
			char clabel[10];
			sprintf_s(clabel, "%d", label[i]);
			string slabel = clabel;
			char clabel_num[10];
			sprintf_s(clabel_num, "%d", label_num[label[i]]);
			string slabel_num = clabel_num;
			string name = dir[iter] + slabel + "_" + slabel_num + ".jpg";
			imwrite(name, image[i]);
			//显示图片
			imshow("mnist", image[i]);
			waitKey(100);
			label_num[label[i]]++;
		}
	}
	return 0;
}

转换出来一共有60000个训练图片，10000个测试图片，部分训练图片：

下边使用OpenCV把训练图片的0~9的前10个图片显示出来：

#include <opencv2/core/core.hpp>  
#include <opencv2/imgproc/imgproc.hpp>  
#include <opencv2/highgui/highgui.hpp>  

using namespace cv;
using namespace std;

int main()
{
	Mat MNIST = Mat(Size(289, 289), CV_8UC1, Scalar::all(255));
	string mnistPath = "D:\Software\Caffe\caffe-master\data\mnist\mnist_train_image\";
	string mnistImagePath;
	stringstream str;
	for (int i = 0; i < 10; i++)
	{
		for (int j = 0; j < 10; j++)
		{
			str.clear();
			str << i;
			string stri, strj;
			str >> stri;
			str.clear();
			str << j;
			str >> strj;
			mnistImagePath = mnistPath + stri + "_" + strj + ".jpg";
			Mat image = imread(mnistImagePath, 0);
			Mat roi = MNIST(Rect(j * 28 + j, i * 28 + i, 28, 28));
			addWeighted(roi, 0, image, 1, 0, roi);
			imshow("mnist", MNIST);
		}
		waitKey();
	}
}

 

执行结果：