MNIST数据集转换为图像
2016-05-11 21:44
316 查看
很多的深度学习框架都有以MNIST为数据集的demo,MNIST是很好的手写数字数据集。在网上很容易找到资源,但是下载下来的文件并不是普通的图片格式。不转换为图片格式也可以用。但有时,我们希望得到可视化的图片格式。
MNIST数据集包含4个文件:
train-images-idx3-ubyte:training set images
train-labels-idx1-ubyte:training set labels
t10k-images-idx3-ubyte: test set images
t10k-labels-idx1-ubyte: test set labels
文件的格式很简单,可以理解为一个很长的一维数组。
测试图像(rain-images-idx3-ubyte)与训练图像(train-images-idx3-ubyte)由5部分组成:
测试标签(t10k-labels-idx1-ubyte)与训练标签(train-labels-idx1-ubyte)由3部分组成:
知道了文件的格式,写一个简单的程序就可以把MNIST数据集转换为图像。
程序来源:http://eric-yuan.me/cpp-read-mnist/
参考:http://yann.lecun.com/exdb/mnist/ http://blog.csdn.net/fengbingchun/article/details/49611549
MNIST数据集包含4个文件:
train-images-idx3-ubyte:training set images
train-labels-idx1-ubyte:training set labels
t10k-images-idx3-ubyte: test set images
t10k-labels-idx1-ubyte: test set labels
文件的格式很简单,可以理解为一个很长的一维数组。
测试图像(rain-images-idx3-ubyte)与训练图像(train-images-idx3-ubyte)由5部分组成:
32bits int (magic number) | 32bits int 图像个数 | 32bits int 图像高度28 | 32bits int 图像宽度28 | 像素值 (pixels) |
测试标签(t10k-labels-idx1-ubyte)与训练标签(train-labels-idx1-ubyte)由3部分组成:
32bits int (magic number) | 32bits int 图像个数 | 标签 (labels) |
<span style="font-family:SimSun;">#include <iostream> #include <fstream> #include "opencv2/core/core.hpp" #include "opencv2/highgui/highgui.hpp" #include "opencv2/imgproc/imgproc.hpp" using namespace std; //英特尔处理器和其他低端机用户必须翻转头字节。 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; } //读取训练与测试数据 void read_Mnist(string filename, vector<cv::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; //从文件中读取sizeof(magic_number) 个字符到 &magic_number file.read((char*) &magic_number, sizeof(magic_number)); magic_number = ReverseInt(magic_number); //获取训练或测试image的个数number_of_images file.read((char*) &number_of_images,sizeof(number_of_images)); number_of_images = ReverseInt(number_of_images); //获取训练或测试图像的高度Heigh file.read((char*) &n_rows, sizeof(n_rows)); n_rows = ReverseInt(n_rows); //获取训练或测试图像的宽度Width file.read((char*) &n_cols, sizeof(n_cols)); n_cols = ReverseInt(n_cols); //获取第i幅图像,保存到vec中 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); } } } //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()) { 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 + ".jpg"; 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 + ".jpg"; cv::imwrite(image_name, vec_train_images[i]); } return 1; }</span>
程序来源:http://eric-yuan.me/cpp-read-mnist/
参考:http://yann.lecun.com/exdb/mnist/ http://blog.csdn.net/fengbingchun/article/details/49611549
相关文章推荐
- [HDU 2066] 多个最短路比较大小
- (MVP+RxJava+Retrofit)解耦+Mockito单元测试 经验分享
- Android自定义视图动画(一)
- 文件的分割与合并
- Opencv3.1使用教程(一)ubuntu 14.04 安装Opencv3.1.0 (包含opencv_contrib模块)
- Tomcat服务器+MySQL数据库+MyBatis持久层框架的简单使用
- ARM交叉编译器_说明
- C 指针
- 笔记10:IPAddress 类、IPInterfaceProperties 类、IPGlobalProperties 类
- BeanUtils主要解决 的问题: 把对象的属性数据封装 到对象中
- 忙活了一天,PDF转epub基本成功
- seaJS 使用随笔
- linux基本命令(23)——linux目录结构
- mysql :=和=的区别
- Android项目之HiTomato源码
- 机器学习基础(林軒田)笔记之一
- 集成ShareSDK QQ分享的四点体会
- 检测下你的显示器是否有问题
- 【HUSTOJ】1112: 统计单词个数
- Linux基础篇四———管道命令