Window下用caffe实现MNIST训练

本博包含MNIST原始数据的格式转化，以及分类训练

1.数据转化

Caffe源码中src/caffe/caffe/examples/mnist/convert_mnist_data.cpp提供的实现代码并不能直接在Windows下运行，这里在源码的基础上进行了改写，使其可以直接在Windows 64位上直接运行，改写代码如下（直接替换convert_mnist_data.cpp中所有内容）：

PS1：蓝色字体部分需要根据你自己的实际路径进行修改

PS2：目前该程序一次只能处理train集或者test集中的一个，下方代码是处理test集的，处理train集的时候需要把蓝色路径改为train集的路径。

#include <gflags/gflags.h>  #include <glog/logging.h>  #include <google/protobuf/text_format.h>  #include <leveldb/db.h>  #include <leveldb/write_batch.h>  #include <lmdb.h>  #include <stdint.h>  #include <sys/stat.h>  #include <fstream>  // NOLINT(readability/streams)  #include <string>  #include <iostream>  #include "caffe/proto/caffe.pb.h"  using namespace caffe;  // NOLINT(build/namespaces)  using std::string;// gflags中的数据类型，c++ string，在这里指定转换到lmdb还是leveldb  DEFINE_string(backend, "lmdb", "The backend for storing the result");uint32_t swap_endian(uint32_t val) {val = ((val << 8) & 0xFF00FF00) | ((val >> 8) & 0xFF00FF);return (val << 16) | (val >> 16);}void convert_dataset(const char* image_filename, const char* label_filename,const char* db_path, const string& db_backend) {// Open files  std::ifstream image_file(image_filename, std::ios::in | std::ios::binary);std::ifstream label_file(label_filename, std::ios::in | std::ios::binary);CHECK(image_file) << "Unable to open file " << image_filename;CHECK(label_file) << "Unable to open file " << label_filename;// Read the magic and the meta data  uint32_t magic;uint32_t num_items;uint32_t num_labels;uint32_t rows;uint32_t cols;// 读取文件前n个字节，获取图像数量、图像宽、图像高  image_file.read(reinterpret_cast<char*>(&magic), 4);magic = swap_endian(magic);CHECK_EQ(magic, 2051) << "Incorrect image file magic.";label_file.read(reinterpret_cast<char*>(&magic), 4);magic = swap_endian(magic);CHECK_EQ(magic, 2049) << "Incorrect label file magic.";image_file.read(reinterpret_cast<char*>(&num_items), 4);num_items = swap_endian(num_items);label_file.read(reinterpret_cast<char*>(&num_labels), 4);num_labels = swap_endian(num_labels);CHECK_EQ(num_items, num_labels);image_file.read(reinterpret_cast<char*>(&rows), 4);rows = swap_endian(rows);image_file.read(reinterpret_cast<char*>(&cols), 4);cols = swap_endian(cols);// lmdb  MDB_env *mdb_env;MDB_dbi mdb_dbi;MDB_val mdb_key, mdb_data;MDB_txn *mdb_txn;// leveldb  leveldb::DB* db = NULL;leveldb::Options options;options.error_if_exists = true;options.create_if_missing = true;options.write_buffer_size = 268435456;leveldb::WriteBatch* batch = NULL;// Open db  if (db_backend == "leveldb") {  // leveldb  LOG(INFO) << "Opening leveldb " << db_path;leveldb::Status status = leveldb::DB::Open(options, db_path, &db);CHECK(status.ok()) << "Failed to open leveldb " << db_path<< ". Is it already existing?";batch = new leveldb::WriteBatch();}else if (db_backend == "lmdb") {  // lmdb  int rc;LOG(INFO) << "Opening lmdb " << db_path;// 创建指定的存放目录  //CHECK_EQ(mkdir(db_path, 0744), 0)  std::string strPath = std::string(db_path);std::string delPath = "rmdir /s/q " + strPath;system(delPath.c_str());strPath = "mkdir " + strPath;system(strPath.c_str());//CHECK_EQ(system(strPath.c_str()), 0) << "mkdir " << db_path << "failed";  // 创建lmdb数据库  CHECK_EQ(mdb_env_create(&mdb_env), MDB_SUCCESS) << "mdb_env_create failed";//CHECK_EQ(mdb_env_set_mapsize(mdb_env, 1099511627776), MDB_SUCCESS) << "mdb_env_set_mapsize failed";//1TB  CHECK_EQ(mdb_env_set_mapsize(mdb_env, 107374182), MDB_SUCCESS) << "mdb_env_set_mapsize failed";//100MB  CHECK_EQ(mdb_env_open(mdb_env, db_path, 0, 0664), MDB_SUCCESS) << "mdb_env_open failed";CHECK_EQ(mdb_txn_begin(mdb_env, NULL, 0, &mdb_txn), MDB_SUCCESS) << "mdb_txn_begin failed";CHECK_EQ(mdb_open(mdb_txn, NULL, 0, &mdb_dbi), MDB_SUCCESS) << "mdb_open failed. Does the lmdb already exist? ";}else {LOG(FATAL) << "Unknown db backend " << db_backend;}// Storing to db  char label;char* pixels = new char[rows * cols];int count = 0;const int kMaxKeyLength = 10;char key_cstr[kMaxKeyLength];string value;Datum datum; // Caffe数据类  datum.set_channels(1);datum.set_height(rows);datum.set_width(cols);LOG(INFO) << "A total of " << num_items << " items.";LOG(INFO) << "Rows: " << rows << " Cols: " << cols;// 将数据写入lmdb或leveldb数据库  for (int item_id = 0; item_id < num_items; ++item_id) {image_file.read(pixels, rows * cols);label_file.read(&label, 1);datum.set_data(pixels, rows*cols);datum.set_label(label);//snprintf(key_cstr, kMaxKeyLength, "%08d", item_id);  int ret = _snprintf(key_cstr, kMaxKeyLength, "%08d", item_id);if (ret == kMaxKeyLength || ret < 0) {printf("warning ");key_cstr[kMaxKeyLength - 1] = 0;}datum.SerializeToString(&value);string keystr(key_cstr);// Put in db  if (db_backend == "leveldb") {  // leveldb  batch->Put(keystr, value);}else if (db_backend == "lmdb") {  // lmdb  mdb_data.mv_size = value.size();mdb_data.mv_data = reinterpret_cast<void*>(&value[0]);mdb_key.mv_size = keystr.size();mdb_key.mv_data = reinterpret_cast<void*>(&keystr[0]);CHECK_EQ(mdb_put(mdb_txn, mdb_dbi, &mdb_key, &mdb_data, 0), MDB_SUCCESS)<< "mdb_put failed";}else {LOG(FATAL) << "Unknown db backend " << db_backend;}if (++count % 1000 == 0) {// Commit txn  if (db_backend == "leveldb") {  // leveldb  db->Write(leveldb::WriteOptions(), batch);delete batch;batch = new leveldb::WriteBatch();}else if (db_backend == "lmdb") {  // lmdb  CHECK_EQ(mdb_txn_commit(mdb_txn), MDB_SUCCESS)<< "mdb_txn_commit failed";CHECK_EQ(mdb_txn_begin(mdb_env, NULL, 0, &mdb_txn), MDB_SUCCESS)<< "mdb_txn_begin failed";}else {LOG(FATAL) << "Unknown db backend " << db_backend;}}}// write the last batch  if (count % 1000 != 0) {if (db_backend == "leveldb") {  // leveldb  db->Write(leveldb::WriteOptions(), batch);delete batch;delete db;}else if (db_backend == "lmdb") {  // lmdb  CHECK_EQ(mdb_txn_commit(mdb_txn), MDB_SUCCESS) << "mdb_txn_commit failed";mdb_close(mdb_env, mdb_dbi);mdb_env_close(mdb_env);}else {LOG(FATAL) << "Unknown db backend " << db_backend;}LOG(ERROR) << "Processed " << count << " files.";}delete[] pixels;}int main(int argc, char* argv[]){#ifndef GFLAGS_GFLAGS_H_  namespace gflags = google;#endif  argc = 4;#ifdef _DEBUG  argv[0] = "D:/Caffe/caffe-windows/Build/x64/Debug/convert_imageset.exe";#else  argv[0] = "D:/Caffe/caffe-windows/Build/x64/Release/convert_imageset.exe";#endif  argv[1] = "D:/Caffe/caffe-windows/Build/x64/Release/MNIST/t10k-images.idx3-ubyte";argv[2] = "D:/Caffe/caffe-windows/Build/x64/Release/MNIST/t10k-labels.idx1-ubyte";argv[3] = "D:\\Caffe\\caffe-windows\\Build\\x64\\Release\\MNIST\\lmdb\\test";// 用来设定usage说明  gflags::SetUsageMessage("This script converts the MNIST dataset to\n""the lmdb/leveldb format used by Caffe to load data.\n""Usage:\n""    convert_mnist_data [FLAGS] input_image_file input_label_file ""output_db_file\n""The MNIST dataset could be downloaded at\n""    http://yann.lecun.com/exdb/mnist/\n""You should gunzip them after downloading,""or directly use data/mnist/get_mnist.sh\n");// 解析命令行参数  gflags::ParseCommandLineFlags(&argc, &argv, true);// 获取标志参数backend的值  const string& db_backend = FLAGS_backend;if (argc != 4) {// 输出usage说明  gflags::ShowUsageWithFlagsRestrict(argv[0],"examples/mnist/convert_mnist_data");}else {// 设置日志文件名中"文件名"字段  // 每个进程中至少要执行一次InitGoogleLogging，否则不产生日志文件  google::InitGoogleLogging(argv[0]);convert_dataset(argv[1], argv[2], argv[3], db_backend);}std::cout << "ok!" << std::endl;return 0;}