caffe中负责整个网络输入的datalayer是从leveldb里读取数据的，是一个google实现的非常高效的kv数据库。
因此我们训练网络必须先把数据转成leveldb的格式。
这里我实现的是把一个文件夹的所有图片转成leveldb的格式。
工具使用命令格格式：convert_imagedata src_dir dst_dir attach_dir channel width height
样例：./convert_imagedata.bin /home/linger/imdata/collar_train/ /home/linger/linger/testfile/crop_train_db/ /home/linger/linger/testfile/crop_train_attachment/ 3 50 50
源代码：
#include <google/protobuf/text_format.h>
#include <glog/logging.h>
#include <leveldb/db.h>
#include <stdint.h>
#include <fstream> // NOLINT(readability/streams)
#include <string>
#include <set>
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <dirent.h>
#include <sys/stat.h>
#include <unistd.h>
#include <sys/types.h>
#include "caffe/proto/caffe.pb.h"
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>
#include <opencv2/imgproc/imgproc.hpp>
using std::string;
using namespace std;
set<string> all_class_name;
map<string,int> class2id;
/**
* path:目录
* files：用于保存文件名的vector
* r：是否需要遍历子目录
* return:文件名，不包含路径
*/
void list_dir(const char *path,vector<string>& files,bool r = false)
{
DIR *pDir;
struct dirent *ent;
char childpath[512];
pDir = opendir(path);
memset(childpath, 0, sizeof(childpath));
while ((ent = readdir(pDir)) != NULL)
{
if (ent->d_type & DT_DIR)
{
if (strcmp(ent->d_name, ".") == 0 || strcmp(ent->d_name, "..") == 0)
{
continue;
}
if(r) //如果需要遍历子目录
{
sprintf(childpath, "%s/%s", path, ent->d_name);
list_dir(childpath,files);
}
}
else
{
files.push_back(ent->d_name);
}
}
sort(files.begin(),files.end());//排序
}
string get_classname(string path)
{
int index = path.find_last_of('_');
return path.substr(0, index);
}
int get_labelid(string fileName)
{
string class_name_tmp = get_classname(fileName);
all_class_name.insert(class_name_tmp);
map<string,int>::iterator name_iter_tmp = class2id.find(class_name_tmp);
if (name_iter_tmp == class2id.end())
{
int id = class2id.size();
class2id.insert(name_iter_tmp, std::make_pair(class_name_tmp, id));
return id;
}
else
{
return name_iter_tmp->second;
}
}
void loadimg(string path,char* buffer)
{
cv::Mat img = cv::imread(path, CV_LOAD_IMAGE_COLOR);
string val;
int rows = img.rows;
int cols = img.cols;
int pos=0;
for (int c = 0; c < 3; c++)
{
for (int row = 0; row < rows; row++)
{
for (int col = 0; col < cols; col++)
{
buffer[pos++]=img.at<cv::Vec3b>(row,col)[c];
}
}
}
}
void convert(string imgdir,string outputdb,string attachdir,int channel,int width,int height)
{
leveldb::DB* db;
leveldb::Options options;
options.create_if_missing = true;
options.error_if_exists = true;
caffe::Datum datum;
datum.set_channels(channel);
datum.set_height(height);
datum.set_width(width);
int image_size = channel*width*height;
char buffer[image_size];
string value;
CHECK(leveldb::DB::Open(options, outputdb, &db).ok());
vector<string> filenames;
list_dir(imgdir.c_str(),filenames);
string img_log = attachdir+"image_filename";
ofstream writefile(img_log.c_str());
for(int i=0;i<filenames.size();i++)
{
string path= imgdir;
path.append(filenames[i]);//算出绝对路径
loadimg(path,buffer);
int labelid = get_labelid(filenames[i]);
datum.add_label(labelid);
datum.set_data(buffer,image_size);
datum.SerializeToString(&value);
snprintf(buffer, image_size, "%05d", i);
printf("\nclassid:%d classname:%s abspath:%s",labelid,get_classname(filenames[i]).c_str(),path.c_str());
db->Put(leveldb::WriteOptions(),string(buffer),value);
//printf("%d %s\n",i,fileNames[i].c_str());
assert(writefile.is_open());
writefile<<i<<" "<<filenames[i]<<"\n";
}
delete db;
writefile.close();
img_log = attachdir+"image_classname";
writefile.open(img_log.c_str());
set<string>::iterator iter = all_class_name.begin();
while(iter != all_class_name.end())
{
assert(writefile.is_open());
writefile<<(*iter)<<"\n";
//printf("%s\n",(*iter).c_str());
iter++;
}
writefile.close();
}
int main(int argc, char** argv)
{
if (argc < 6)
{
LOG(ERROR) << "convert_imagedata src_dir dst_dir attach_dir channel width height";
return 0;
}
//./convert_imagedata.bin /home/linger/imdata/collarTest/ /home/linger/linger/testfile/dbtest/ /home/linger/linger/testfile/test_attachment/ 3 250 250
// ./convert_imagedata.bin /home/linger/imdata/collar_train/ /home/linger/linger/testfile/crop_train_db/ /home/linger/linger/testfile/crop_train_attachment/ 3 50 50
google::InitGoogleLogging(argv[0]);
string src_dir = argv[1];
string src_dst = argv[2];
string attach_dir = argv[3];
int channel = atoi(argv[4]);
int width = atoi(argv[5]);
int height = atoi(argv[6]);
//for test
/*
src_dir = "/home/linger/imdata/collarTest/";
src_dst = "/home/linger/linger/testfile/dbtest/";
attach_dir = "/home/linger/linger/testfile/";
channel = 3;
width = 250;
height = 250;
*/
convert(src_dir,src_dst,attach_dir,channel,width,height);
}
caffe神经网络框架的辅助工具（将图片转换为leveldb格式）,布布扣,bubuko.com
caffe神经网络框架的辅助工具（将图片转换为leveldb格式）
原文地址：http://blog.csdn.net/lingerlanlan/article/details/31361299
