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convert_cifar_data.cpp
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convert_cifar_data.cpp
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// Copyright 2014 BVLC and contributors.
//
// This script converts the CIFAR dataset to the leveldb format used
// by caffe to perform classification.
// Usage:
// convert_cifar_data input_folder output_db_file
// The CIFAR dataset could be downloaded at
// http://www.cs.toronto.edu/~kriz/cifar.html
#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 "caffe/proto/caffe.pb.h"
using std::string;
const int kCIFARSize = 32;
const int kCIFARImageNBytes = 3072;
const int kCIFARBatchSize = 10000;
const int kCIFARTrainBatches = 5;
void read_image(std::ifstream* file, int* label, char* buffer) {
char label_char;
file->read(&label_char, 1);
*label = label_char;
file->read(buffer, kCIFARImageNBytes);
return;
}
void convert_dataset(const string& input_folder, const string& output_folder) {
// Leveldb options
leveldb::Options options;
options.create_if_missing = true;
options.error_if_exists = true;
// Data buffer
int label;
char str_buffer[kCIFARImageNBytes];
string value;
caffe::Datum datum;
datum.set_channels(3);
datum.set_height(kCIFARSize);
datum.set_width(kCIFARSize);
LOG(INFO) << "Writing Training data";
leveldb::DB* train_db;
leveldb::Status status;
status = leveldb::DB::Open(options, output_folder + "/cifar-train-leveldb",
&train_db);
CHECK(status.ok()) << "Failed to open leveldb.";
for (int fileid = 0; fileid < kCIFARTrainBatches; ++fileid) {
// Open files
LOG(INFO) << "Training Batch " << fileid + 1;
snprintf(str_buffer, kCIFARImageNBytes, "/data_batch_%d.bin", fileid + 1);
std::ifstream data_file((input_folder + str_buffer).c_str(),
std::ios::in | std::ios::binary);
CHECK(data_file) << "Unable to open train file #" << fileid + 1;
for (int itemid = 0; itemid < kCIFARBatchSize; ++itemid) {
read_image(&data_file, &label, str_buffer);
datum.set_label(label);
datum.set_data(str_buffer, kCIFARImageNBytes);
datum.SerializeToString(&value);
snprintf(str_buffer, kCIFARImageNBytes, "%05d",
fileid * kCIFARBatchSize + itemid);
train_db->Put(leveldb::WriteOptions(), string(str_buffer), value);
}
}
LOG(INFO) << "Writing Testing data";
leveldb::DB* test_db;
CHECK(leveldb::DB::Open(options, output_folder + "/cifar-test-leveldb",
&test_db).ok()) << "Failed to open leveldb.";
// Open files
std::ifstream data_file((input_folder + "/test_batch.bin").c_str(),
std::ios::in | std::ios::binary);
CHECK(data_file) << "Unable to open test file.";
for (int itemid = 0; itemid < kCIFARBatchSize; ++itemid) {
read_image(&data_file, &label, str_buffer);
datum.set_label(label);
datum.set_data(str_buffer, kCIFARImageNBytes);
datum.SerializeToString(&value);
snprintf(str_buffer, kCIFARImageNBytes, "%05d", itemid);
test_db->Put(leveldb::WriteOptions(), string(str_buffer), value);
}
delete train_db;
delete test_db;
}
int main(int argc, char** argv) {
if (argc != 3) {
printf("This script converts the CIFAR dataset to the leveldb format used\n"
"by caffe to perform classification.\n"
"Usage:\n"
" convert_cifar_data input_folder output_folder\n"
"Where the input folder should contain the binary batch files.\n"
"The CIFAR dataset could be downloaded at\n"
" http://www.cs.toronto.edu/~kriz/cifar.html\n"
"You should gunzip them after downloading.\n");
} else {
google::InitGoogleLogging(argv[0]);
convert_dataset(string(argv[1]), string(argv[2]));
}
return 0;
}