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/**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
//
// 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 <array>
#include <fstream> // NOLINT(readability/streams)
#include <sstream>
#include <string>
#include "caffe2/core/common.h"
#include "caffe2/core/db.h"
#include "caffe2/core/init.h"
#include "caffe2/proto/caffe2_pb.h"
#include "caffe2/core/logging.h"
C10_DEFINE_string(input_folder, "", "The input folder name.");
C10_DEFINE_string(output_train_db_name, "", "The output training db name.");
C10_DEFINE_string(output_test_db_name, "", "The output testing db name.");
C10_DEFINE_string(db, "leveldb", "The db type.");
C10_DEFINE_bool(
is_cifar100,
false,
"If set, convert cifar100. Otherwise do cifar10.");
namespace caffe2 {
using std::stringstream;
const int kCIFARSize = 32;
const int kCIFARImageNBytes = kCIFARSize * kCIFARSize * 3;
const int kCIFAR10BatchSize = 10000;
const int kCIFAR10TestDataSize = 10000;
const int kCIFAR10TrainBatches = 5;
const int kCIFAR100TrainDataSize = 50000;
const int kCIFAR100TestDataSize = 10000;
void ReadImage(std::ifstream* file, int* label, char* buffer) {
char label_char;
if (FLAGS_is_cifar100) {
// Skip the coarse label.
file->read(&label_char, 1);
}
file->read(&label_char, 1);
*label = label_char;
// Yes, there are better ways to do it, like in-place swap... but I am too
// lazy so let's just write it in a memory-wasteful way.
std::array<char, kCIFARImageNBytes> channel_first_storage;
file->read(channel_first_storage.data(), kCIFARImageNBytes);
for (int c = 0; c < 3; ++c) {
for (int i = 0; i < kCIFARSize * kCIFARSize; ++i) {
buffer[i * 3 + c] =
channel_first_storage[c * kCIFARSize * kCIFARSize + i];
}
}
return;
}
void WriteToDB(const string& filename, const int num_items,
const int& offset, db::DB* db) {
TensorProtos protos;
TensorProto* data = protos.add_protos();
TensorProto* label = protos.add_protos();
data->set_data_type(TensorProto::BYTE);
data->add_dims(kCIFARSize);
data->add_dims(kCIFARSize);
data->add_dims(3);
label->set_data_type(TensorProto::INT32);
label->add_dims(1);
label->add_int32_data(0);
LOG(INFO) << "Converting file " << filename;
std::ifstream data_file(filename.c_str(),
std::ios::in | std::ios::binary);
CAFFE_ENFORCE(data_file, "Unable to open file ", filename);
char str_buffer[kCIFARImageNBytes];
int label_value;
std::unique_ptr<db::Transaction> transaction(db->NewTransaction());
for (int itemid = 0; itemid < num_items; ++itemid) {
ReadImage(&data_file, &label_value, str_buffer);
data->set_byte_data(str_buffer, kCIFARImageNBytes);
label->set_int32_data(0, label_value);
snprintf(str_buffer, kCIFARImageNBytes, "%05d",
offset + itemid);
transaction->Put(string(str_buffer), protos.SerializeAsString());
}
}
void ConvertCIFAR() {
std::unique_ptr<db::DB> train_db(
db::CreateDB(FLAGS_db, FLAGS_output_train_db_name, db::NEW));
std::unique_ptr<db::DB> test_db(
db::CreateDB(FLAGS_db, FLAGS_output_test_db_name, db::NEW));
if (!FLAGS_is_cifar100) {
// This is cifar 10.
for (int fileid = 0; fileid < kCIFAR10TrainBatches; ++fileid) {
stringstream train_file;
train_file << FLAGS_input_folder << "/data_batch_" << fileid + 1
<< ".bin";
WriteToDB(train_file.str(), kCIFAR10BatchSize,
fileid * kCIFAR10BatchSize, train_db.get());
}
stringstream test_file;
test_file << FLAGS_input_folder << "/test_batch.bin";
WriteToDB(test_file.str(), kCIFAR10TestDataSize, 0, test_db.get());
} else {
// This is cifar 100.
stringstream train_file;
train_file << FLAGS_input_folder << "/train.bin";
WriteToDB(train_file.str(), kCIFAR100TrainDataSize, 0, train_db.get());
stringstream test_file;
test_file << FLAGS_input_folder << "/test.bin";
WriteToDB(test_file.str(), kCIFAR100TestDataSize, 0, test_db.get());
}
}
} // namespace caffe2
int main(int argc, char** argv) {
caffe2::GlobalInit(&argc, &argv);
caffe2::ConvertCIFAR();
return 0;
}
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