From 370217bf7206150901133ac9399bcf3a87462d90 Mon Sep 17 00:00:00 2001 From: Yangqing Jia Date: Mon, 13 Oct 2014 16:01:07 -0700 Subject: [PATCH] some namespace cleaning. --- src/caffe/test/test_caffe_main.cpp | 3 ++- src/caffe/test/test_dummy_data_layer.cpp | 3 --- src/caffe/test/test_hdf5_output_layer.cpp | 3 --- src/caffe/test/test_hdf5data_layer.cpp | 2 -- src/caffe/test/test_upgrade_proto.cpp | 2 -- tools/compute_image_mean.cpp | 9 ++++----- tools/convert_imageset.cpp | 15 +++++++-------- tools/dump_network.cpp | 15 ++++++++++----- tools/extract_features.cpp | 30 +++++++++++++++++------------- 9 files changed, 40 insertions(+), 42 deletions(-) diff --git a/src/caffe/test/test_caffe_main.cpp b/src/caffe/test/test_caffe_main.cpp index bff0c4e..c8caf5a 100644 --- a/src/caffe/test/test_caffe_main.cpp +++ b/src/caffe/test/test_caffe_main.cpp @@ -1,6 +1,7 @@ // The main caffe test code. Your test cpp code should include this hpp // to allow a main function to be compiled into the binary. +#include "caffe/caffe.hpp" #include "caffe/test/test_caffe_main.hpp" namespace caffe { @@ -15,7 +16,7 @@ using caffe::CAFFE_TEST_CUDA_PROP; int main(int argc, char** argv) { ::testing::InitGoogleTest(&argc, argv); - ::google::InitGoogleLogging(argv[0]); + caffe::GlobalInit(&argc, &argv); #ifndef CPU_ONLY // Before starting testing, let's first print out a few cuda defice info. int device; diff --git a/src/caffe/test/test_dummy_data_layer.cpp b/src/caffe/test/test_dummy_data_layer.cpp index da121fa..9954835 100644 --- a/src/caffe/test/test_dummy_data_layer.cpp +++ b/src/caffe/test/test_dummy_data_layer.cpp @@ -10,9 +10,6 @@ #include "caffe/test/test_caffe_main.hpp" -using std::string; -using std::stringstream; - namespace caffe { template diff --git a/src/caffe/test/test_hdf5_output_layer.cpp b/src/caffe/test/test_hdf5_output_layer.cpp index c828223..2e8f096 100644 --- a/src/caffe/test/test_hdf5_output_layer.cpp +++ b/src/caffe/test/test_hdf5_output_layer.cpp @@ -11,9 +11,6 @@ #include "caffe/test/test_caffe_main.hpp" -using std::string; -using std::vector; - namespace caffe { template diff --git a/src/caffe/test/test_hdf5data_layer.cpp b/src/caffe/test/test_hdf5data_layer.cpp index ed6fed8..41a3a83 100644 --- a/src/caffe/test/test_hdf5data_layer.cpp +++ b/src/caffe/test/test_hdf5data_layer.cpp @@ -13,8 +13,6 @@ #include "caffe/test/test_caffe_main.hpp" -using std::string; - namespace caffe { template diff --git a/src/caffe/test/test_upgrade_proto.cpp b/src/caffe/test/test_upgrade_proto.cpp index f46a0e8..52e7f1f 100644 --- a/src/caffe/test/test_upgrade_proto.cpp +++ b/src/caffe/test/test_upgrade_proto.cpp @@ -11,8 +11,6 @@ #include "caffe/test/test_caffe_main.hpp" -using std::string; - namespace caffe { class PaddingLayerUpgradeTest : public ::testing::Test { diff --git a/tools/compute_image_mean.cpp b/tools/compute_image_mean.cpp index 20f1ff8..6adde8b 100644 --- a/tools/compute_image_mean.cpp +++ b/tools/compute_image_mean.cpp @@ -11,7 +11,6 @@ using caffe::Datum; using caffe::BlobProto; -using std::string; using std::max; int main(int argc, char** argv) { @@ -22,9 +21,9 @@ int main(int argc, char** argv) { return 1; } - string db_backend = "lmdb"; + std::string db_backend = "lmdb"; if (argc == 4) { - db_backend = string(argv[3]); + db_backend = std::string(argv[3]); } // leveldb @@ -94,7 +93,7 @@ int main(int argc, char** argv) { for (it->SeekToFirst(); it->Valid(); it->Next()) { // just a dummy operation datum.ParseFromString(it->value().ToString()); - const string& data = datum.data(); + const std::string& data = datum.data(); size_in_datum = std::max(datum.data().size(), datum.float_data_size()); CHECK_EQ(size_in_datum, data_size) << "Incorrect data field size " << @@ -120,7 +119,7 @@ int main(int argc, char** argv) { do { // just a dummy operation datum.ParseFromArray(mdb_value.mv_data, mdb_value.mv_size); - const string& data = datum.data(); + const std::string& data = datum.data(); size_in_datum = std::max(datum.data().size(), datum.float_data_size()); CHECK_EQ(size_in_datum, data_size) << "Incorrect data field size " << diff --git a/tools/convert_imageset.cpp b/tools/convert_imageset.cpp index 4ab93fd..7c8c1da 100644 --- a/tools/convert_imageset.cpp +++ b/tools/convert_imageset.cpp @@ -27,7 +27,6 @@ using namespace caffe; // NOLINT(build/namespaces) using std::pair; -using std::string; DEFINE_bool(gray, false, "When this option is on, treat images as grayscale ones"); @@ -62,8 +61,8 @@ int main(int argc, char** argv) { bool is_color = !FLAGS_gray; bool check_size = FLAGS_check_size; std::ifstream infile(argv[2]); - std::vector > lines; - string filename; + std::vector > lines; + std::string filename; int label; while (infile >> filename >> label) { lines.push_back(std::make_pair(filename, label)); @@ -75,7 +74,7 @@ int main(int argc, char** argv) { } LOG(INFO) << "A total of " << lines.size() << " images."; - const string& db_backend = FLAGS_backend; + const std::string& db_backend = FLAGS_backend; const char* db_path = argv[3]; int resize_height = std::max(0, FLAGS_resize_height); @@ -121,7 +120,7 @@ int main(int argc, char** argv) { } // Storing to db - string root_folder(argv[1]); + std::string root_folder(argv[1]); Datum datum; int count = 0; const int kMaxKeyLength = 256; @@ -139,7 +138,7 @@ int main(int argc, char** argv) { data_size = datum.channels() * datum.height() * datum.width(); data_size_initialized = true; } else { - const string& data = datum.data(); + const std::string& data = datum.data(); CHECK_EQ(data.size(), data_size) << "Incorrect data field size " << data.size(); } @@ -147,9 +146,9 @@ int main(int argc, char** argv) { // sequential snprintf(key_cstr, kMaxKeyLength, "%08d_%s", line_id, lines[line_id].first.c_str()); - string value; + std::string value; datum.SerializeToString(&value); - string keystr(key_cstr); + std::string keystr(key_cstr); // Put in db if (db_backend == "leveldb") { // leveldb diff --git a/tools/dump_network.cpp b/tools/dump_network.cpp index 90895fd..9cb996e 100644 --- a/tools/dump_network.cpp +++ b/tools/dump_network.cpp @@ -22,7 +22,12 @@ #include "caffe/solver.hpp" #include "caffe/util/io.hpp" -using namespace caffe; // NOLINT(build/namespaces) +using boost::shared_ptr; +using caffe::Blob; +using caffe::BlobProto; +using caffe::Caffe; +using caffe::Net; +using caffe::NetParameter; int main(int argc, char** argv) { Caffe::set_mode(Caffe::GPU); @@ -37,7 +42,7 @@ int main(int argc, char** argv) { } caffe_net->CopyTrainedLayersFrom(argv[2]); - vector* > input_vec; + std::vector* > input_vec; shared_ptr > input_blob(new Blob()); if (strcmp(argv[3], "none") != 0) { BlobProto input_blob_proto; @@ -46,7 +51,7 @@ int main(int argc, char** argv) { input_vec.push_back(input_blob.get()); } - string output_prefix(argv[4]); + std::string output_prefix(argv[4]); // Run the network without training. LOG(ERROR) << "Performing Forward"; caffe_net->Forward(input_vec); @@ -62,8 +67,8 @@ int main(int argc, char** argv) { } // Now, let's dump all the layers - const vector& blob_names = caffe_net->blob_names(); - const vector > >& blobs = caffe_net->blobs(); + const std::vector& blob_names = caffe_net->blob_names(); + const std::vector > >& blobs = caffe_net->blobs(); for (int blobid = 0; blobid < caffe_net->blobs().size(); ++blobid) { // Serialize blob LOG(ERROR) << "Dumping " << blob_names[blobid]; diff --git a/tools/extract_features.cpp b/tools/extract_features.cpp index 9b0288a..299b311 100644 --- a/tools/extract_features.cpp +++ b/tools/extract_features.cpp @@ -14,7 +14,11 @@ #include "caffe/util/io.hpp" #include "caffe/vision_layers.hpp" -using namespace caffe; // NOLINT(build/namespaces) +using boost::shared_ptr; +using caffe::Blob; +using caffe::Caffe; +using caffe::Datum; +using caffe::Net; template int feature_extraction_pipeline(int argc, char** argv); @@ -62,7 +66,7 @@ int feature_extraction_pipeline(int argc, char** argv) { Caffe::set_phase(Caffe::TEST); arg_pos = 0; // the name of the executable - string pretrained_binary_proto(argv[++arg_pos]); + std::string pretrained_binary_proto(argv[++arg_pos]); // Expected prototxt contains at least one data layer such as // the layer data_layer_name and one feature blob such as the @@ -91,17 +95,17 @@ int feature_extraction_pipeline(int argc, char** argv) { top: "fc7" } */ - string feature_extraction_proto(argv[++arg_pos]); + std::string feature_extraction_proto(argv[++arg_pos]); shared_ptr > feature_extraction_net( new Net(feature_extraction_proto)); feature_extraction_net->CopyTrainedLayersFrom(pretrained_binary_proto); - string extract_feature_blob_names(argv[++arg_pos]); - vector blob_names; + std::string extract_feature_blob_names(argv[++arg_pos]); + std::vector blob_names; boost::split(blob_names, extract_feature_blob_names, boost::is_any_of(",")); - string save_feature_leveldb_names(argv[++arg_pos]); - vector leveldb_names; + std::string save_feature_leveldb_names(argv[++arg_pos]); + std::vector leveldb_names; boost::split(leveldb_names, save_feature_leveldb_names, boost::is_any_of(",")); CHECK_EQ(blob_names.size(), leveldb_names.size()) << @@ -118,7 +122,7 @@ int feature_extraction_pipeline(int argc, char** argv) { options.error_if_exists = true; options.create_if_missing = true; options.write_buffer_size = 268435456; - vector > feature_dbs; + std::vector > feature_dbs; for (size_t i = 0; i < num_features; ++i) { LOG(INFO)<< "Opening leveldb " << leveldb_names[i]; leveldb::DB* db; @@ -134,13 +138,13 @@ int feature_extraction_pipeline(int argc, char** argv) { LOG(ERROR)<< "Extacting Features"; Datum datum; - vector > feature_batches( + std::vector > feature_batches( num_features, shared_ptr(new leveldb::WriteBatch())); const int kMaxKeyStrLength = 100; char key_str[kMaxKeyStrLength]; - vector*> input_vec; - vector image_indices(num_features, 0); + std::vector*> input_vec; + std::vector image_indices(num_features, 0); for (int batch_index = 0; batch_index < num_mini_batches; ++batch_index) { feature_extraction_net->Forward(input_vec); for (int i = 0; i < num_features; ++i) { @@ -160,10 +164,10 @@ int feature_extraction_pipeline(int argc, char** argv) { for (int d = 0; d < dim_features; ++d) { datum.add_float_data(feature_blob_data[d]); } - string value; + std::string value; datum.SerializeToString(&value); snprintf(key_str, kMaxKeyStrLength, "%d", image_indices[i]); - feature_batches[i]->Put(string(key_str), value); + feature_batches[i]->Put(std::string(key_str), value); ++image_indices[i]; if (image_indices[i] % 1000 == 0) { feature_dbs[i]->Write(leveldb::WriteOptions(), -- 2.7.4