7 #include "boost/scoped_ptr.hpp"
8 #include "gflags/gflags.h"
9 #include "glog/logging.h"
11 #include "caffe/proto/caffe.pb.h"
12 #include "caffe/util/db.hpp"
13 #include "caffe/util/io.hpp"
15 using namespace caffe; // NOLINT(build/namespaces)
19 using boost::scoped_ptr;
21 DEFINE_string(backend, "lmdb",
22 "The backend {leveldb, lmdb} containing the images");
24 int main(int argc, char** argv) {
25 ::google::InitGoogleLogging(argv[0]);
28 #ifndef GFLAGS_GFLAGS_H_
29 namespace gflags = google;
32 gflags::SetUsageMessage("Compute the mean_image of a set of images given by"
35 " compute_image_mean [FLAGS] INPUT_DB [OUTPUT_FILE]\n");
37 gflags::ParseCommandLineFlags(&argc, &argv, true);
39 if (argc < 2 || argc > 3) {
40 gflags::ShowUsageWithFlagsRestrict(argv[0], "tools/compute_image_mean");
44 scoped_ptr<db::DB> db(db::GetDB(FLAGS_backend));
45 db->Open(argv[1], db::READ);
46 scoped_ptr<db::Cursor> cursor(db->NewCursor());
52 datum.ParseFromString(cursor->value());
54 if (DecodeDatumNative(&datum)) {
55 LOG(INFO) << "Decoding Datum";
59 sum_blob.set_channels(datum.channels());
60 sum_blob.set_height(datum.height());
61 sum_blob.set_width(datum.width());
62 const int data_size = datum.channels() * datum.height() * datum.width();
63 int size_in_datum = std::max<int>(datum.data().size(),
64 datum.float_data_size());
65 for (int i = 0; i < size_in_datum; ++i) {
66 sum_blob.add_data(0.);
68 LOG(INFO) << "Starting Iteration";
69 while (cursor->valid()) {
71 datum.ParseFromString(cursor->value());
72 DecodeDatumNative(&datum);
74 const std::string& data = datum.data();
75 size_in_datum = std::max<int>(datum.data().size(),
76 datum.float_data_size());
77 CHECK_EQ(size_in_datum, data_size) << "Incorrect data field size " <<
79 if (data.size() != 0) {
80 CHECK_EQ(data.size(), size_in_datum);
81 for (int i = 0; i < size_in_datum; ++i) {
82 sum_blob.set_data(i, sum_blob.data(i) + (uint8_t)data[i]);
85 CHECK_EQ(datum.float_data_size(), size_in_datum);
86 for (int i = 0; i < size_in_datum; ++i) {
87 sum_blob.set_data(i, sum_blob.data(i) +
88 static_cast<float>(datum.float_data(i)));
92 if (count % 10000 == 0) {
93 LOG(INFO) << "Processed " << count << " files.";
98 if (count % 10000 != 0) {
99 LOG(INFO) << "Processed " << count << " files.";
101 for (int i = 0; i < sum_blob.data_size(); ++i) {
102 sum_blob.set_data(i, sum_blob.data(i) / count);
106 LOG(INFO) << "Write to " << argv[2];
107 WriteProtoToBinaryFile(sum_blob, argv[2]);
109 const int channels = sum_blob.channels();
110 const int dim = sum_blob.height() * sum_blob.width();
111 std::vector<float> mean_values(channels, 0.0);
112 LOG(INFO) << "Number of channels: " << channels;
113 for (int c = 0; c < channels; ++c) {
114 for (int i = 0; i < dim; ++i) {
115 mean_values[c] += sum_blob.data(dim * c + i);
117 LOG(INFO) << "mean_value channel [" << c << "]:" << mean_values[c] / dim;
120 LOG(FATAL) << "This tool requires OpenCV; compile with USE_OPENCV.";