compute_bow_simple.cxx File Reference

#include "tests_config.hpp"
#include <config.hpp>
#include <utils/filesystem.hpp>
#include <utils/numerics.hpp>
#include <utils/dataset.hpp>
#include <utils/vision.hpp>
#include <utils/logger.hpp>
#include <search/bag_of_words/bag_of_words.hpp>
#include <iostream>
#include <sstream>

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Functions
_INITIALIZE_EASYLOGGINGPP int	main (int argc, char *argv[])

Function Documentation

_INITIALIZE_EASYLOGGINGPP int main	(	int	argc,
		char *	argv[]
	)

Definition at line 23 of file compute_bow_simple.cxx.

References vision::compute_bow_feature(), vision::construct_descriptor_matcher(), filesystem::create_file_directory(), filesystem::file_exists(), filesystem::load_cvmat(), s_oxfordmini_data_dir, s_oxfordmini_database_location, BagOfWords::save(), numerics::sparsify(), BagOfWords::train(), BagOfWords::vocabulary(), and filesystem::write_sparse_vector().

                                 {
#if ENABLE_MULTITHREADING && ENABLE_MPI
        MPI::Init(argc, argv);
        int rank = MPI::COMM_WORLD.Get_rank();
#endif

        SimpleDataset simple_dataset(s_oxfordmini_data_dir, s_oxfordmini_database_location);
        LINFO << simple_dataset;

        BagOfWords bow;
        
        std::shared_ptr<BagOfWords::TrainParams> train_params = std::make_shared<BagOfWords::TrainParams>();
        const std::vector<  std::shared_ptr<const Image> > &all_images = simple_dataset.random_images(128);
        bow.train(simple_dataset, train_params, all_images);
        
#if ENABLE_MULTITHREADING && ENABLE_MPI
        if(rank == 0) {
#endif

        std::stringstream vocab_output_file;
        vocab_output_file << simple_dataset.location() << "/vocabulary/" << train_params->numClusters << ".vocab";
        bow.save(vocab_output_file.str());
        
#if ENABLE_MULTITHREADING && ENABLE_OPENMP
        uint32_t num_threads = omp_get_max_threads();
        std::vector< cv::Ptr<cv::DescriptorMatcher> > matchers;
        for(uint32_t i=0; i<num_threads; i++) {
                matchers.push_back(vision::construct_descriptor_matcher(bow.vocabulary()));
        }
#pragma omp parallel for schedule(dynamic)
#else
        const cv::Ptr<cv::DescriptorMatcher> &matcher = vision::construct_descriptor_matcher(bow.vocabulary());
#endif

        for (int64_t i = 0; i < (int64_t)all_images.size(); i++) {

#if ENABLE_MULTITHREADING && ENABLE_OPENMP
                const cv::Ptr<cv::DescriptorMatcher> &matcher = matchers[omp_get_thread_num()];
#endif
                const std::string &sift_descriptor_location = simple_dataset.location(all_images[i]->feature_path("descriptors"));
                const std::string &bow_descriptor_location = simple_dataset.location(all_images[i]->feature_path("bow_descriptors"));

                cv::Mat descriptors, bow_descriptors, descriptorsf;
                if (!filesystem::file_exists(sift_descriptor_location)) continue;
                if (!filesystem::load_cvmat(sift_descriptor_location, descriptors)) continue;
                descriptors.convertTo(descriptorsf, CV_32FC1);
                filesystem::create_file_directory(bow_descriptor_location);

                if (!vision::compute_bow_feature(descriptorsf, matcher, bow_descriptors, nullptr)) continue;
                const std::vector< std::pair<uint32_t, float> > &bow_descriptors_sparse = numerics::sparsify(bow_descriptors);
                filesystem::write_sparse_vector(bow_descriptor_location, bow_descriptors_sparse);
                
                LINFO << "Wrote " << bow_descriptor_location;
        }
#if ENABLE_MULTITHREADING && ENABLE_MPI
        }
        MPI::Finalize();
#endif
        return 0;
}