TEST(matching_image_collection, contiguousWithOverlap)
{
Pair_Set pairSet = exhaustivePairs(0);
EXPECT_EQ( 0, pairSet.size());
pairSet = contiguousWithOverlap(4,1);
EXPECT_TRUE( checkPairOrder(pairSet) );
EXPECT_EQ( 3, pairSet.size());
EXPECT_TRUE( pairSet.find(std::make_pair(0,1)) != pairSet.end() );
EXPECT_TRUE( pairSet.find(std::make_pair(1,2)) != pairSet.end() );
EXPECT_TRUE( pairSet.find(std::make_pair(2,3)) != pairSet.end() );
}
TEST(matching_image_collection, exhaustivePairs)
{
Pair_Set pairSet = exhaustivePairs(0);
EXPECT_EQ( 0, pairSet.size());
pairSet = exhaustivePairs(4);
EXPECT_TRUE( checkPairOrder(pairSet) );
EXPECT_EQ( 6, pairSet.size());
EXPECT_TRUE( pairSet.find(std::make_pair(0,1)) != pairSet.end() );
EXPECT_TRUE( pairSet.find(std::make_pair(0,2)) != pairSet.end() );
EXPECT_TRUE( pairSet.find(std::make_pair(0,3)) != pairSet.end() );
EXPECT_TRUE( pairSet.find(std::make_pair(1,2)) != pairSet.end() );
EXPECT_TRUE( pairSet.find(std::make_pair(1,3)) != pairSet.end() );
EXPECT_TRUE( pairSet.find(std::make_pair(2,3)) != pairSet.end() );
}
/// Use guided matching to find corresponding 2-view correspondences
void SfM_Data_Structure_Estimation_From_Known_Poses::match(
const SfM_Data & sfm_data,
const Pair_Set & pairs,
const std::shared_ptr<Regions_Provider> & regions_provider)
{
C_Progress_display my_progress_bar( pairs.size(), std::cout,
"Compute pairwise fundamental guided matching:\n" );
#ifdef OPENMVG_USE_OPENMP
#pragma omp parallel
#endif // OPENMVG_USE_OPENMP
for (Pair_Set::const_iterator it = pairs.begin(); it != pairs.end(); ++it)
{
#ifdef OPENMVG_USE_OPENMP
#pragma omp single nowait
#endif // OPENMVG_USE_OPENMP
{
// --
// Perform GUIDED MATCHING
// --
// Use the computed model to check valid correspondences
// - by considering geometric error and descriptor distance ratio.
std::vector<IndMatch> vec_corresponding_indexes;
const View * viewL = sfm_data.GetViews().at(it->first).get();
const Pose3 poseL = sfm_data.GetPoseOrDie(viewL);
const Intrinsics::const_iterator iterIntrinsicL = sfm_data.GetIntrinsics().find(viewL->id_intrinsic);
const View * viewR = sfm_data.GetViews().at(it->second).get();
const Pose3 poseR = sfm_data.GetPoseOrDie(viewR);
const Intrinsics::const_iterator iterIntrinsicR = sfm_data.GetIntrinsics().find(viewR->id_intrinsic);
Mat xL, xR;
PointsToMat(iterIntrinsicL->second.get(), regions_provider->regions_per_view.at(it->first)->GetRegionsPositions(), xL);
PointsToMat(iterIntrinsicR->second.get(), regions_provider->regions_per_view.at(it->second)->GetRegionsPositions(), xR);
const Mat34 P_L = iterIntrinsicL->second.get()->get_projective_equivalent(poseL);
const Mat34 P_R = iterIntrinsicR->second.get()->get_projective_equivalent(poseR);
const Mat3 F_lr = F_from_P(P_L, P_R);
const double thresholdF = 4.0;
#if defined(EXHAUSTIVE_MATCHING)
// Guided matching considering geometric error and descriptor distance ratio
geometry_aware::GuidedMatching
<Mat3, openMVG::fundamental::kernel::EpipolarDistanceError,
DescriptorT, L2_Vectorized<DescriptorT::bin_type> >(
F_lr, xL, desc_provider.at(it->first), xR, desc_provider.at(it->second),
Square(thresholdF), Square(0.8),
vec_corresponding_indexes);
#else
const Vec3 epipole2 = epipole_from_P(P_R, poseL);
const features::Regions * regions = regions_provider->regions_per_view.at(it->first).get();
if (regions->IsScalar())
{
// L2 Metric (Handle descriptor internal type)
if(regions->Type_id() == typeid(unsigned char).name())
{
geometry_aware::GuidedMatching_Fundamental_Fast<
openMVG::fundamental::kernel::EpipolarDistanceError,
L2_Vectorized<unsigned char> >
( F_lr,
epipole2,
regions_provider->regions_per_view.at(it->first).get(),
iterIntrinsicR->second.get()->w(), iterIntrinsicR->second.get()->h(),
regions_provider->regions_per_view.at(it->second).get(),
Square(thresholdF), Square(0.8),
vec_corresponding_indexes);
}
else
if(regions->Type_id() == typeid(float).name())
{
geometry_aware::GuidedMatching_Fundamental_Fast<
openMVG::fundamental::kernel::EpipolarDistanceError,
L2_Vectorized<float> >
( F_lr,
epipole2,
regions_provider->regions_per_view.at(it->first).get(),
iterIntrinsicR->second.get()->w(), iterIntrinsicR->second.get()->h(),
regions_provider->regions_per_view.at(it->second).get(),
Square(thresholdF), Square(0.8),
vec_corresponding_indexes);
}
else
if(regions->Type_id() == typeid(double).name())
{
geometry_aware::GuidedMatching_Fundamental_Fast<
openMVG::fundamental::kernel::EpipolarDistanceError,
L2_Vectorized<double> >
( F_lr,
epipole2,
regions_provider->regions_per_view.at(it->first).get(),
iterIntrinsicR->second.get()->w(), iterIntrinsicR->second.get()->h(),
regions_provider->regions_per_view.at(it->second).get(),
Square(thresholdF), Square(0.8),
vec_corresponding_indexes);
}
}
else
if (regions->IsBinary() && regions->Type_id() == typeid(unsigned char).name())
{
// Hamming metric
geometry_aware::GuidedMatching_Fundamental_Fast<
openMVG::fundamental::kernel::EpipolarDistanceError,
Hamming<unsigned char> >
( F_lr,
epipole2,
regions_provider->regions_per_view.at(it->first).get(),
iterIntrinsicR->second.get()->w(), iterIntrinsicR->second.get()->h(),
regions_provider->regions_per_view.at(it->second).get(),
Square(thresholdF), 0.8,
vec_corresponding_indexes);
}
#endif
#ifdef OPENMVG_USE_OPENMP
#pragma omp critical
#endif // OPENMVG_USE_OPENMP
{
++my_progress_bar;
for (size_t i = 0; i < vec_corresponding_indexes.size(); ++i)
putatives_matches[*it].push_back(vec_corresponding_indexes[i]);
}
}
}
}
/// Use guided matching to find corresponding 2-view correspondences
void SfM_Data_Structure_Estimation_From_Known_Poses::match(
const SfM_Data & sfm_data,
const Pair_Set & pairs,
const std::shared_ptr<Regions_Provider> & regions_provider)
{
C_Progress_display my_progress_bar( pairs.size(), std::cout,
"Compute pairwise fundamental guided matching:\n" );
#ifdef OPENMVG_USE_OPENMP
#pragma omp parallel
#endif // OPENMVG_USE_OPENMP
for (Pair_Set::const_iterator it = pairs.begin(); it != pairs.end(); ++it)
{
#ifdef OPENMVG_USE_OPENMP
#pragma omp single nowait
#endif // OPENMVG_USE_OPENMP
{
// --
// Perform GUIDED MATCHING
// --
// Use the computed model to check valid correspondences
// - by considering geometric error and descriptor distance ratio.
std::vector<IndMatch> vec_corresponding_indexes;
const View * viewL = sfm_data.GetViews().at(it->first).get();
const Pose3 poseL = sfm_data.GetPoseOrDie(viewL);
const Intrinsics::const_iterator iterIntrinsicL = sfm_data.GetIntrinsics().find(viewL->id_intrinsic);
const View * viewR = sfm_data.GetViews().at(it->second).get();
const Pose3 poseR = sfm_data.GetPoseOrDie(viewR);
const Intrinsics::const_iterator iterIntrinsicR = sfm_data.GetIntrinsics().find(viewR->id_intrinsic);
if (sfm_data.GetIntrinsics().count(viewL->id_intrinsic) != 0 ||
sfm_data.GetIntrinsics().count(viewR->id_intrinsic) != 0)
{
const Mat34 P_L = iterIntrinsicL->second.get()->get_projective_equivalent(poseL);
const Mat34 P_R = iterIntrinsicR->second.get()->get_projective_equivalent(poseR);
const Mat3 F_lr = F_from_P(P_L, P_R);
const double thresholdF = 4.0;
#if defined(EXHAUSTIVE_MATCHING)
geometry_aware::GuidedMatching
<Mat3, openMVG::fundamental::kernel::EpipolarDistanceError>
(
F_lr,
iterIntrinsicL->second.get(),
*regions_provider->regions_per_view.at(it->first),
iterIntrinsicR->second.get(),
*regions_provider->regions_per_view.at(it->second),
Square(thresholdF), Square(0.8),
vec_corresponding_indexes
);
#else
const Vec3 epipole2 = epipole_from_P(P_R, poseL);
const features::Regions * regions = regions_provider->regions_per_view.at(it->first).get();
geometry_aware::GuidedMatching_Fundamental_Fast
<openMVG::fundamental::kernel::EpipolarDistanceError>
(
F_lr,
epipole2,
iterIntrinsicL->second.get(),
*regions_provider->regions_per_view.at(it->first),
iterIntrinsicR->second.get(),
*regions_provider->regions_per_view.at(it->second),
iterIntrinsicR->second->w(), iterIntrinsicR->second->h(),
Square(thresholdF), Square(0.8),
vec_corresponding_indexes
);
#endif
#ifdef OPENMVG_USE_OPENMP
#pragma omp critical
#endif // OPENMVG_USE_OPENMP
{
++my_progress_bar;
for (size_t i = 0; i < vec_corresponding_indexes.size(); ++i)
putatives_matches[*it].push_back(vec_corresponding_indexes[i]);
}
}
}
}
}
void Match
(
const sfm::SfM_Data & sfm_data,
const sfm::Regions_Provider & regions_provider,
const Pair_Set & pairs,
float fDistRatio,
PairWiseMatchesContainer & map_PutativesMatches // the pairwise photometric corresponding points
)
{
C_Progress_display my_progress_bar( pairs.size() );
// Collect used view indexes
std::set<IndexT> used_index;
// Sort pairs according the first index to minimize later memory swapping
using Map_vectorT = std::map<IndexT, std::vector<IndexT>>;
Map_vectorT map_Pairs;
for (Pair_Set::const_iterator iter = pairs.begin(); iter != pairs.end(); ++iter)
{
map_Pairs[iter->first].push_back(iter->second);
used_index.insert(iter->first);
used_index.insert(iter->second);
}
using BaseMat = Eigen::Matrix<ScalarT, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>;
// Init the cascade hasher
CascadeHasher cascade_hasher;
if (!used_index.empty())
{
const IndexT I = *used_index.begin();
std::shared_ptr<features::Regions> regionsI = regions_provider.get(I);
const size_t dimension = regionsI.get()->DescriptorLength();
cascade_hasher.Init(dimension);
}
std::map<IndexT, HashedDescriptions> hashed_base_;
// Compute the zero mean descriptor that will be used for hashing (one for all the image regions)
Eigen::VectorXf zero_mean_descriptor;
{
Eigen::MatrixXf matForZeroMean;
for (int i =0; i < used_index.size(); ++i)
{
std::set<IndexT>::const_iterator iter = used_index.begin();
std::advance(iter, i);
const IndexT I = *iter;
std::shared_ptr<features::Regions> regionsI = regions_provider.get(I);
const ScalarT * tabI =
reinterpret_cast<const ScalarT*>(regionsI.get()->DescriptorRawData());
const size_t dimension = regionsI.get()->DescriptorLength();
if (i==0)
{
matForZeroMean.resize(used_index.size(), dimension);
matForZeroMean.fill(0.0f);
}
if (regionsI.get()->RegionCount() > 0)
{
Eigen::Map<BaseMat> mat_I( (ScalarT*)tabI, regionsI.get()->RegionCount(), dimension);
matForZeroMean.row(i) = CascadeHasher::GetZeroMeanDescriptor(mat_I);
}
}
zero_mean_descriptor = CascadeHasher::GetZeroMeanDescriptor(matForZeroMean);
}
// Index the input regions
#ifdef OPENMVG_USE_OPENMP
#pragma omp parallel for schedule(dynamic)
#endif
for (int i =0; i < used_index.size(); ++i)
{
std::set<IndexT>::const_iterator iter = used_index.begin();
std::advance(iter, i);
const IndexT I = *iter;
std::shared_ptr<features::Regions> regionsI = regions_provider.get(I);
const ScalarT * tabI =
reinterpret_cast<const ScalarT*>(regionsI.get()->DescriptorRawData());
const size_t dimension = regionsI.get()->DescriptorLength();
Eigen::Map<BaseMat> mat_I( (ScalarT*)tabI, regionsI.get()->RegionCount(), dimension);
HashedDescriptions hashed_description = cascade_hasher.CreateHashedDescriptions(mat_I,
zero_mean_descriptor);
#ifdef OPENMVG_USE_OPENMP
#pragma omp critical
#endif
{
hashed_base_[I] = std::move(hashed_description);
}
}
// Perform matching between all the pairs
for (Map_vectorT::const_iterator iter = map_Pairs.begin();
iter != map_Pairs.end(); ++iter)
{
const IndexT I = iter->first;
const std::vector<IndexT> & indexToCompare = iter->second;
std::shared_ptr<features::Regions> regionsI = regions_provider.get(I);
if (regionsI.get()->RegionCount() == 0)
{
my_progress_bar += indexToCompare.size();
continue;
}
const std::vector<features::PointFeature> pointFeaturesI = regionsI.get()->GetRegionsPositions();
const ScalarT * tabI =
reinterpret_cast<const ScalarT*>(regionsI.get()->DescriptorRawData());
const size_t dimension = regionsI.get()->DescriptorLength();
Eigen::Map<BaseMat> mat_I( (ScalarT*)tabI, regionsI.get()->RegionCount(), dimension);
#ifdef OPENMVG_USE_OPENMP
#pragma omp parallel for schedule(dynamic)
#endif
for (int j = 0; j < (int)indexToCompare.size(); ++j)
{
size_t J = indexToCompare[j];
std::shared_ptr<features::Regions> regionsJ = regions_provider.get(J);
if (regionsI.get()->Type_id() != regionsJ.get()->Type_id())
{
#ifdef OPENMVG_USE_OPENMP
#pragma omp critical
#endif
++my_progress_bar;
continue;
}
// Matrix representation of the query input data;
const ScalarT * tabJ = reinterpret_cast<const ScalarT*>(regionsJ.get()->DescriptorRawData());
Eigen::Map<BaseMat> mat_J( (ScalarT*)tabJ, regionsJ.get()->RegionCount(), dimension);
IndMatches pvec_indices;
using ResultType = typename Accumulator<ScalarT>::Type;
std::vector<ResultType> pvec_distances;
pvec_distances.reserve(regionsJ.get()->RegionCount() * 2);
pvec_indices.reserve(regionsJ.get()->RegionCount() * 2);
// Match the query descriptors to the database
cascade_hasher.Match_HashedDescriptions<BaseMat, ResultType>(
hashed_base_[J], mat_J,
hashed_base_[I], mat_I,
&pvec_indices, &pvec_distances);
std::vector<int> vec_nn_ratio_idx;
// Filter the matches using a distance ratio test:
// The probability that a match is correct is determined by taking
// the ratio of distance from the closest neighbor to the distance
// of the second closest.
matching::NNdistanceRatio(
pvec_distances.begin(), // distance start
pvec_distances.end(), // distance end
2, // Number of neighbor in iterator sequence (minimum required 2)
vec_nn_ratio_idx, // output (indices that respect the distance Ratio)
Square(fDistRatio));
matching::IndMatches vec_putative_matches;
vec_putative_matches.reserve(vec_nn_ratio_idx.size());
for (size_t k=0; k < vec_nn_ratio_idx.size(); ++k)
{
const size_t index = vec_nn_ratio_idx[k];
vec_putative_matches.emplace_back(pvec_indices[index*2].j_, pvec_indices[index*2].i_);
}
// Remove duplicates
matching::IndMatch::getDeduplicated(vec_putative_matches);
// Remove matches that have the same (X,Y) coordinates
const std::vector<features::PointFeature> pointFeaturesJ = regionsJ.get()->GetRegionsPositions();
matching::IndMatchDecorator<float> matchDeduplicator(vec_putative_matches,
pointFeaturesI, pointFeaturesJ);
matchDeduplicator.getDeduplicated(vec_putative_matches);
#ifdef OPENMVG_USE_OPENMP
#pragma omp critical
#endif
{
++my_progress_bar;
if (!vec_putative_matches.empty())
{
map_PutativesMatches.insert( make_pair( make_pair(I,J), std::move(vec_putative_matches) ));
}
}
}
}
}
int main(int argc, char ** argv)
{
CmdLine cmd;
std::string sSfM_Data_Filename;
std::string sMatchesDir;
std::string sMatchFile;
std::string sOutDir = "";
cmd.add( make_option('i', sSfM_Data_Filename, "input_file") );
cmd.add( make_option('d', sMatchesDir, "matchdir") );
cmd.add( make_option('m', sMatchFile, "matchfile") );
cmd.add( make_option('o', sOutDir, "outdir") );
try {
if (argc == 1) throw std::string("Invalid command line parameter.");
cmd.process(argc, argv);
} catch(const std::string& s) {
std::cerr << "Export pairwise matches.\nUsage: " << argv[0] << "\n"
<< "[-i|--input_file file] path to a SfM_Data scene\n"
<< "[-d|--matchdir path]\n"
<< "[-m|--sMatchFile filename]\n"
<< "[-o|--outdir path]\n"
<< std::endl;
std::cerr << s << std::endl;
return EXIT_FAILURE;
}
if (sOutDir.empty()) {
std::cerr << "\nIt is an invalid output directory" << std::endl;
return EXIT_FAILURE;
}
//---------------------------------------
// Read SfM Scene (image view names)
//---------------------------------------
SfM_Data sfm_data;
if (!Load(sfm_data, sSfM_Data_Filename, ESfM_Data(VIEWS|INTRINSICS))) {
std::cerr << std::endl
<< "The input SfM_Data file \""<< sSfM_Data_Filename << "\" cannot be read." << std::endl;
return EXIT_FAILURE;
}
//---------------------------------------
// Load SfM Scene regions
//---------------------------------------
// Init the regions_type from the image describer file (used for image regions extraction)
const std::string sImage_describer = stlplus::create_filespec(sMatchesDir, "image_describer", "json");
std::unique_ptr<Regions> regions_type = Init_region_type_from_file(sImage_describer);
if (!regions_type)
{
std::cerr << "Invalid: "
<< sImage_describer << " regions type file." << std::endl;
return EXIT_FAILURE;
}
// Read the features
std::shared_ptr<Features_Provider> feats_provider = std::make_shared<Features_Provider>();
if (!feats_provider->load(sfm_data, sMatchesDir, regions_type)) {
std::cerr << std::endl
<< "Invalid features." << std::endl;
return EXIT_FAILURE;
}
std::shared_ptr<Matches_Provider> matches_provider = std::make_shared<Matches_Provider>();
if (!matches_provider->load(sfm_data, sMatchFile)) {
std::cerr << std::endl
<< "Invalid matches file." << std::endl;
return EXIT_FAILURE;
}
// ------------
// For each pair, export the matches
// ------------
stlplus::folder_create(sOutDir);
std::cout << "\n Export pairwise matches" << std::endl;
const Pair_Set pairs = matches_provider->getPairs();
C_Progress_display my_progress_bar( pairs.size() );
for (Pair_Set::const_iterator iter = pairs.begin();
iter != pairs.end();
++iter, ++my_progress_bar)
{
const size_t I = iter->first;
const size_t J = iter->second;
const View * view_I = sfm_data.GetViews().at(I).get();
const std::string sView_I= stlplus::create_filespec(sfm_data.s_root_path,
view_I->s_Img_path);
const View * view_J = sfm_data.GetViews().at(J).get();
const std::string sView_J= stlplus::create_filespec(sfm_data.s_root_path,
view_J->s_Img_path);
const std::pair<size_t, size_t>
dimImage_I = std::make_pair(view_I->ui_width, view_I->ui_height),
dimImage_J = std::make_pair(view_J->ui_width, view_J->ui_height);
svgDrawer svgStream( dimImage_I.first + dimImage_J.first, max(dimImage_I.second, dimImage_J.second));
svgStream.drawImage(sView_I,
dimImage_I.first,
dimImage_I.second);
svgStream.drawImage(sView_J,
dimImage_J.first,
dimImage_J.second, dimImage_I.first);
const vector<IndMatch> & vec_FilteredMatches = matches_provider->_pairWise_matches.at(*iter);
if (!vec_FilteredMatches.empty()) {
const PointFeatures & vec_feat_I = feats_provider->getFeatures(view_I->id_view);
const PointFeatures & vec_feat_J = feats_provider->getFeatures(view_J->id_view);
//-- Draw link between features :
for (size_t i=0; i< vec_FilteredMatches.size(); ++i) {
const PointFeature & imaA = vec_feat_I[vec_FilteredMatches[i]._i];
const PointFeature & imaB = vec_feat_J[vec_FilteredMatches[i]._j];
// Compute a flashy colour for the correspondence
unsigned char r,g,b;
hslToRgb( (rand()%360) / 360., 1.0, .5, r, g, b);
std::ostringstream osCol;
osCol << "rgb(" << (int)r <<',' << (int)g << ',' << (int)b <<")";
svgStream.drawLine(imaA.x(), imaA.y(),
imaB.x()+dimImage_I.first, imaB.y(), svgStyle().stroke(osCol.str(), 2.0));
}
//-- Draw features (in two loop, in order to have the features upper the link, svg layer order):
for (size_t i=0; i< vec_FilteredMatches.size(); ++i) {
const PointFeature & imaA = vec_feat_I[vec_FilteredMatches[i]._i];
const PointFeature & imaB = vec_feat_J[vec_FilteredMatches[i]._j];
svgStream.drawCircle(imaA.x(), imaA.y(), 3.0,
svgStyle().stroke("yellow", 2.0));
svgStream.drawCircle(imaB.x() + dimImage_I.first, imaB.y(), 3.0,
svgStyle().stroke("yellow", 2.0));
}
}
std::ostringstream os;
os << stlplus::folder_append_separator(sOutDir)
<< iter->first << "_" << iter->second
<< "_" << vec_FilteredMatches.size() << "_.svg";
ofstream svgFile( os.str().c_str() );
svgFile << svgStream.closeSvgFile().str();
svgFile.close();
}
return EXIT_SUCCESS;
}
int main(int argc, char **argv)
{
using namespace std;
std::cout << std::endl
<< "-----------------------------------------------------------\n"
<< "Frustum filtering:\n"
<< "-----------------------------------------------------------\n"
<< "Compute camera cones that share some putative visual content.\n"
<< "------------------------------------------------------------"
<< std::endl;
CmdLine cmd;
std::string sSfM_Data_Filename;
std::string sOutFile;
double z_near = -1.;
double z_far = -1.;
cmd.add( make_option('i', sSfM_Data_Filename, "input_file") );
cmd.add( make_option('o', sOutFile, "output_file") );
cmd.add( make_option('n', z_near, "z_near") );
cmd.add( make_option('f', z_far, "z_far") );
try {
if (argc == 1) throw std::string("Invalid parameter.");
cmd.process(argc, argv);
} catch (const std::string& s) {
std::cerr << "Usage: " << argv[0] << '\n'
<< "[-i|--input_file] path to a SfM_Data scene\n"
<< "[-o|--output_file] filename of the output pair file\n"
<< "[-n|--z_near] 'optional' distance of the near camera plane\n"
<< "[-f|--z_far] 'optional' distance of the far camera plane\n"
<< std::endl;
std::cerr << s << std::endl;
return EXIT_FAILURE;
}
// Assert that we can create the output directory
if (!stlplus::folder_exists( stlplus::folder_part(sOutFile)) &&
!stlplus::folder_create( stlplus::folder_part(sOutFile)))
return EXIT_FAILURE;
// Load input SfM_Data scene
SfM_Data sfm_data;
if (!Load(sfm_data, sSfM_Data_Filename, ESfM_Data(ALL))) {
std::cerr << std::endl
<< "The input SfM_Data file \""<< sSfM_Data_Filename << "\" cannot be read." << std::endl;
return EXIT_FAILURE;
}
openMVG::system::Timer timer;
const Pair_Set pairs = BuildPairsFromFrustumsIntersections(sfm_data, z_near, z_far, stlplus::folder_part(sOutFile));
/*const Pair_Set pairs = BuildPairsFromStructureObservations(sfm_data); */
std::cout << "#pairs: " << pairs.size() << std::endl;
std::cout << std::endl << " Pair filtering took (s): " << timer.elapsed() << std::endl;
// export pairs on disk
if (savePairs(sOutFile, pairs))
{
return EXIT_SUCCESS;
}
return EXIT_FAILURE;
}
void Matcher_Regions_AllInMemory::Match(
const sfm::SfM_Data & sfm_data,
const std::shared_ptr<sfm::Regions_Provider> & regions_provider,
const Pair_Set & pairs,
PairWiseMatches & map_PutativesMatches)const // the pairwise photometric corresponding points
{
#ifdef OPENMVG_USE_OPENMP
std::cout << "Using the OPENMP thread interface" << std::endl;
#endif
const bool b_multithreaded_pair_search = (eMatcherType_ == CASCADE_HASHING_L2);
// -> set to true for CASCADE_HASHING_L2, since OpenMP instructions are not used in this matcher
C_Progress_display my_progress_bar( pairs.size() );
// Sort pairs according the first index to minimize the MatcherT build operations
typedef std::map<size_t, std::vector<size_t> > Map_vectorT;
Map_vectorT map_Pairs;
for (Pair_Set::const_iterator iter = pairs.begin(); iter != pairs.end(); ++iter)
{
map_Pairs[iter->first].push_back(iter->second);
}
// Perform matching between all the pairs
for (Map_vectorT::const_iterator iter = map_Pairs.begin();
iter != map_Pairs.end(); ++iter)
{
const size_t I = iter->first;
const std::vector<size_t> & indexToCompare = iter->second;
const features::Regions & regionsI = *regions_provider->regions_per_view.at(I).get();
if (regionsI.RegionCount() == 0)
{
my_progress_bar += indexToCompare.size();
continue;
}
// Initialize the matching interface
matching::Matcher_Regions_Database matcher(eMatcherType_, regionsI);
#ifdef OPENMVG_USE_OPENMP
#pragma omp parallel for schedule(dynamic) if(b_multithreaded_pair_search)
#endif
for (int j = 0; j < (int)indexToCompare.size(); ++j)
{
const size_t J = indexToCompare[j];
const features::Regions ®ionsJ = *regions_provider->regions_per_view.at(J).get();
if (regionsJ.RegionCount() == 0
|| regionsI.Type_id() != regionsJ.Type_id())
{
#ifdef OPENMVG_USE_OPENMP
#pragma omp critical
#endif
++my_progress_bar;
continue;
}
IndMatches vec_putatives_matches;
matcher.Match(f_dist_ratio_, regionsJ, vec_putatives_matches);
#ifdef OPENMVG_USE_OPENMP
#pragma omp critical
#endif
{
++my_progress_bar;
if (!vec_putatives_matches.empty())
{
map_PutativesMatches.insert( make_pair( make_pair(I,J), std::move(vec_putatives_matches) ));
}
}
}
}
}