void extractFeaturesAndDescriptors(
const std::vector<std::string> & vec_fileNames, // input filenames
const std::string & sOutDir, // Output directory where features and descriptor will be saved
std::vector<std::pair<size_t, size_t> > & vec_imagesSize) // input image size (w,h)
{
vec_imagesSize.resize(vec_fileNames.size());
Image<RGBColor> imageRGB;
Image<unsigned char> imageGray;
C_Progress_display my_progress_bar( vec_fileNames.size() );
for(size_t i=0; i < vec_fileNames.size(); ++i) {
KeypointSetT kpSet;
std::string sFeat = stlplus::create_filespec(sOutDir,
stlplus::basename_part(vec_fileNames[i]), "feat");
std::string sDesc = stlplus::create_filespec(sOutDir,
stlplus::basename_part(vec_fileNames[i]), "desc");
//Test if descriptor and feature was already computed
if (stlplus::file_exists(sFeat) && stlplus::file_exists(sDesc)) {
if (ReadImage(vec_fileNames[i].c_str(), &imageRGB)) {
vec_imagesSize[i] = make_pair(imageRGB.Width(), imageRGB.Height());
}
else {
ReadImage(vec_fileNames[i].c_str(), &imageGray);
vec_imagesSize[i] = make_pair(imageGray.Width(), imageGray.Height());
}
}
else { //Not already computed, so compute and save
if (!ReadImage(vec_fileNames[i].c_str(), &imageGray))
continue;
// Compute features and descriptors and export them to file
ComputeCVFeatAndDesc<DescriptorT, cvFeature2DInterfaceT>(imageGray, kpSet.features(), kpSet.descriptors());
kpSet.saveToBinFile(sFeat, sDesc);
vec_imagesSize[i] = make_pair(imageGray.Width(), imageGray.Height());
}
++my_progress_bar;
}
}
int main(int argc, char **argv)
{
CmdLine cmd;
std::string sImaDirectory;
std::string sOutDir = "";
std::string sGeometricModel = "f";
float fDistRatio = .6f;
bool bOctMinus1 = false;
float dPeakThreshold = 0.04f;
int sequentialLimit = 0;
cmd.add( make_option('i', sImaDirectory, "imadir") );
cmd.add( make_option('o', sOutDir, "outdir") );
cmd.add( make_option('r', fDistRatio, "distratio") );
cmd.add( make_option('s', bOctMinus1, "octminus1") );
cmd.add( make_option('p', dPeakThreshold, "peakThreshold") );
cmd.add( make_option('g', sGeometricModel, "geometricModel") );
cmd.add(make_option('l', sequentialLimit, "sequentialLimit"));//
try {
if (argc == 1) throw std::string("Invalid command line parameter.");
cmd.process(argc, argv);
} catch(const std::string& s) {
std::cerr << "Usage: " << argv[0] << '\n'
<< "[-i|--imadir path] \n"
<< "[-o|--outdir path] \n"
<< "\n[Optional]\n"
<< "[-r|--distratio 0.6] \n"
<< "[-s|--octminus1 0 or 1] \n"
<< "[-p|--peakThreshold 0.04 -> 0.01] \n"
<< "[-g|--geometricModel f, e or h] \n"
<< "[-l|--sequentialLimit 1 or greater]"
<< std::endl;
std::cerr << s << std::endl;
return EXIT_FAILURE;
}
std::cout << " You called : " <<std::endl
<< argv[0] << std::endl
<< "--imadir " << sImaDirectory << std::endl
<< "--outdir " << sOutDir << std::endl
<< "--distratio " << fDistRatio << std::endl
<< "--octminus1 " << bOctMinus1 << std::endl
<< "--peakThreshold " << dPeakThreshold << std::endl
<< "--geometricModel " << sGeometricModel << std::endl
<< "--sequentialLimit " << sequentialLimit << std::endl;
if (sOutDir.empty()) {
std::cerr << "\nIt is an invalid output directory" << std::endl;
return EXIT_FAILURE;
}
eGeometricModel eGeometricModelToCompute = FUNDAMENTAL_MATRIX;
std::string sGeometricMatchesFilename = "";
switch(sGeometricModel[0])
{
case 'f': case 'F':
eGeometricModelToCompute = FUNDAMENTAL_MATRIX;
sGeometricMatchesFilename = "matches.f.txt";
break;
case 'e': case 'E':
eGeometricModelToCompute = ESSENTIAL_MATRIX;
sGeometricMatchesFilename = "matches.e.txt";
break;
case 'h': case 'H':
eGeometricModelToCompute = HOMOGRAPHY_MATRIX;
sGeometricMatchesFilename = "matches.h.txt";
break;
default:
std::cerr << "Unknown geometric model" << std::endl;
return EXIT_FAILURE;
}
// -----------------------------
// a. List images
// b. Compute features and descriptors
// c. Compute putative descriptor matches
// d. Geometric filtering of putative matches
// e. Export some statistics
// -----------------------------
// Create output dir
if (!stlplus::folder_exists(sOutDir))
stlplus::folder_create( sOutDir );
//---------------------------------------
// a. List images
//---------------------------------------
std::string sListsFile = stlplus::create_filespec(sOutDir, "lists.txt" );
if (!stlplus::is_file(sListsFile)) {
std::cerr << std::endl
<< "The input file \""<< sListsFile << "\" is missing" << std::endl;
return false;
}
std::vector<openMVG::SfMIO::CameraInfo> vec_camImageName;
std::vector<openMVG::SfMIO::IntrinsicCameraInfo> vec_focalGroup;
// if (!openMVG::SfMIO::loadImageList( vec_camImageName,
// vec_focalGroup,
// sListsFile) )
if (!readImageList(vec_camImageName, vec_focalGroup, sListsFile))
{
std::cerr << "\nEmpty image list." << std::endl;
return false;
}
if (eGeometricModelToCompute == ESSENTIAL_MATRIX)
{
//-- In the case of the essential matrix we check if only one K matrix is present.
//-- Due to the fact that the generic framework allows only one K matrix for the
// robust essential matrix estimation in image collection.
std::vector<openMVG::SfMIO::IntrinsicCameraInfo>::iterator iterF =
std::unique(vec_focalGroup.begin(), vec_focalGroup.end(), testIntrinsicsEquality);
vec_focalGroup.resize( std::distance(vec_focalGroup.begin(), iterF) );
if (vec_focalGroup.size() == 1) {
// Set all the intrinsic ID to 0
for (size_t i = 0; i < vec_camImageName.size(); ++i)
vec_camImageName[i].m_intrinsicId = 0;
}
else {
std::cerr << "There is more than one focal group in the lists.txt file." << std::endl
<< "Only one focal group is supported for the image collection robust essential matrix estimation." << std::endl;
return EXIT_FAILURE;
}
}
//-- Two alias to ease access to image filenames and image sizes
std::vector<std::string> vec_fileNames;
std::vector<std::pair<size_t, size_t> > vec_imagesSize;
for ( std::vector<openMVG::SfMIO::CameraInfo>::const_iterator
iter_camInfo = vec_camImageName.begin();
iter_camInfo != vec_camImageName.end();
iter_camInfo++ )
{
vec_imagesSize.push_back( std::make_pair( vec_focalGroup[iter_camInfo->m_intrinsicId].m_w,
vec_focalGroup[iter_camInfo->m_intrinsicId].m_h ) );
vec_fileNames.push_back( stlplus::create_filespec( sImaDirectory, iter_camInfo->m_sImageName) );
}
//---------------------------------------
// b. Compute features and descriptor
// - extract sift features and descriptor
// - if keypoints already computed, re-load them
// - else save features and descriptors on disk
//---------------------------------------
typedef Descriptor<unsigned char, 128> DescriptorT;
typedef SIOPointFeature FeatureT;
typedef std::vector<FeatureT> FeatsT;
typedef vector<DescriptorT > DescsT;
typedef KeypointSet<FeatsT, DescsT > KeypointSetT;
{
std::cout << "\n\nEXTRACT FEATURES" << std::endl;
vec_imagesSize.resize(vec_fileNames.size());
Image<unsigned char> imageGray;
C_Progress_display my_progress_bar(vec_fileNames.size());
for (size_t i = 0; i < vec_fileNames.size(); ++i) {
std::string sFeat = stlplus::create_filespec(sOutDir,
stlplus::basename_part(vec_fileNames[i]), "feat");
std::string sDesc = stlplus::create_filespec(sOutDir,
stlplus::basename_part(vec_fileNames[i]), "desc");
//If descriptors or features file are missing, compute them
if (!stlplus::file_exists(sFeat) || !stlplus::file_exists(sDesc)) {
if (!ReadImage(vec_fileNames[i].c_str(), &imageGray))
continue;
// Compute features and descriptors and export them to files
KeypointSetT kpSet;
SIFTDetector(imageGray,
kpSet.features(), kpSet.descriptors(),
bOctMinus1, true, dPeakThreshold);
kpSet.saveToBinFile(sFeat, sDesc);
}
++my_progress_bar;
}
}
//---------------------------------------
// c. Compute putative descriptor matches
// - L2 descriptor matching
// - Keep correspondences only if NearestNeighbor ratio is ok
//---------------------------------------
PairWiseMatches map_PutativesMatches;
// Define the matcher and the used metric (Squared L2)
// ANN matcher could be defined as follow:
typedef flann::L2<DescriptorT::bin_type> MetricT;
typedef ArrayMatcher_Kdtree_Flann<DescriptorT::bin_type, MetricT> MatcherT;
// Brute force matcher can be defined as following:
//typedef L2_Vectorized<DescriptorT::bin_type> MetricT;
//typedef ArrayMatcherBruteForce<DescriptorT::bin_type, MetricT> MatcherT;
// If the matches already exists, reload them
if (stlplus::file_exists(sOutDir + "/matches.putative.txt"))
{
PairedIndMatchImport(sOutDir + "/matches.putative.txt", map_PutativesMatches);
std::cout << std::endl << "PUTATIVE MATCHES -- PREVIOUS RESULTS LOADED" << std::endl;
}
else // Compute the putatives matches
{
//Matcher_AllInMemory<KeypointSetT, MatcherT> collectionMatcher(fDistRatio);
SparseMatcher<KeypointSetT, MatcherT> collectionMatcher(fDistRatio, sequentialLimit);
if (collectionMatcher.loadData(vec_fileNames, sOutDir))
{
std::cout << std::endl << "PUTATIVE MATCHES" << std::endl;
collectionMatcher.Match(vec_fileNames, map_PutativesMatches);
//---------------------------------------
//-- Export putative matches
//---------------------------------------
std::ofstream file(std::string(sOutDir + "/matches.putative.txt").c_str());
if (file.is_open())
PairedIndMatchToStream(map_PutativesMatches, file);
file.close();
}
}
//-- export putative matches Adjacency matrix
PairWiseMatchingToAdjacencyMatrixSVG(vec_fileNames.size(),
map_PutativesMatches,
stlplus::create_filespec(sOutDir, "PutativeAdjacencyMatrix", "svg"));
//---------------------------------------
// d. Geometric filtering of putative matches
// - AContrario Estimation of the desired geometric model
// - Use an upper bound for the a contrario estimated threshold
//---------------------------------------
PairWiseMatches map_GeometricMatches;
ImageCollectionGeometricFilter<FeatureT> collectionGeomFilter;
const double maxResidualError = 4.0;
size_t iterations = 8192; // 4096
if (collectionGeomFilter.loadData(vec_fileNames, sOutDir))
{
std::cout << std::endl << " - GEOMETRIC FILTERING - " << std::endl;
switch (eGeometricModelToCompute)
{
case FUNDAMENTAL_MATRIX:
{
collectionGeomFilter.Filter(
GeometricFilter_FMatrix_AC(maxResidualError, iterations),
map_PutativesMatches,
map_GeometricMatches,
vec_imagesSize);
}
break;
case ESSENTIAL_MATRIX:
{
collectionGeomFilter.Filter(
GeometricFilter_EMatrix_AC(vec_focalGroup[0].m_K, maxResidualError),
map_PutativesMatches,
map_GeometricMatches,
vec_imagesSize);
//-- Perform an additional check to remove pairs with poor overlap
std::vector<PairWiseMatches::key_type> vec_toRemove;
for (PairWiseMatches::const_iterator iterMap = map_GeometricMatches.begin();
iterMap != map_GeometricMatches.end(); ++iterMap)
{
size_t putativePhotometricCount = map_PutativesMatches.find(iterMap->first)->second.size();
size_t putativeGeometricCount = iterMap->second.size();
float ratio = putativeGeometricCount / (float)putativePhotometricCount;
if (putativeGeometricCount < 50 || ratio < .3f) {
// the pair will be removed
vec_toRemove.push_back(iterMap->first);
}
}
//-- remove discarded pairs
for (std::vector<PairWiseMatches::key_type>::const_iterator
iter = vec_toRemove.begin(); iter != vec_toRemove.end(); ++iter)
{
map_GeometricMatches.erase(*iter);
}
}
break;
case HOMOGRAPHY_MATRIX:
{
collectionGeomFilter.Filter(
GeometricFilter_HMatrix_AC(maxResidualError),
map_PutativesMatches,
map_GeometricMatches,
vec_imagesSize);
}
break;
}
//---------------------------------------
//-- Export geometric filtered matches
//---------------------------------------
std::ofstream file (string(sOutDir + "/" + sGeometricMatchesFilename).c_str());
if (file.is_open())
PairedIndMatchToStream(map_GeometricMatches, file);
file.close();
//-- export Adjacency matrix
std::cout << "\n Export Adjacency Matrix of the pairwise's geometric matches"
<< std::endl;
PairWiseMatchingToAdjacencyMatrixSVG(vec_fileNames.size(),
map_GeometricMatches,
stlplus::create_filespec(sOutDir, "GeometricAdjacencyMatrix", "svg"));
}
return EXIT_SUCCESS;
}
