bool MainWindow::serverArgs(QStringList& args, QString& app)
{
app = appPath(appConfig().synergysName(), appConfig().synergys());
if (!QFile::exists(app))
{
if (QMessageBox::warning(this, tr("Synergy server not found"), tr("The executable for the synergy server does not exist. Do you want to browse for the synergy server now?"), QMessageBox::Yes | QMessageBox::No) != QMessageBox::Yes)
return false;
app = SettingsDialog::browseForSynergys(this, appConfig().synergyProgramDir(), appConfig().synergysName());
if (app.isEmpty())
return false;
appConfig().setSynergys(app);
}
if (appConfig().logToFile())
{
appConfig().persistLogDir();
args << "--log" << appConfig().logFilename();
}
args << "-c" << configFilename() << "--address" << address();
return true;
}
void WINAPI ServiceMain( DWORD argc, LPSTR *argv )
{
std::memset( &SPEPService::serviceStatus, 0, sizeof(SPEPService::serviceStatus) );
SPEPService::serviceStatus.dwServiceType = SERVICE_WIN32;
SPEPService::serviceStatus.dwControlsAccepted = SERVICE_ACCEPT_STOP;
SPEPService::updateStatus( SERVICE_START_PENDING );
std::vector<saml2::Handler*> handlers;
std::auto_ptr<spep::daemon::StreamLogHandler> logHandler;
std::auto_ptr<std::ostream> stream;
std::string logFilename;
boost::program_options::variables_map configFileVariableMap;
bool readConfig = false;
// Open the registry to get the filename
RegistryKey rKeySoftware( HKEY_LOCAL_MACHINE, REGISTRY_KEY_SOFTWARE, KEY_ENUMERATE_SUB_KEYS );
if( rKeySoftware.valid() )
{
RegistryKey rKeyESOEProject( rKeySoftware, REGISTRY_KEY_ESOEPROJECT, KEY_ENUMERATE_SUB_KEYS );
if( rKeyESOEProject.valid() )
{
RegistryKey rKeySPEP( rKeyESOEProject, REGISTRY_KEY_SPEP, KEY_READ );
if( rKeySPEP.valid() )
{
std::string configFilename( rKeySPEP.queryValueString( "ConfigFile" ) );
logFilename = ( rKeySPEP.queryValueString( "LogFile" ) );
if( logFilename.length() != 0 )
{
stream.reset( new std::ofstream( logFilename.c_str() ) );
logHandler.reset( new spep::daemon::StreamLogHandler( *stream, spep::DEBUG ) );
handlers.push_back( logHandler.get() );
}
// Read the file
std::ifstream configFileInput( configFilename.c_str() );
if( configFileInput.good() )
{
parseConfig( configFileVariableMap, configFileInput, handlers );
readConfig = true;
}
else
{
directLog( handlers, "The config file specified in the registry key doesn't exist." );
return;
}
}
else
{
directLog( handlers, "Couldn't open HKEY_LOCAL_MACHINE\Software\ESOE Project\SPEP" );
return;
}
}
int main(int argc, char *argv[]) {
if (argc < 3)
return EXIT_FAILURE;
std::string port(argv[1]);
std::string configFilename(argv[2]);
std::cout << "Welcome to Megaman 3 Server Edition" << std::endl;
// Seed rand
srand(time(NULL));
Logger::getInstance().log(1, "Server starting...");
Server server = Server(port, configFilename);
server.run();
Logger::getInstance().log(1, "Server quitting...");
return EXIT_SUCCESS;
}
AppConfig* AppConfig::Instance()
{
static AppConfig* instance = 0;
if (!instance)
{
std::string configFilename(FileUtils::Join(
Host::GetInstance()->GetApplication()->getPath().c_str(),
CONFIG_FILENAME, 0));
GetLogger()->Debug("Loading config file: %s", configFilename.c_str());
if (!FileUtils::IsFile(configFilename))
{
GetLogger()->Critical("Cannot load config file: %s",
configFilename.c_str());
throw ValueException::FromFormat("Cannot load config file: %s",
configFilename.c_str());
}
instance = new AppConfig(configFilename);
}
return instance;
}
//--------------------------------------------------------------------------------------------------
int main( int argc, char** argv )
{
// Read in a configuration file
if ( argc < 2 )
{
fprintf( stderr, "No configuration file provided\n" );
showUsage( argv[ 0 ] );
return -1;
}
initialiseTestPositions();
//std::string configFilename = Utilities::getDataDir() + std::string( "/" ) + std::string( argv[ 1 ] );
std::string configFilename( argv[ 1 ] );
cv::FileStorage configFileStorage;
configFileStorage.open( configFilename, cv::FileStorage::READ );
if ( !configFileStorage.isOpened() )
{
fprintf( stderr, "Unable to open %s\n", configFilename.c_str() );
return -1;
}
cv::Mat kinectDepthCameraPos;
cv::Mat kinectDepthCameraRotXYZDeg;
double kinectDepthFocalLengthPixel;
int32_t kinectDepthImageWidth;
int32_t kinectDepthImageHeight;
cv::Mat kinectRGBCameraPos;
cv::Mat kinectRGBCameraRotXYZDeg;
double kinectRGBFocalLengthPixel;
int32_t kinectRGBImageWidth;
int32_t kinectRGBImageHeight;
cv::Mat highResCameraPos;
cv::Mat highResCameraRotXYZDeg;
double highResFocalLengthPixel;
int32_t highResImageWidth;
int32_t highResImageHeight;
// The camera poses are defined in a coordinate system with the Kinect depth camera at the
// origin looking down the +ve z-axis, so z values increase into the image. The x and y axes
// of the depth camera are aligned with its image plane, so +ve x points to its right, and
// +ve y points down through the base of the camera. To position the camera in world space, it
// is rotated 180 degrees about the z axis, the chessboard positions are defined in world space.
configFileStorage[ "kinectDepthFocalLengthPixel" ] >> kinectDepthFocalLengthPixel;
configFileStorage[ "kinectDepthImageWidth" ] >> kinectDepthImageWidth;
configFileStorage[ "kinectDepthImageHeight" ] >> kinectDepthImageHeight;
configFileStorage[ "kinectRGBCameraPos" ] >> kinectRGBCameraPos;
configFileStorage[ "kinectRGBCameraRotXYZDeg" ] >> kinectRGBCameraRotXYZDeg;
configFileStorage[ "kinectRGBFocalLengthPixel" ] >> kinectRGBFocalLengthPixel;
configFileStorage[ "kinectRGBImageWidth" ] >> kinectRGBImageWidth;
configFileStorage[ "kinectRGBImageHeight" ] >> kinectRGBImageHeight;
configFileStorage[ "highResCameraPos" ] >> highResCameraPos;
configFileStorage[ "highResCameraRotXYZDeg" ] >> highResCameraRotXYZDeg;
configFileStorage[ "highResFocalLengthPixel" ] >> highResFocalLengthPixel;
configFileStorage[ "highResImageWidth" ] >> highResImageWidth;
configFileStorage[ "highResImageHeight" ] >> highResImageHeight;
// Construct camera matrices
cv::Mat zeroVec = cv::Mat::zeros( 3, 1, CV_64FC1 );
cv::Mat kinectDepthCalibMtx = createCameraCalibrationMatrix(
kinectDepthFocalLengthPixel, kinectDepthImageWidth, kinectDepthImageHeight );
cv::Mat kinectDepthWorldMtx = createCameraWorldMatrix( zeroVec, zeroVec );
cv::Mat kinectRGBCalibMtx = createCameraCalibrationMatrix(
kinectRGBFocalLengthPixel, kinectRGBImageWidth, kinectRGBImageHeight );
cv::Mat kinectRGBWorldMtx = createCameraWorldMatrix(
kinectRGBCameraPos, kinectRGBCameraRotXYZDeg );
cv::Mat highResCalibMtx = createCameraCalibrationMatrix(
highResFocalLengthPixel, highResImageWidth, highResImageHeight );
cv::Mat highResWorldMtx = createCameraWorldMatrix(
highResCameraPos, highResCameraRotXYZDeg );
// First generate calibration images for the high resolution camera
for ( uint32_t testPosIdx = 0; testPosIdx < gHighResCalibrationPositions.size(); testPosIdx++ )
{
cv::Mat chessboardPoseMtx = createChessboardPoseMatrix( gHighResCalibrationPositions[ testPosIdx ] );
// Generate an image from the high resolution camera
cv::Mat highResRgbImage = generateRGBImageOfChessboard( highResWorldMtx, highResCalibMtx,
highResImageWidth, highResImageHeight, chessboardPoseMtx );
cv::imwrite( createOutputFilename( "chessboard_highres", testPosIdx + 1, ".png" ), highResRgbImage );
}
// Now generate images to identify the relative poses of the cameras
for ( uint32_t testPosIdx = 0; testPosIdx < gRelativeCalibrationPositions.size(); testPosIdx++ )
{
cv::Mat chessboardPoseMtx = createChessboardPoseMatrix( gRelativeCalibrationPositions[ testPosIdx ] );
// Generate a point cloud from the Kinect
PointCloud::Ptr pCloud = generatePointCloudOfChessboard( kinectDepthWorldMtx, kinectDepthCalibMtx,
kinectDepthImageWidth, kinectDepthImageHeight, chessboardPoseMtx );
pCloud->saveToSpcFile( createOutputFilename( "relative_chessboard", testPosIdx + 1, ".spc" ), true );
// Generate an image from the Kinect RGB camera
cv::Mat rgbImage = generateRGBImageOfChessboard( kinectRGBWorldMtx, kinectRGBCalibMtx,
kinectRGBImageWidth, kinectRGBImageHeight, chessboardPoseMtx );
cv::imwrite( createOutputFilename( "relative_chessboard", testPosIdx + 1, ".png" ), rgbImage );
// Generate an image from the high resolution camera
cv::Mat highResRgbImage = generateRGBImageOfChessboard( highResWorldMtx, highResCalibMtx,
highResImageWidth, highResImageHeight, chessboardPoseMtx );
cv::imwrite( createOutputFilename( "relative_chessboard_highres", testPosIdx + 1, ".png" ), highResRgbImage );
}
// Generate ideal calibration files
// First the kinect calibration
cv::FileStorage dataFile( "kinect_calib.yaml", cv::FileStorage::WRITE );
dataFile << "DepthCameraCalibrationMtx" << kinectDepthCalibMtx;
dataFile << "ColorCameraCalibrationMtx" << kinectRGBCalibMtx;
cv::Mat kinectRGBInKinectDepthSpace = (kinectDepthWorldMtx.inv())*kinectRGBWorldMtx;
dataFile << "DepthToColorCameraRotation" << cv::Mat( kinectRGBInKinectDepthSpace, cv::Rect( 0, 0, 3, 3 ) );
dataFile << "DepthToColorCameraTranslation" << cv::Mat( kinectRGBInKinectDepthSpace, cv::Rect( 3, 0, 1, 3 ) );
dataFile.release();
// Now the high resolution camera calibration
dataFile = cv::FileStorage( "high_res_calib.yaml", cv::FileStorage::WRITE );
dataFile << "cameraMatrix" << highResCalibMtx;
dataFile.release();
// Finally, the position of the high resolution colour camera in Kinect colour camera space
dataFile = cv::FileStorage( "colour_stereo_calib.yaml", cv::FileStorage::WRITE );
cv::Mat highResInKinectRGBSpace = (kinectRGBWorldMtx.inv())*highResWorldMtx;
dataFile << "R" << cv::Mat( highResInKinectRGBSpace, cv::Rect( 0, 0, 3, 3 ) );
dataFile << "T" << cv::Mat( highResInKinectRGBSpace, cv::Rect( 3, 0, 1, 3 ) );
dataFile.release();
//std::cout << kinectRGBWorldMtx << std::endl;
//std::cout << highResWorldMtx << std::endl;
//std::cout << highResInKinectRGBSpace << std::endl;
return 0;
}
int main( int argc, char *argv[] )
{
// try {
time_t programStartTime(time(NULL) );
boost::filesystem::path workingDir( boost::filesystem::current_path() );
// ========== PROGRAM PARAMETERS ==========
std::string progName( "buildrandctree" );
std::string configFilename( "/home/raid2/moreno/Code/hClustering/config/"+progName+".cfg" );
// program parameters
std::string roiFilename, inputFolder, outputFolder;
float memory( 0.5 ), maxNbDist( 1 );
unsigned int nbLevel( 26 ), threads( 0 );
bool keepDiscarded( false ), niftiMode( true ), debug( false );
TC_GROWTYPE growType( TC_GROWOFF );
size_t baseSize( 0 );
// Declare a group of options that will be allowed only on command line
boost::program_options::options_description genericOptions( "Generic options" );
genericOptions.add_options()
( "version", "Program version" )
( "help,h", "Produce extended program help message" )
( "roi,r", boost::program_options::value< std::string >(&roiFilename), "file with the seed voxels coordinates." )
( "inputf,I", boost::program_options::value< std::string >(&inputFolder), "input data folder (seed tractograms)." )
( "outputf,O", boost::program_options::value< std::string >(&outputFolder), "output folder" )
( "maxnbdist,d", boost::program_options::value< float >(&maxNbDist)->implicit_value(1), "[opt] maximum dissimilarity a seed voxel tract must have to its most similar neighbor not be discarded. (0,1]." )
( "cnbhood,c", boost::program_options::value< unsigned int >(&nbLevel)->implicit_value(26), "[opt] centroid method neighborhood level. Valid values: 6, 18, 26(default), 32, 96, 124." )
( "basesize,S", boost::program_options::value< size_t >(&baseSize), "[opt] grow homogeneous base nodes (meta-leaves) of size S. (>=2)." )
( "basenum,N", boost::program_options::value< size_t >(&baseSize), "[opt] grow N homogeneous base nodes (meta-leaves). (>=10)." )
;
// Declare a group of options that will be allowed both on command line and in config file
boost::program_options::options_description configOptions( "Configuration" );
configOptions.add_options()
( "verbose,v", "[opt] verbose output." )
( "vista", "[opt] use vista file format (default is nifti)." )
( "cache-mem,m", boost::program_options::value< float >(&memory)->implicit_value(0.5), "[opt] maximum of memory (in GBytes) to use for tractogram cache memory. Default: 0.5." )
( "keep-disc,k", "[opt] keep discarded voxels data in a section of the tree file." )
( "debugout", "[opt] write additional detailed outputs meant for debug." )
( "pthreads,p", boost::program_options::value< unsigned int >(&threads), "[opt] number of processing cores to run the program in. Default: all available." )
;
// Hidden options, will be allowed both on command line and in config file, but will not be shown to the user.
boost::program_options::options_description hiddenOptions( "Hidden options" );
//hiddenOptions.add_options() ;
boost::program_options::options_description cmdlineOptions;
cmdlineOptions.add(genericOptions).add(configOptions).add(hiddenOptions);
boost::program_options::options_description configFileOptions;
configFileOptions.add(configOptions).add(hiddenOptions);
boost::program_options::options_description visibleOptions( "Allowed options" );
visibleOptions.add(genericOptions).add(configOptions);
boost::program_options::positional_options_description posOpt; //this arguments do not need to specify the option descriptor when typed in
//posOpt.add( "roi", -1);
boost::program_options::variables_map variableMap;
store(boost::program_options::command_line_parser(argc, argv).options(cmdlineOptions).positional(posOpt).run(), variableMap);
std::ifstream ifs(configFilename.c_str() );
store(parse_config_file(ifs, configFileOptions), variableMap);
notify( variableMap);
if ( variableMap.count( "help" ) )
{
std::cout << "---------------------------------------------------------------------------" << std::endl;
std::cout << std::endl;
std::cout << " Project: hClustering" << std::endl;
std::cout << std::endl;
std::cout << " Whole-Brain Connectivity-Based Hierarchical Parcellation Project" << std::endl;
std::cout << " David Moreno-Dominguez" << std::endl;
std::cout << " [email protected]" << std::endl;
std::cout << " [email protected]" << std::endl;
std::cout << " www.cbs.mpg.de/~moreno" << std::endl;
std::cout << std::endl;
std::cout << " For more reference on the underlying algorithm and research they have been used for refer to:" << std::endl;
std::cout << " - Moreno-Dominguez, D., Anwander, A., & Knösche, T. R. (2014)." << std::endl;
std::cout << " A hierarchical method for whole-brain connectivity-based parcellation." << std::endl;
std::cout << " Human Brain Mapping, 35(10), 5000-5025. doi: http://dx.doi.org/10.1002/hbm.22528" << std::endl;
std::cout << " - Moreno-Dominguez, D. (2014)." << std::endl;
std::cout << " Whole-brain cortical parcellation: A hierarchical method based on dMRI tractography." << std::endl;
std::cout << " PhD Thesis, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig." << std::endl;
std::cout << " ISBN 978-3-941504-45-5" << std::endl;
std::cout << std::endl;
std::cout << " hClustering is free software: you can redistribute it and/or modify" << std::endl;
std::cout << " it under the terms of the GNU Lesser General Public License as published by" << std::endl;
std::cout << " the Free Software Foundation, either version 3 of the License, or" << std::endl;
std::cout << " (at your option) any later version." << std::endl;
std::cout << " http://creativecommons.org/licenses/by-nc/3.0" << std::endl;
std::cout << std::endl;
std::cout << " hClustering is distributed in the hope that it will be useful," << std::endl;
std::cout << " but WITHOUT ANY WARRANTY; without even the implied warranty of" << std::endl;
std::cout << " MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the" << std::endl;
std::cout << " GNU Lesser General Public License for more details." << std::endl;
std::cout << std::endl;
std::cout << "---------------------------------------------------------------------------" << std::endl << std::endl;
std::cout << "buildrandctree" << std::endl << std::endl;
std::cout << "Build a centroid hierarchical tree from a set of artificially pre-generated set of tractograms yoielding a uniformly random similarity matrix and a seed neighborhood information voxel list." << std::endl << std::endl;
std::cout << "* Arguments:" << std::endl << std::endl;
std::cout << " --version: Program version." << std::endl << std::endl;
std::cout << " -h --help: Produce extended program help message." << std::endl << std::endl;
std::cout << " -r --roi: A text file with the seed voxel coordinates and the corresponding tractogram index (if tractogram naming is based on index rather than coordinates)." << std::endl << std::endl;
std::cout << " -I --inputf: input data folder (containing the compact tractograms)." << std::endl << std::endl;
std::cout << " -O --outputf: Output folder where tree files will be written." << std::endl << std::endl;
std::cout << "[-d --maxnbdist]: Maximum dissimilarity a seed voxel tract must have to its most similar neighbor not be discarded." << std::endl;
std::cout << " Valid values: (0,1] Use a value of 1 (default) if no discarding is desired." << std::endl << std::endl;
std::cout << "[-c --cnbhood]: Use centroid method with C neighborhood level. Valid values: 6, 18, 24(default), 32, 96, 124." << std::endl << std::endl;
std::cout << "[-S --basesize]: Merge homogeneous base nodes of size S. (mutually exclusive with -N option). Default: 0 (no homogeneous merging)." << std::endl << std::endl;
std::cout << "[-N --basenum]: Grow N homogeneous base nodes. (mutually exclusive with -S option). Default: 0 (no homogeneous merging)." << std::endl << std::endl;
std::cout << "[-v --verbose]: Verbose output (recommended)." << std::endl << std::endl;
std::cout << "[--vista]: Read/write vista (.v) files [default is nifti (.nii) and compact (.cmpct) files]." << std::endl << std::endl;
std::cout << "[-m --cache-mem]: Maximum amount of RAM memory (in GBytes) to use for temporal tractogram cache storing. Valid values [0.1,50]. Default: 0.5." << std::endl << std::endl;
std::cout << "[-k --keep-disc]: Keep discarded voxel information in a specialiced section of the tree." << std::endl << std::endl;
std::cout << "[--debugout]: Write additional detailed outputs meant to be used for debugging." << std::endl << std::endl;
std::cout << "[-p --pthreads]: Number of processing threads to run the program in parallel. Default: use all available processors." << std::endl << std::endl;
std::cout << std::endl;
std::cout << "* Usage example:" << std::endl << std::endl;
std::cout << " buildrandctree -r roi_lh.txt -I tractograms/ -O results/ -c 26 -N 1000 -k -m 2 -v " << std::endl << std::endl;
std::cout << std::endl;
std::cout << "* Outputs (in output folder defined at option -O):" << std::endl << std::endl;
std::cout << " - 'cX_bin_nmt.txt' - (where X is the neighborhood level defined at option -c) non-monotonic binary-branching hierarchical tree without tree processing (if desired use processtree command)." << std::endl;
std::cout << " - 'baselist_nmt.txt' - meta-leaves (base nodes defined by the us of option -N or -S) list with IDs corresponding to the non-monotonic tree file." << std::endl;
std::cout << " - 'success.txt' - An empty file created when the program has sucessfully exited after completion (to help for automatic re-running scripting after failure)." << std::endl;
std::cout << " - 'buildrandtree_log.txt' - A text log file containing the parameter details and in-run and completion information of the program." << std::endl;
std::cout << std::endl;
std::cout << " [extra outputs when using --debugout option)" << std::endl << std::endl;
std::cout << " - 'cX_bin_nmt_debug.txt' - version of the counterpart file without '_debug' suffix with redundant information for debugging purposes." << std::endl;
std::cout << std::endl;
exit(0);
}
if ( variableMap.count( "verbose" ) ) {
std::cout << "verbose output" << std::endl;
verbose=true;
}
if ( variableMap.count( "pthreads" ) )
{
if ( threads == 1 )
{
std::cout << "Using a single processor" << std::endl;
}
else if( threads == 0 || threads >= omp_get_num_procs() )
{
threads = omp_get_num_procs();
std::cout << "Using all available processors ( " << threads << " )." << std::endl;
}
else
{
std::cout << "Using a maximum of " << threads << " processors " << std::endl;
}
omp_set_num_threads( threads );
}
else
{
threads = omp_get_num_procs();
omp_set_num_threads( threads );
std::cout << "Using all available processors ( " << threads << " )." << std::endl;
}
if ( variableMap.count( "vista" ) )
{
if( verbose )
{
std::cout << "Using vista format" << std::endl;
}
fileManagerFactory fmf;
fmf.setVista();
niftiMode = false;
}
else
{
if( verbose )
{
std::cout << "Using nifti format" << std::endl;
}
fileManagerFactory fmf;
fmf.setNifti();
niftiMode = true;
}
if ( variableMap.count( "debugout" ) )
{
if( verbose )
{
std::cout << "Debug output files activated" << std::endl;
}
debug = true;
}
if ( variableMap.count( "version" ) )
{
std::cout << progName << ", version 2.0" << std::endl;
exit(0);
}
if ( variableMap.count( "roi" ) )
{
if( !boost::filesystem::is_regular_file( boost::filesystem::path( roiFilename ) ) )
{
std::cerr << "ERROR: roi file \"" <<roiFilename<< "\" is not a regular file" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
else if( verbose )
{
std::cout << "Seed voxels roi file: " << roiFilename << std::endl;
}
}
else
{
std::cerr << "ERROR: no seed voxels roi file stated" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if( verbose )
{
std::cout << "Maximum distance to most similar neighbor: " << maxNbDist << std::endl;
}
if ( maxNbDist <= 0 || maxNbDist > 1 )
{
std::cerr << "ERROR: distance value used is out of bounds please use a value within (0,1]" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
else if ( maxNbDist == 1 && verbose )
{
std::cout << "No neighbor distance restrictions will be applied" << std::endl;
}
else if( verbose )
{
std::cout << "Seed voxels with no neighbors with tract dissimilarity lower than " << maxNbDist << " will be discarded as outliers" << std::endl;
}
if( verbose )
{
std::cout << "Centroid neighborhood level: " << nbLevel << std::endl;
}
if ( ( nbLevel != 6 ) && ( nbLevel != 18 ) && ( nbLevel != 26 ) && ( nbLevel != 32 ) && ( nbLevel != 92 ) && ( nbLevel != 124 ) )
{
std::cerr << "ERROR: invalid nbhood level, only (6,18,26,32,92,124) are accepted" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if ( ( variableMap.count( "basesize" ) && variableMap.count( "basenum" ) ) )
{
std::cerr << "ERROR: options --basesize (-S) and --basenum (-N) are mutually exclusive" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if ( variableMap.count( "basesize" ) )
{
if( baseSize <= 1 )
{
std::cerr << "ERROR: base node (meta-leaf) size must be greater than 1" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
else
{
if( verbose )
{
std::cout << "Initial merging stage up to homogeneous base nodes of size: " << baseSize << std::endl;
}
growType = TC_GROWSIZE;
}
}
if ( variableMap.count( "basenum" ) )
{
if( baseSize < 10 )
{
std::cerr << "ERROR: base node (meta-leaf) number must be equal or greater than 10" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
else
{
if( verbose )
{
std::cout << "Initial merging stage up to " << baseSize << " homogeneous base nodes (meta-leaves)" << std::endl;
}
growType = TC_GROWNUM;
}
}
if( growType == TC_GROWOFF && verbose )
{
std::cout << "No homogeneous merging stage" << std::endl;
}
if ( variableMap.count( "keep-disc" ) )
{
if( verbose )
{
std::cout << "Discarded voxel coordinates will be saved in an special section fo the tree file" << std::endl;
}
keepDiscarded = true;
}
else
{
if( verbose )
{
std::cout << "Discarded voxel coordinates will not be saved" << std::endl;
}
keepDiscarded = false;
}
if ( variableMap.count( "inputf" ) )
{
if( !boost::filesystem::is_directory( boost::filesystem::path( inputFolder ) ) )
{
std::cerr << "ERROR: input seed tractogram folder \"" <<inputFolder<< "\" is not a directory" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
else if( verbose )
{
std::cout << "Input seed tractogram folder: " << inputFolder << std::endl;
}
}
else
{
std::cerr << "ERROR: no input seed tractogram stated" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if ( variableMap.count( "outputf" ) )
{
if( !boost::filesystem::is_directory( boost::filesystem::path( outputFolder ) ) )
{
std::cerr << "ERROR: output folder \"" <<outputFolder<< "\" is not a directory" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
else if( verbose )
{
std::cout << "Output folder: " << outputFolder << std::endl;
}
}
else
{
std::cerr << "ERROR: no output folder stated" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if ( memory < 0.1 || memory > 50)
{
std::cerr << "ERROR: cache size must be a positive float between 0.1 and 50 (GB)" << std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
else if( verbose )
{
std::cout << "Tractogram cache memory: " << memory << " GBytes" << std::endl;
}
std::string logFilename(outputFolder+"/"+progName+"_log.txt" );
std::ofstream logFile(logFilename.c_str() );
if(!logFile)
{
std::cerr << "ERROR: unable to open log file: \"" <<logFilename<< "\"" << std::endl;
exit(-1);
}
logFile << "Start Time:\t" << ctime(&programStartTime) << std::endl;
logFile << "Working directory:\t" << workingDir.string() << std::endl;
logFile << "Verbose:\t" << verbose << std::endl;
logFile << "Processors used:\t" << threads << std::endl;
if( niftiMode )
{
logFile << "Using nifti file format" << std::endl;
}
else
{
logFile << "Using vista file format" << std::endl;
}
logFile << "Vista mode flag:\t" << verbose << std::endl;
logFile << "Roi file:\t" << roiFilename << std::endl;
logFile << "Max nb distance:\t" << maxNbDist << std::endl;
logFile << "Nbhood restriction level:\t" <<nbLevel<< std::endl;
switch(growType)
{
case TC_GROWOFF:
logFile << "Region growing: None" << std::endl;
break;
case TC_GROWSIZE:
logFile << "Region growing: Size: " << baseSize << std::endl;
break;
case TC_GROWNUM:
logFile << "Region growing: Number: " << baseSize << std::endl;
break;
}
logFile << "Input seed tract folder:\t" << inputFolder << std::endl;
logFile << "Output folder:\t" << outputFolder << std::endl;
logFile << "Memory cache size:\t" << memory << " GB" << std::endl;
logFile << "Debug outputr:\t" << debug << std::endl;
logFile << "-------------" << std::endl;
/////////////////////////////////////////////////////////////////
randCnbTreeBuilder builder( roiFilename, verbose );
logFile << "Roi size:\t" << builder.roiSize() << std::endl;
builder.log( &logFile );
builder.setInputFolder( inputFolder );
builder.setOutputFolder( outputFolder );
builder.setDebugOutput( debug );
builder.buildRandCentroid( nbLevel, memory, growType, baseSize, keepDiscarded );
/////////////////////////////////////////////////////////////////
// save and print total time
time_t programEndTime(time(NULL) );
int totalTime( difftime(programEndTime,programStartTime) );
std::cout << "Program Finished, total time: " << totalTime/3600 << "h " << (totalTime%3600)/60 << "' " << ((totalTime%3600)%60) << "\" " << std::endl;
logFile << "-------------" << std::endl;
logFile << "Finish Time:\t" << ctime(&programEndTime) << std::endl;
logFile << "Elapsed time : " << totalTime/3600 << "h " << (totalTime%3600)/60 << "' " << ((totalTime%3600)%60) << "\"" << std::endl;
// create file that indicates process was finished successfully
std::string successFilename(outputFolder+"/success.txt" );
std::ofstream successFile(successFilename.c_str() );
if(!successFile)
{
std::cerr << "ERROR: unable to create success file: \"" <<successFile<< "\"" << std::endl;
exit(-1);
}
successFile << "success";
// }
// catch(std::exception& e)
// {
// std::cout << e.what() << std::endl;
// return 1;
// }
return 0;
}
int main( int argc, char *argv[] )
{
// try {
time_t programStartTime(time(NULL));
boost::filesystem::path workingDir( boost::filesystem::current_path());
// ========== PROGRAM PARAMETERS ==========
std::string progName("partitiontree");
std::string configFilename("../../config/"+progName+".cfg");
unsigned int threads(0), levelDepth(3), filterRadius(0);
bool verbose(false), niftiMode( true );
// program parameters
std::string treeFilename, outputFolder;
// Declare a group of options that will be allowed only on command line
boost::program_options::options_description genericOptions("Generic options");
genericOptions.add_options()
( "version", "Program version" )
( "help,h", "Produce extended program help message" )
( "tree,t", boost::program_options::value< std::string >(&treeFilename), "file with the tree to compute partitions from")
( "outputf,O", boost::program_options::value< std::string >(&outputFolder), "output folder where partition files will be written")
( "search-depth,d", boost::program_options::value< unsigned int >(&levelDepth)->implicit_value(3), "[opt] optimal partition search depth (default = 3)")
( "filter-radius,r", boost::program_options::value< unsigned int >(&filterRadius)->implicit_value(0), "[opt] output partition filter kernel radius (default = 0 | no filtering)")
( "hoz", "[opt] obtain horizontal cut partitions (instead of Spread-Separation ones)")
( "maxgran,m", "[opt] obtain only the maximum granularity partition")
;
// Declare a group of options that will be allowed both on command line and in config file
boost::program_options::options_description configOptions("Configuration");
configOptions.add_options()
( "verbose,v", "[opt] verbose output." )
( "vista", "[opt] use vista file format (default is nifti)." )
( "pthreads,p", boost::program_options::value< unsigned int >(&threads), "[opt] number of processing threads to run the program in parallel, default: all available")
;
// Hidden options, will be allowed both on command line and in config file, but will not be shown to the user.
boost::program_options::options_description hiddenOptions("Hidden options");
//hiddenOptions.add_options() ;
boost::program_options::options_description cmdlineOptions;
cmdlineOptions.add(genericOptions).add(configOptions).add(hiddenOptions);
boost::program_options::options_description configFileOptions;
configFileOptions.add(configOptions).add(hiddenOptions);
boost::program_options::options_description visibleOptions("Allowed options");
visibleOptions.add(genericOptions).add(configOptions);
boost::program_options::positional_options_description posOpt; //this arguments do not need to specify the option descriptor when typed in
//posOpt.add("roi-file", -1);
boost::program_options::variables_map variableMap;
store(boost::program_options::command_line_parser(argc, argv).options(cmdlineOptions).positional(posOpt).run(), variableMap);
std::ifstream ifs(configFilename.c_str());
store(parse_config_file(ifs, configFileOptions), variableMap);
notify(variableMap);
if (variableMap.count("help"))
{
std::cout << "---------------------------------------------------------------------------" << std::endl;
std::cout << std::endl;
std::cout << " Project: hClustering" << std::endl;
std::cout << std::endl;
std::cout << " Whole-Brain Connectivity-Based Hierarchical Parcellation Project" << std::endl;
std::cout << " David Moreno-Dominguez" << std::endl;
std::cout << " [email protected]" << std::endl;
std::cout << " [email protected]" << std::endl;
std::cout << " www.cbs.mpg.de/~moreno" << std::endl;
std::cout << std::endl;
std::cout << " For more reference on the underlying algorithm and research they have been used for refer to:" << std::endl;
std::cout << " - Moreno-Dominguez, D., Anwander, A., & Knösche, T. R. (2014)." << std::endl;
std::cout << " A hierarchical method for whole-brain connectivity-based parcellation." << std::endl;
std::cout << " Human Brain Mapping, 35(10), 5000-5025. doi: http://dx.doi.org/10.1002/hbm.22528" << std::endl;
std::cout << " - Moreno-Dominguez, D. (2014)." << std::endl;
std::cout << " Whole-brain cortical parcellation: A hierarchical method based on dMRI tractography." << std::endl;
std::cout << " PhD Thesis, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig." << std::endl;
std::cout << " ISBN 978-3-941504-45-5" << std::endl;
std::cout << std::endl;
std::cout << " hClustering is free software: you can redistribute it and/or modify" << std::endl;
std::cout << " it under the terms of the GNU Lesser General Public License as published by" << std::endl;
std::cout << " the Free Software Foundation, either version 3 of the License, or" << std::endl;
std::cout << " (at your option) any later version." << std::endl;
std::cout << " http://creativecommons.org/licenses/by-nc/3.0" << std::endl;
std::cout << std::endl;
std::cout << " hClustering is distributed in the hope that it will be useful," << std::endl;
std::cout << " but WITHOUT ANY WARRANTY; without even the implied warranty of" << std::endl;
std::cout << " MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the" << std::endl;
std::cout << " GNU Lesser General Public License for more details." << std::endl;
std::cout << std::endl;
std::cout << "---------------------------------------------------------------------------" << std::endl << std::endl;
std::cout << "partitiontree" << std::endl << std::endl;
std::cout << "Obtain tree partitions at all granularity levels using the Spread-Separation method (finding the the partition with highest SS index at each granularity)." << std::endl;
std::cout << " Optimal SS value for each partition is searched within a defined search-depth hierarchical levels. Final partitions can be filtered with a defined kernel size." << std::endl;
std::cout << " to keep local SS maxima within that kernel. For SS index refer to (Moreno-Dominguez, 2014)" << std::endl;
std::cout << " For an interactive 3D partition management with more options please use the Hierarchcial Clustering module developed in OpenWalnut (www.openwalnut.org)." << std::endl << std::endl;
std::cout << "* Arguments:" << std::endl << std::endl;
std::cout << " --version: Program version." << std::endl << std::endl;
std::cout << " -h --help: produce extended program help message." << std::endl << std::endl;
std::cout << " -t --tree: File with the hierarchical tree to extract partitions from." << std::endl << std::endl;
std::cout << " -O --outputf: Output folder where partition files will be written." << std::endl << std::endl;
std::cout << "[-d --search-depth]: Search optimal partition for each granularity within d hierarchical levels." << std::endl;
std::cout << " A higher value will produce more optimized partition but will increase computing time." << std::endl;
std::cout << " Default: 3. Recommendened values: 3 for good quality and fast computation, 4 for enhanced quality." << std::endl << std::endl;
std::cout << "[-r --filter-radius]: Filter output partitions to keep only local SS (partition quality) maxima" << std::endl;
std::cout << " within a r-sized kernel across the granularity dimension." << std::endl << std::endl;
std::cout << "[-h --hoz]: Write horizontal cut partitions instead of SS ones (optimal partition search is still based on SS index)." << std::endl << std::endl;
std::cout << "[-m --maxgran]: Compute and write only the maximum granularity (meta-leaves) partition." << std::endl << std::endl;
std::cout << "[-v --verbose]: verbose output (recommended)." << std::endl << std::endl;
std::cout << "[--vista]: write output tree in vista coordinates (default is nifti)." << std::endl << std::endl;
std::cout << "[-p --pthreads]: number of processing threads to run the program in parallel. Default: use all available processors." << std::endl << std::endl;
std::cout << std::endl;
std::cout << "* Usage example:" << std::endl << std::endl;
std::cout << " partitiontree -t tree_lh.txt -O results/ -d 3 -r 50 -v" << std::endl << std::endl;
std::cout << std::endl;
std::cout << "* Outputs (in output folder defined at option -O):" << std::endl << std::endl;
std::cout << " (default outputs)" << std::endl;
std::cout << " - 'allSSparts_dX.txt' - (where X is the search depth level defined at parameter -d) Contains a summary of the partition information (cut value and size) for all granularities." << std::endl;
std::cout << " - 'TREE_SSparts_dX.txt' - (where TREE is the filename of the input tree defined at parameter -t) contains a copy of the original tree file with the partitions at all granularities included in the relevant fields." << std::endl;
std::cout << " - 'partitiontree_log.txt' - A text log file containing the parameter details and in-run and completion information of the program." << std::endl;
std::cout << std::endl;
std::cout << " (additional if using option -r)" << std::endl;
std::cout << " - 'filtSSparts_dX_rY.txt' - (where Y is the filter radius defined at parameter -r) Contains a summary of the resulting filtered partitions." << std::endl;
std::cout << " - 'TREE_SSparts_dX_rY.txt' - contains a copy of the original tree file with the resulting filtered partitions included in the relevant fields." << std::endl;
std::cout << std::endl;
std::cout << " (when using --hoz option, the prefix 'SS' will be replaced by 'Hoz'')" << std::endl;
std::cout << std::endl;
std::cout << " (alternative outputs when using option --maxgran)" << std::endl;
std::cout << " - 'fmaxgranPart.txt' - Contains the size information of the resulting maximal granularity partition for that tree." << std::endl;
std::cout << " - 'TREE_maxgranPart.txt' - contains a copy of the original tree file with the resulting max granularity partition included in the relevant fields." << std::endl;
std::cout << std::endl;
exit(0);
}
if (variableMap.count("version"))
{
std::cout << progName <<", version 2.0"<<std::endl;
exit(0);
}
if (variableMap.count("verbose"))
{
std::cout << "verbose output"<<std::endl;
verbose=true;
}
if (variableMap.count("pthreads"))
{
if (threads==1)
{
std::cout <<"Using a single processor"<< std::endl;
}
else if(threads==0 || threads>=omp_get_num_procs())
{
threads = omp_get_num_procs();
std::cout <<"Using all available processors ("<< threads <<")." << std::endl;
}
else
{
std::cout <<"Using a maximum of "<< threads <<" processors "<< std::endl;
}
omp_set_num_threads( threads );
}
else
{
threads = omp_get_num_procs();
omp_set_num_threads( threads );
std::cout <<"Using all available processors ("<< threads <<")." << std::endl;
}
if ( variableMap.count( "vista" ) )
{
if( verbose )
{
std::cout << "Using vista format" << std::endl;
}
fileManagerFactory fmf;
fmf.setVista();
niftiMode = false;
}
else
{
if( verbose )
{
std::cout << "Using nifti format" << std::endl;
}
fileManagerFactory fmf;
fmf.setNifti();
niftiMode = true;
}
if (variableMap.count("tree"))
{
if(!boost::filesystem::is_regular_file(boost::filesystem::path(treeFilename)))
{
std::cerr << "ERROR: tree file \""<<treeFilename<<"\" is not a regular file"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
std::cout << "Roi voxels file: "<< treeFilename << std::endl;
}
else
{
std::cerr << "ERROR: no tree file stated"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if (variableMap.count("outputf"))
{
if(!boost::filesystem::is_directory(boost::filesystem::path(outputFolder)))
{
std::cerr << "ERROR: output folder \""<<outputFolder<<"\" is not a directory"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
std::cout << "Output folder: "<< outputFolder << std::endl;
}
else
{
std::cerr << "ERROR: no output folder stated"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if (variableMap.count("maxgran"))
{
std::cout<<"Obtaining only max. granularity partition..."<<std::endl;
WHtree tree(treeFilename);
std::cout<<tree.getReport( false )<<std::endl;
if( tree.testRootBaseNodes() )
{
std::vector<size_t > maxpart( tree.getRootBaseNodes() );
std::vector<std::vector<size_t > > partitionVector( 1, maxpart);
std::vector<float > partitionValues(1,0);
std::cout<<"maxgranpart size: "<<std::endl<<maxpart.size()<<std::endl;
WHtreePartition partitioner(&tree);
std::string outPartFilename( outputFolder + "/maxgranPart.txt" );
partitioner.writePartitionSet( outPartFilename, partitionValues,partitionVector);
tree.insertPartitions( partitionVector, partitionValues );
std::string outTreeFilename( outputFolder + "/" + tree.getName() + "_maxgranPart" );
outTreeFilename += ( ".txt" );
tree.writeTree( outTreeFilename, niftiMode );
return 0;
}
else
{
std::cout<<"ERROR: tree does not have a maximum granularity meta-leaf partition"<<std::endl;
return(-1);
}
}
if( levelDepth > 5 )
{
std::cout << "Level depth indicated: " << levelDepth << " is too high, setting to a maximum of 5" << std::endl;
levelDepth = 5;
}
std::cout << "Using a search depth of: " << levelDepth << std::endl;
if( filterRadius > 1000 )
{
std::cout << "filter radius indicated: " << filterRadius << " is too high (max is 1000), setting to 100" << std::endl;
filterRadius = 10;
}
if( filterRadius == 0 )
{
std::cout << "using no filtering (radius 0)" << std::endl;
}
else if( filterRadius < 0 )
{
std::cout << "filter radius indicated: " << filterRadius << " must be positive. using no filtering (radius 0)" << std::endl;
filterRadius = 0;
}
else
{
std::cout << "Using a filter radius of: " << filterRadius << std::endl;
}
/////////////////////////////////////////////////////////////////
std::string logFilename(outputFolder+"/"+progName+"_log.txt");
std::ofstream logFile(logFilename.c_str());
if(!logFile) {
std::cerr << "ERROR: unable to open log file: \""<<logFilename<<"\""<<std::endl;
exit(-1);
}
logFile <<"Start Time:\t"<< ctime(&programStartTime) <<std::endl;
logFile <<"Working directory:\t"<< workingDir.string() <<std::endl;
logFile <<"Verbose:\t"<< verbose <<std::endl;
logFile <<"Tree file:\t"<< treeFilename <<std::endl;
logFile <<"Output folder:\t"<< outputFolder <<std::endl;
logFile <<"Verbose:\t"<< verbose <<std::endl;
if( niftiMode )
{
logFile << "Using nifti file format" << std::endl;
}
else
{
logFile << "Using vista file format" << std::endl;
}
WHtree tree(treeFilename);
logFile << tree.getReport( false ) <<std::endl;
std::cout<<tree.getReport( false )<<std::endl;
std::vector< float > partitionValues;
std::vector< std::vector< size_t> > partitionVector;
WHtreePartition treePartition(&tree);
std::string prefix;
if (variableMap.count("hoz"))
{
prefix = "Hoz";
std::cout <<"getting hoz partitions at all levels..." <<std::endl;
treePartition.scanHozPartitions( &partitionValues, &partitionVector );
std::cout << partitionValues.size() << " Partitions obtained, writing to file..." <<std::endl;
logFile <<"Initial partitions:\t"<< partitionValues.size() <<std::endl;
std::string outPartFilename( outputFolder + "/all" + prefix + "parts.txt" );
treePartition.writePartitionSet( outPartFilename, partitionValues, partitionVector);
tree.insertPartitions( partitionVector, partitionValues );
std::string outTreeFilename( outputFolder + "/" + tree.getName() + "_" + prefix + "parts_d" + boost::lexical_cast<std::string>(levelDepth) );
outTreeFilename += ( ".txt" );
tree.writeTree( outTreeFilename, niftiMode );
}
else
{
prefix = "SS";
std::cout <<"getting SS partitions at all levels..." <<std::endl;
treePartition.scanOptimalPartitions( levelDepth, &partitionValues, &partitionVector );
std::cout << partitionValues.size() << " Partitions obtained, writing to file..." <<std::endl;
logFile <<"Initial partitions:\t"<< partitionValues.size() <<std::endl;
std::string outPartFilename( outputFolder + "/all" + prefix + "parts_d" + boost::lexical_cast<std::string>(levelDepth) + ".txt" );
treePartition.writePartitionSet( outPartFilename, partitionValues, partitionVector);
tree.insertPartitions( partitionVector, partitionValues );
std::string outTreeFilename( outputFolder + "/" + tree.getName() + "_" + prefix + "parts_d" + boost::lexical_cast<std::string>(levelDepth) );
outTreeFilename += ( ".txt" );
tree.writeTree( outTreeFilename, niftiMode );
}
std::vector < unsigned int > filterRadii;
//filterRadii.reserve( 6 );
// filterRadii.push_back( 1 );
// filterRadii.push_back( 2 );
// filterRadii.push_back( 5 );
// filterRadii.push_back( 10 );
// filterRadii.push_back( 15 );
// filterRadii.push_back( 20 );
filterRadii.push_back( filterRadius );
for(size_t i=0; i< filterRadii.size(); ++i)
{
if( filterRadii[i] <= 0 )
{
continue;
}
std::vector< float > filtPartValues( partitionValues );
std::vector< std::vector< size_t> > filtPartVector( partitionVector );
std::cout << "Filtering with a radius of "<< filterRadii[i] << "..." <<std::endl;
treePartition.filterMaxPartitions( filterRadii[i], &filtPartValues, &filtPartVector );
std::cout << filtPartValues.size() << " Filtered partitions obtained, writing to file..." <<std::endl;
logFile <<"Filtered partitions:\t"<< filtPartValues.size() <<std::endl;
std::string outPartFilename( outputFolder + "/filt" + prefix + "parts_d" + boost::lexical_cast<std::string>(levelDepth) );
outPartFilename += ( "_r" + boost::lexical_cast<std::string>(filterRadii[i]) + ".txt" );
treePartition.writePartitionSet(outPartFilename, filtPartValues, filtPartVector);
std::cout << "Adding filtered partitions to tree and writing..." <<std::endl;
std::string outTreeFilename( outputFolder + "/" + tree.getName() + "_" + prefix + "parts_d" + boost::lexical_cast<std::string>(levelDepth) );
outTreeFilename += ( "_r" + boost::lexical_cast<std::string>(filterRadii[i]) + ".txt" );
tree.insertPartitions( filtPartVector, filtPartValues );
tree.writeTree( outTreeFilename, niftiMode );
}
/////////////////////////////////////////////////////////////////
// save and print total time
time_t programEndTime(time(NULL));
int totalTime( difftime(programEndTime,programStartTime) );
std::cout <<"Program Finished, total time: "<< totalTime/3600 <<"h "<< (totalTime%3600)/60 <<"' "<< ((totalTime%3600)%60) <<"\" "<< std::endl;
logFile <<"-------------"<<std::endl;
logFile <<"Finish Time:\t"<< ctime(&programEndTime) <<std::endl;
logFile <<"Elapsed time : "<< totalTime/3600 <<"h "<< (totalTime%3600)/60 <<"' "<< ((totalTime%3600)%60) <<"\""<< std::endl;
// }
// catch(std::exception& e)
// {
// std::cout << e.what() << std::endl;
// return 1;
// }
return 0;
}
//--------------------------------------------------------------------------------------------------
int main(int argc, char** argv)
{
// Read in a configuration file
if ( argc < 2 )
{
fprintf( stderr, "No configuration file provided\n" );
showUsage( argv[ 0 ] );
return -1;
}
std::cout << "Starting Camera Calibration" << std::endl;
cv::Size boardSize;
cv::Size boardSizeMm;
cv::Size imageSize;
std::string cameraName;
bool bUseDotPattern;
std::string configFilename( argv[ 1 ] );
std::vector<std::string> NameLocation = LoadConfig(
configFilename,&boardSize,&boardSizeMm,&cameraName,&bUseDotPattern);
float squareWidth = ((float)boardSizeMm.width/1000.0f)/(boardSize.width-1);
float squareHeight = ((float)boardSizeMm.height/1000.0f)/(boardSize.height-1);
std::cout << squareWidth << " " << squareHeight << std::endl;
std::vector<cv::Point3f> objectCorners;
//The points in the world coordinates
std::vector<std::vector<cv::Point3f>> objectPoints;
//The points positions in pixels
std::vector<std::vector<cv::Point2f>> imagePoints;
//Camera output matrices
cv::Mat cameraMatrix;
cv::Mat distCoeffs;
int successes = 0;
//3D Scene Points
//Initialize the chessboard corners
//in the chessboard reference frame
//The corners are at 3D location (x,y,z) = (i,j,0)
for(int i=boardSize.height-1; i>=0; i--)
for(int j=0; j<boardSize.width; j++)
objectCorners.push_back(cv::Point3f(j*squareWidth,i*squareHeight,0.0f));
for(int i = 0; i < (int)NameLocation.size(); i++)
{
std::string ImageAddress = NameLocation.at(i);
std::cout << "Image Name " <<ImageAddress << std::endl;
cv::Mat image,colorimage1,colorimage2;
image =cv::imread(ImageAddress, CV_LOAD_IMAGE_GRAYSCALE);
//colorimage1 =cv::imread(ImageAddress, CV_LOAD_IMAGE_COLOR);
//colorimage2 =cv::imread(ImageAddress, CV_LOAD_IMAGE_COLOR);
imageSize.height = image.rows;
imageSize.width = image.cols;
/*cv::imshow("Image",image);
cv::waitKey();
cv::destroyWindow("Image");*/
// output vector of image points
std::vector<cv::Point2f> imageCorners;
// number of corners on the chessboard
bool found = false;
if ( !bUseDotPattern )
{
found = cv::findChessboardCorners(image,boardSize,imageCorners);
if ( found )
{
//cv::drawChessboardCorners(colorimage1,boardSize,imageCorners,found);
//Get subpixel accuracy on the corners
//cv::cornerSubPix(image,imageCorners,cv::Size(5,5),cv::Size(-1,-1),cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS,100,0.225));
//cv::drawChessboardCorners(colorimage2,boardSize,imageCorners,found);
}
}
else
{
printf( "Looking for circles...\n" );
//found = cv::findCirclesGrid(image,boardSize,imageCorners);
BlobDetector::Params params;
//params.minArea = 5.0;
//params.minArea = 5.0;
params.maxArea = 20000.0;
//params.minCircularity = 0.5;
//params.minDistBetweenBlobs = 1.0;
//params.filterByCircularity = false;
//params.filterByInertia = false;
//params.filterByConvexity = false;
//printf( "minDistBetweenBlobs is %f\n", params.min );
cv::Ptr<cv::FeatureDetector> pDetector = new BlobDetector( params );
found = findCirclesGridAB( image, boardSize, imageCorners,
cv::CALIB_CB_SYMMETRIC_GRID, pDetector );
if ( !found )
{
cv::Mat scaled;
float scale;
if ( image.rows < 480 )
{
scale = 2.0;
}
else
{
scale = 0.25;
}
cv::resize( image, scaled, cv::Size( 0, 0 ), scale, scale );
found = findCirclesGridAB( scaled, boardSize, imageCorners,
cv::CALIB_CB_SYMMETRIC_GRID, pDetector );
std::cout << "Found " << imageCorners.size() << " corners" << std::endl;
for ( uint32_t i = 0; i < imageCorners.size(); i++ )
{
imageCorners[ i ].x /= scale;
imageCorners[ i ].y /= scale;
}
}
/*cv::namedWindow("Corners", CV_WINDOW_NORMAL);
cv::drawChessboardCorners(image,boardSize,imageCorners,found);
cv::imshow( "Corners", image );
cv::waitKey();*/
//cv::destroyWindow("Corners");
}
if ( !found )
{
printf( "Warning: Unable to find corners in %s\n", ImageAddress.c_str() );
continue;
}
//cv::drawChessboardCorners(colorimage1,boardSize,imageCorners,found);
//If we have a good board, add it to our data
if(imageCorners.size() == (uint32_t)boardSize.area())
{
//Add Image and scene points from one view
imagePoints.push_back(imageCorners);
objectPoints.push_back(objectCorners);
std::cout << "Successfully found " << imageCorners.size() << " corners" << std::endl;
successes++;
}
else
std::cout << "Failed" << std::endl;
//cv::resize(colorimage1,colorimage1,cv::Size(1024,768));
//cv::resize(colorimage2,colorimage2,cv::Size(1024,768));
//cv::imshow("Pre Sub Pixel",colorimage1);
//cv::imshow("Post Sub Pixel",colorimage2);
//cv::waitKey();
//cv::destroyWindow("Pre Sub Pixel");
//cv::destroyWindow("Post Sub Pixel");
}
std::vector<cv::Mat> rvecs,tvecs;
cameraMatrix = cv::Mat::eye( 3, 3, CV_64F );
cameraMatrix.at<double>( 0, 0 ) = 5458.0;
cameraMatrix.at<double>( 1, 1 ) = 5458.0;
cameraMatrix.at<double>( 0, 2 ) = 2272.0/2.0;
cameraMatrix.at<double>( 1, 2 ) = 1704.0/2.0;
distCoeffs = cv::Mat::zeros( 8, 1, CV_64F );
std::cout << cv::calibrateCamera(
objectPoints,imagePoints,imageSize,cameraMatrix,distCoeffs,rvecs,tvecs,
CV_CALIB_USE_INTRINSIC_GUESS
//| CV_CALIB_FIX_PRINCIPAL_POINT
//| CV_CALIB_FIX_ASPECT_RATIO
// | CV_CALIB_ZERO_TANGENT_DIST | CV_CALIB_FIX_K1 | CV_CALIB_FIX_K2 | CV_CALIB_FIX_K3
//| CV_CALIB_FIX_K4 | CV_CALIB_FIX_K5 | CV_CALIB_FIX_K6
)<< std::endl;
cv::FileStorage fs((cameraName + "_cameraMatrix.yml").c_str(), cv::FileStorage::WRITE);
fs << "cameraMatrix" << cameraMatrix;
fs << "distCoeffs" << distCoeffs;
std::cout << cameraMatrix << std::endl;
std::cout << "Finished Camera Calibration" << std::endl;
return 0;
}
int main( int argc, char *argv[] )
{
// try {
time_t programStartTime(time(NULL));
boost::filesystem::path workingDir( boost::filesystem::current_path());
// ========== PROGRAM PARAMETERS ==========
std::string progName("cpcc");
std::string configFilename("../../config/"+progName+".cfg");
// program parameters
std::string treeFilename;
std::string distMatrixFolder;
unsigned int threads(0);
bool niftiMode( true );
bool verbose(false);
// Declare a group of options that will be allowed only on command line
boost::program_options::options_description genericOptions("Generic options");
genericOptions.add_options()
( "version", "Program version" )
( "help,h", "Produce extended program help message" )
( "tree,t", boost::program_options::value< std::string >(&treeFilename), "file with the hierarchical tree to compute the cpcc value from")
( "inputf,I", boost::program_options::value< std::string >(&distMatrixFolder), "Input data folder with the distance matrix files.")
;
// Declare a group of options that will be allowed both on command line and in config file
boost::program_options::options_description configOptions("Configuration");
configOptions.add_options()
( "verbose,v", "[opt] verbose output." )
( "vista", "[opt] use vista file format (default is nifti)." )
( "pthreads,p", boost::program_options::value< unsigned int >(&threads), "[opt] number of processing cores to run the program in. Default: all available." )
;
// Hidden options, will be allowed both on command line and in config file, but will not be shown to the user.
boost::program_options::options_description hiddenOptions("Hidden options");
//hiddenOptions.add_options() ;
boost::program_options::options_description cmdlineOptions;
cmdlineOptions.add(genericOptions).add(configOptions).add(hiddenOptions);
boost::program_options::options_description configFileOptions;
configFileOptions.add(configOptions).add(hiddenOptions);
boost::program_options::options_description visibleOptions("Allowed options");
visibleOptions.add(genericOptions).add(configOptions);
boost::program_options::positional_options_description posOpt; //this arguments do not need to specify the option descriptor when typed in
posOpt.add("tree", -1);
boost::program_options::variables_map variableMap;
store(boost::program_options::command_line_parser(argc, argv).options(cmdlineOptions).positional(posOpt).run(), variableMap);
std::ifstream ifs(configFilename.c_str());
store(parse_config_file(ifs, configFileOptions), variableMap);
notify(variableMap);
if (variableMap.count("help"))
{
std::cout << "---------------------------------------------------------------------------" << std::endl;
std::cout << std::endl;
std::cout << " Project: hClustering" << std::endl;
std::cout << std::endl;
std::cout << " Whole-Brain Connectivity-Based Hierarchical Parcellation Project" << std::endl;
std::cout << " David Moreno-Dominguez" << std::endl;
std::cout << " [email protected]" << std::endl;
std::cout << " [email protected]" << std::endl;
std::cout << " www.cbs.mpg.de/~moreno" << std::endl;
std::cout << std::endl;
std::cout << " For more reference on the underlying algorithm and research they have been used for refer to:" << std::endl;
std::cout << " - Moreno-Dominguez, D., Anwander, A., & Knösche, T. R. (2014)." << std::endl;
std::cout << " A hierarchical method for whole-brain connectivity-based parcellation." << std::endl;
std::cout << " Human Brain Mapping, 35(10), 5000-5025. doi: http://dx.doi.org/10.1002/hbm.22528" << std::endl;
std::cout << " - Moreno-Dominguez, D. (2014)." << std::endl;
std::cout << " Whole-brain cortical parcellation: A hierarchical method based on dMRI tractography." << std::endl;
std::cout << " PhD Thesis, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig." << std::endl;
std::cout << " ISBN 978-3-941504-45-5" << std::endl;
std::cout << std::endl;
std::cout << " hClustering is free software: you can redistribute it and/or modify" << std::endl;
std::cout << " it under the terms of the GNU Lesser General Public License as published by" << std::endl;
std::cout << " the Free Software Foundation, either version 3 of the License, or" << std::endl;
std::cout << " (at your option) any later version." << std::endl;
std::cout << " http://creativecommons.org/licenses/by-nc/3.0" << std::endl;
std::cout << std::endl;
std::cout << " hClustering is distributed in the hope that it will be useful," << std::endl;
std::cout << " but WITHOUT ANY WARRANTY; without even the implied warranty of" << std::endl;
std::cout << " MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the" << std::endl;
std::cout << " GNU Lesser General Public License for more details." << std::endl;
std::cout << std::endl;
std::cout << "---------------------------------------------------------------------------" << std::endl << std::endl;
std::cout << "cpcc" << std::endl << std::endl;
std::cout << "Compute the cophenetic correlation coefficient (Farris, 1969) of a hierarchical tree." << std::endl << std::endl;
std::cout << "* Arguments:" << std::endl << std::endl;
std::cout << " --version: Program version." << std::endl << std::endl;
std::cout << " -h --help: produce extended program help message." << std::endl << std::endl;
std::cout << " -t --tree: File with the hierarchical tree to compute cpcc from." << std::endl << std::endl;
std::cout << " -I --inputf: Input data folder containing the blocks of the precomputed tract pairwise distance matrix." << std::endl << std::endl;
std::cout << "[-v --verbose]: verbose output (recommended)." << std::endl << std::endl;
std::cout << "[--vista]: read/write vista (.v) files [default is nifti (.nii) and compact (.cmpct) files]." << std::endl << std::endl;
std::cout << "[-p --pthreads]: number of processing threads to run the program in parallel. Default: use all available processors." << std::endl << std::endl;
std::cout << std::endl;
std::cout << "* Usage example:" << std::endl << std::endl;
std::cout << " cpcc -t tree_lh.txt -I distBlocks/ -v" << std::endl << std::endl;
std::cout << std::endl;
std::cout << "* Outputs:" << std::endl << std::endl;
std::cout << " - Introduces the cpcc value in the #cpcc field of the tree file defined at option -t." << std::endl;
std::cout << std::endl;
exit(0);
}
if (variableMap.count("version")) {
std::cout << progName <<", version 2.0"<<std::endl;
exit(0);
}
if (variableMap.count("verbose")) {
std::cout << "verbose output"<<std::endl;
verbose=true;
}
if (variableMap.count("pthreads"))
{
if (threads==1)
{
std::cout <<"Using a single processor"<< std::endl;
}
else if(threads==0 || threads>=omp_get_max_threads())
{
threads = omp_get_max_threads();
std::cout <<"Using all available processors ("<< threads <<")." << std::endl;
}
else
{
std::cout <<"Using a maximum of "<< threads <<" processors "<< std::endl;
}
omp_set_num_threads( threads );
}
else
{
threads = omp_get_max_threads();
omp_set_num_threads( threads );
std::cout <<"Using all available processors ("<< threads <<")." << std::endl;
}
if (variableMap.count("tree")) {
if(!boost::filesystem::is_regular_file(boost::filesystem::path(treeFilename))) {
std::cerr << "ERROR: tree file \""<<treeFilename<<"\" is not a regular file"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
std::cout << "Input tree file: "<< treeFilename << std::endl;
} else {
std::cerr << "ERROR: no tree file stated"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if (variableMap.count("inputf")) {
if(!boost::filesystem::is_directory(boost::filesystem::path(distMatrixFolder))) {
std::cerr << "ERROR: distance matrix folder \""<<distMatrixFolder<<"\" is not a directory"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
std::cout << "Distance matrix folder: "<< distMatrixFolder << std::endl;
} else {
std::cerr << "ERROR: no distance matrix folder stated"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if ( variableMap.count( "vista" ) )
{
if( verbose )
{
std::cout << "Using vista format" << std::endl;
}
fileManagerFactory fmf;
fmf.setVista();
niftiMode = false;
}
else
{
if( verbose )
{
std::cout << "Using nifti format" << std::endl;
}
fileManagerFactory fmf;
fmf.setNifti();
niftiMode = true;
}
/////////////////////////////////////////////////////////////////
WHtree tree(treeFilename);
if (verbose)
{
std::cout<<tree.getReport()<<std::endl;
}
if( !tree.isLoaded() )
{
std::cerr << "Error while loading tree "<< std::endl;
exit(-1);
}
treeManager treeMngr(&tree, verbose);
treeMngr.setDistMatrixFolder(distMatrixFolder);
float cpcc(treeMngr.doCpcc());
tree.writeTree(treeFilename,niftiMode);
std::cout<<std::endl<<std::endl<<"CPCC: "<< cpcc <<std::endl<<std::endl;
/////////////////////////////////////////////////////////////////
// save and print total time
time_t programEndTime(time(NULL));
int totalTime( difftime(programEndTime,programStartTime) );
std::cout << "Program Finished, total time: " << totalTime/3600 <<"h "<< (totalTime%3600)/60 <<"' "<< ((totalTime%3600)%60) <<"\""<< std::endl;
// }
// catch(std::exception& e)
// {
// std::cout << e.what() << std::endl;
// return 1;
// }
return 0;
}
int main( int argc, char *argv[] )
{
// try {
time_t programStartTime(time(NULL));
boost::filesystem::path workingDir( boost::filesystem::current_path());
// ========== PROGRAM PARAMETERS ==========
std::string progName("matchpartition");
std::string configFilename("../../config/"+progName+".cfg");
// program parameters
std::string refTreeFilename, targetTreeFilename, matchTableFilename, outputFolder;
unsigned int searchDepth(1);
float lambda(0);
bool signaturePart(false), colorMatching(false), overlapPart(false), exclusive(false);
bool verbose(false), niftiMode( true );
// Declare a group of options that will be allowed only on command line
boost::program_options::options_description genericOptions("Generic options");
genericOptions.add_options()
( "version", "Program version" )
( "help,h", "Produce extended program help message" )
( "reference,r", boost::program_options::value< std::string >(&refTreeFilename), "file with reference partitioned tree" )
( "target,t", boost::program_options::value< std::string >(&targetTreeFilename), "file with target tree to be partitioned-matched" )
( "leafmatch,m", boost::program_options::value< std::string >(&matchTableFilename), "file with meta-leaves (base-nodes) matching table" )
( "outputf,O", boost::program_options::value< std::string >(&outputFolder), "output folder where partition-matched trees will be written" )
( "signature,s", boost::program_options::value< float >(&lambda), "[xor with -o and -c] Signature-based partition matching, inster lambda coefficient value" )
( "overlap,o", "[xor with -s and -c] Meta-leaf overlap-based partition matching")
( "depth,d", boost::program_options::value< unsigned int >(&searchDepth)->implicit_value(0), "[opt] partition search depth. Default: 0 (automatic partition-size based adaptive depth, recommended)")
( "justcolor,c", "[xor with -s and -o] Perform only olor matching (requires pre-computed partitions in both trees)")
( "excl,x", "[opt] color exclusively clusters that have a match, clusters without match will be white")
;
// Declare a group of options that will be allowed both on command line and in config file
boost::program_options::options_description configOptions("Configuration");
configOptions.add_options()
( "verbose,v", "[opt] verbose output." )
( "vista", "[opt] Write output tree in vista coordinates (default is nifti)." )
;
// Hidden options, will be allowed both on command line and in config file, but will not be shown to the user.
boost::program_options::options_description hiddenOptions("Hidden options");
//hiddenOptions.add_options() ;
boost::program_options::options_description cmdlineOptions;
cmdlineOptions.add(genericOptions).add(configOptions).add(hiddenOptions);
boost::program_options::options_description configFileOptions;
configFileOptions.add(configOptions).add(hiddenOptions);
boost::program_options::options_description visibleOptions("Allowed options");
visibleOptions.add(genericOptions).add(configOptions);
boost::program_options::positional_options_description posOpt; //this arguments do not need to specify the option descriptor when typed in
//posOpt.add("roi-file", -1);
boost::program_options::variables_map variableMap;
store(boost::program_options::command_line_parser(argc, argv).options(cmdlineOptions).positional(posOpt).run(), variableMap);
std::ifstream ifs(configFilename.c_str());
store(parse_config_file(ifs, configFileOptions), variableMap);
notify(variableMap);
if (variableMap.count( "help" ) )
{
std::cout << "---------------------------------------------------------------------------" << std::endl;
std::cout << std::endl;
std::cout << " Project: hClustering" << std::endl;
std::cout << std::endl;
std::cout << " Whole-Brain Connectivity-Based Hierarchical Parcellation Project" << std::endl;
std::cout << " David Moreno-Dominguez" << std::endl;
std::cout << " [email protected]" << std::endl;
std::cout << " [email protected]" << std::endl;
std::cout << " www.cbs.mpg.de/~moreno" << std::endl;
std::cout << std::endl;
std::cout << " For more reference on the underlying algorithm and research they have been used for refer to:" << std::endl;
std::cout << " - Moreno-Dominguez, D., Anwander, A., & Knösche, T. R. (2014)." << std::endl;
std::cout << " A hierarchical method for whole-brain connectivity-based parcellation." << std::endl;
std::cout << " Human Brain Mapping, 35(10), 5000-5025. doi: http://dx.doi.org/10.1002/hbm.22528" << std::endl;
std::cout << " - Moreno-Dominguez, D. (2014)." << std::endl;
std::cout << " Whole-brain cortical parcellation: A hierarchical method based on dMRI tractography." << std::endl;
std::cout << " PhD Thesis, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig." << std::endl;
std::cout << " ISBN 978-3-941504-45-5" << std::endl;
std::cout << std::endl;
std::cout << " hClustering is free software: you can redistribute it and/or modify" << std::endl;
std::cout << " it under the terms of the GNU Lesser General Public License as published by" << std::endl;
std::cout << " the Free Software Foundation, either version 3 of the License, or" << std::endl;
std::cout << " (at your option) any later version." << std::endl;
std::cout << " http://creativecommons.org/licenses/by-nc/3.0" << std::endl;
std::cout << std::endl;
std::cout << " hClustering is distributed in the hope that it will be useful," << std::endl;
std::cout << " but WITHOUT ANY WARRANTY; without even the implied warranty of" << std::endl;
std::cout << " MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the" << std::endl;
std::cout << " GNU Lesser General Public License for more details." << std::endl;
std::cout << std::endl;
std::cout << "---------------------------------------------------------------------------" << std::endl << std::endl;
std::cout << "matchpartition" << std::endl << std::endl;
std::cout << "Finds the best matching corresponding partitions in a target tree to those present in an unrelated reference tree (meta-leaf matching across these two trees must have been precomputed using comparetrees)." << std::endl;
std::cout << " Two partition matching algorithms are available: signature matching and overlap matching. Found target partitions will be color-matched as best as possible." << std::endl;
std::cout << " There is also the possibility of only color-matching predefined partitions of the target tree to predefined partitions of the reference tree." << std::endl << std::endl;
std::cout << "* Arguments:" << std::endl << std::endl;
std::cout << " --version: Program version." << std::endl << std::endl;
std::cout << " -h --help: produce extended program help message." << std::endl << std::endl;
std::cout << " -r --reference: The tree file with the reference partitioned tree." << std::endl << std::endl;
std::cout << " -t --target: The tree file with the target tree to find matching partitions in (or with partitions to be color-matched)." << std::endl << std::endl;
std::cout << " -m --leafmatch File with the meta-leaf matching information across both trees (output of comparetrees command)." << std::endl << std::endl;
std::cout << " -O --outputf: Output folder where partitioned/color matched tree files will be written." << std::endl << std::endl;
std::cout << "[-s --signature]: Signature-based partition matching, instert lambda coefficient value. [xor with -o and -c]." << std::endl;
std::cout << " In this method a pair signature matrices are computed for each reference-target partitions to find the quality of the match." << std::endl;
std::cout << " Each signature matrix defines a value for each pair of base-nodes of the tree it belongs to: 1 the base nodes are found in the same cluster, 0 if otherwise." << std::endl;
std::cout << " The higher the correlation between the reference and target-derived matrices, the best match is the target tree partition to the reference tree one." << std::endl;
std::cout << " A smart hierarchical search through possible partritions is conducted to find the one with best signature matching." << std::endl;
std::cout << " The lambda coefficient determines if and how a similar number of clusters in both partitions affects the matching quality value," << std::endl;
std::cout << " Lambda=0 -> cluster number does not affect the quality value. Lambda=1 -> cluster value similarity has as much weight as singature correlation." << std::endl << std::endl;
std::cout << "[-o --overlap]: Overlap-based partition matching. [xor with -o and -c]." << std::endl;
std::cout << " A match between two partititionsis found by iteratively matching clusters with higher base-node overlap and resolving possible ambiguities." << std::endl;
std::cout << " The matching quality between partitions is defined as the number of base-nodes pairs that are classified in the same way in both partitions" << std::endl;
std::cout << " (both in the smae cluster r both in different clusters) against the total number of pair combinations." << std::endl;
std::cout << " A smart hierarchical search through possible partritions is conducted to find the one with best signature matching." << std::endl << std::endl;
std::cout << "[-d --depth]: Partition search depth (for signature and overlap matching. A higher value will mean a more exhaustive search of the possible partitions," << std::endl;
std::cout << " but also a higher computation time, specially if the partition to be matched has a high number of clusters (>100)." << std::endl;
std::cout << " The default value (0, recommended) will adaptively give high search depth to low-cluster partitions and lower search depth to high-cluster partittions." << std::endl << std::endl;
std::cout << "[-c --justcolor]: Perform only color matching across reference and target tree parttitions (both trees need to have the same number of precompouted partitions)." << std::endl;
std::cout << " In multiple-to-one matching cases clusters from the reference tree might also be recolored to better identify matching relationships across partitions." << std::endl << std::endl;
std::cout << "[-x --excl]: Color exclusively clusters that have a match, clusters without match will be recolored white (on both reference and target trees)" << std::endl << std::endl;
std::cout << "[-v --verbose]: Verbose output (recommended)." << std::endl << std::endl;
std::cout << "[--vista]: Write output tree files in vista coordinates (default is nifti)." << std::endl << std::endl;
std::cout << std::endl;
std::cout << "* Usage example:" << std::endl << std::endl;
std::cout << " matchpartition -r refTree.txt -t targetTree.txt -m matching.txt -O results/ -s 0.5 -v" << std::endl << std::endl;
exit(0);
}
if (variableMap.count( "version" ) )
{
std::cout << progName <<", version 2.0"<<std::endl;
exit(0);
}
if ( variableMap.count( "verbose" ) )
{
std::cout << "verbose output" << std::endl;
verbose=true;
}
if ( variableMap.count( "vista" ) )
{
if( verbose )
{
std::cout << "Using vista coordinates" << std::endl;
}
fileManagerFactory fmf;
fmf.setVista();
niftiMode = false;
}
else
{
if( verbose )
{
std::cout << "Using nifti coordinates" << std::endl;
}
fileManagerFactory fmf;
fmf.setNifti();
niftiMode = true;
}
if (variableMap.count("reference"))
{
if(!boost::filesystem::is_regular_file( boost::filesystem::path( refTreeFilename ) ) )
{
std::cerr << "ERROR: reference tree file \""<<refTreeFilename<<"\" is not a regular file"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
std::cout << "Reference tree file: "<< refTreeFilename << std::endl;
}
else
{
std::cerr << "ERROR: no reference tree file stated"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if (variableMap.count( "target" ) )
{
if(!boost::filesystem::is_regular_file(boost::filesystem::path( targetTreeFilename ) ) )
{
std::cerr << "ERROR: target tree file \""<<targetTreeFilename<<"\" is not a regular file"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
std::cout << "Target tree file: "<< targetTreeFilename << std::endl;
} else {
std::cerr << "ERROR: no target tree file stated"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if (variableMap.count( "leafmatch" ) )
{
if(!boost::filesystem::is_regular_file(boost::filesystem::path( matchTableFilename ) ) )
{
std::cerr << "ERROR: match table file \""<<matchTableFilename<<"\" is not a regular file"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
std::cout << "Match table file: "<< matchTableFilename << std::endl;
}
else
{
std::cerr << "ERROR: no match Table file stated"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if( variableMap.count( "signature" ) + variableMap.count( "overlap" ) + variableMap.count( "justcolor" ) > 1 )
{
std::cerr << "ERROR: multiple matching types selected, please use only one from -s, -o, -c."<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if (variableMap.count( "signature" ) )
{
std::cout << "Performing Signature partition matching (and color matching)" << std::endl;
std::cout <<" Using a lambda factor of "<< lambda << std::endl;
signaturePart = true;
colorMatching = true;
}
else if (variableMap.count( "overlap" ) )
{
std::cout << "Performing Overlap partition matching (and color matching): " << std::endl;
overlapPart = true;
colorMatching = true;
}
else if (variableMap.count( "justcolor" ) )
{
std::cout << "Performing only color matching: " << std::endl;
colorMatching = true;
}
else
{
std::cerr << "ERROR: no matching type selected, select signature, overlap or color matching"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
if (variableMap.count( "excl" ) )
{
std::cout << "Color exclusively matched clusters (unmatched clusters will be white) " << std::endl;
exclusive = true;
}
if( signaturePart || overlapPart )
{
if( searchDepth > 5 )
{
std::cout << "Level depth indicated: " << searchDepth << " is too high, setting to a maximum of 5" << std::endl;
searchDepth = 5;
}
else if ( searchDepth = 0 )
{
std::cout << "Using automatic parttion-size based adaptive search depth " << std::endl;
}
else
{
std::cout << "Using a search depth of: " << searchDepth << std::endl;
}
}
if (variableMap.count( "outputf" ) )
{
if(!boost::filesystem::is_directory(boost::filesystem::path( outputFolder ) ) )
{
std::cerr << "ERROR: output folder \""<<outputFolder<<"\" is not a directory"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
std::cout << "Output folder: "<< outputFolder << std::endl;
}
else
{
std::cerr << "ERROR: no output folder stated"<<std::endl;
std::cerr << visibleOptions << std::endl;
exit(-1);
}
std::string logFilename(outputFolder+"/"+progName+"_log.txt");
std::ofstream logFile(logFilename.c_str());
if(!logFile) {
std::cerr << "ERROR: unable to open log file: \""<<logFilename<<"\""<<std::endl;
exit(-1);
}
logFile <<"Start Time:\t"<< ctime(&programStartTime) <<std::endl;
logFile <<"Working directory:\t"<< workingDir.string() <<std::endl;
logFile <<"Verbose:\t"<< verbose <<std::endl;
logFile <<"Reference tree:\t"<< refTreeFilename <<std::endl;
logFile <<"Target tree:\t"<< targetTreeFilename <<std::endl;
logFile <<"Matching table:\t"<< matchTableFilename <<std::endl;
logFile <<"Output folder:\t"<< outputFolder <<std::endl;
if( niftiMode )
{
logFile << "Using nifti coordinates" << std::endl;
}
else
{
logFile << "Using vista coordinates" << std::endl;
}
logFile <<"-------------"<<std::endl;
/////////////////////////////////////////////////////////////////
WHtree refTree( refTreeFilename );
WHtree targetTree( targetTreeFilename );
if (!refTree.isLoaded() || !targetTree.isLoaded() )
{
throw std::runtime_error ("ERROR @ compareTrees(): trees are not loaded");
}
logFile <<"Reference Tree: "<< refTree.getReport(false) <<std::endl;
logFile <<"Target Tree: "<< targetTree.getReport(false) <<std::endl;
if (refTree.getDataSize() != targetTree.getDataSize() )
{
std::cerr <<"Reference Tree: "<< refTree.getReport() <<std::endl;
std::cerr <<"Target Tree: "<< targetTree.getReport() <<std::endl;
throw std::runtime_error ("ERROR @ compareTrees() datasets have different dimensions");
}
if (verbose) {
std::cout <<"Reference Tree: "<< refTree.getReport(false) <<std::endl;
std::cout <<"Target Tree: "<< targetTree.getReport(false) <<std::endl;
}
partitionMatcher matcher(&refTree,&targetTree,matchTableFilename, verbose);
std::string depthString;
if( searchDepth > 0 )
{
depthString = "_d"+string_utils::toString< unsigned int >( searchDepth ) ;
}
std::cout <<matcher.reportBaseNodes()<<std::endl;
std::string suffixPart("_pm_Signature_l" + string_utils::toString< float >( lambda ) + depthString + ".txt");
std::string suffixNew("_pm_Overlap" + depthString + ".txt");
std::string suffixColor("_colorMatch.txt");
bool refTreeColorsChanged( false );
if( signaturePart )
{
logFile << "Signature Matching" << std::endl;
logFile << "Lambda:\t" << lambda <<std::endl;
logFile << "Search depth:\t" << searchDepth <<std::endl;
matcher.findMatchingPartitions( lambda );
}
else if ( overlapPart )
{
logFile << "Overlap Matching" <<std::endl;
logFile << "Search depth:\t" << searchDepth <<std::endl;
matcher.findMatchingPartitions( -1 );
}
if( colorMatching )
{
logFile << "Color Matching" <<std::endl;
refTreeColorsChanged = matcher.matchColors( exclusive );
}
std::string refOutput;
std::string targetOutput;
if ( signaturePart )
{
targetOutput = outputFolder + "/" + targetTree.getName() + suffixPart;
}
else if ( overlapPart )
{
targetOutput = outputFolder + "/" + targetTree.getName() + suffixNew ;
}
else
{
targetOutput = outputFolder + "/" + targetTree.getName() + suffixColor;
}
if( refTreeColorsChanged )
{
refOutput = outputFolder + "/" + refTree.getName() + suffixColor;
}
else
{
refOutput = outputFolder + "/" + refTree.getName() + ".txt";
}
if( verbose )
{
std::cout << "Writing output target tree file to " << targetOutput << std::endl;
std::cout << "Writing output reference tree file to " << refOutput << std::endl;
}
targetTree.writeTree( targetOutput, niftiMode );
refTree.writeTree( refOutput, niftiMode );
logFile << "Written output target tree file to " << targetOutput << std::endl;
logFile << "Written output reference tree file to " << refOutput << std::endl;
/////////////////////////////////////////////////////////////////
// save and print total time
time_t programEndTime( time( NULL ) );
int totalTime( difftime( programEndTime, programStartTime ) );
std::cout <<"Program Finished, total time: "<< totalTime/3600 <<"h "<< (totalTime%3600)/60 <<"' "<< ((totalTime%3600)%60) <<"\" "<< std::endl;
logFile <<"-------------"<<std::endl;
logFile <<"Finish Time:\t"<< ctime(&programEndTime) <<std::endl;
logFile <<"Elapsed time : "<< totalTime/3600 <<"h "<< (totalTime%3600)/60 <<"' "<< ((totalTime%3600)%60) <<"\""<< std::endl;
// }
// catch(std::exception& e)
// {
// std::cout << e.what() << std::endl;
// return 1;
// }
return 0;
}
/**
Find out operating system name and version
This method caches system information in m_osName, m_osVersion and m_osAlias.
It requires m_unameInfo to be set prior to call.
*/
void SCXOSTypeInfo::Init() // private
{
m_osVersion = L"";
m_osName = L"Unknown";
assert(m_unameIsValid);
#if defined(hpux) || defined(sun)
if (m_unameIsValid)
{
m_osName = StrFromUTF8(m_unameInfo.sysname);
m_osVersion = StrFromUTF8(m_unameInfo.release);
}
#if defined(hpux)
m_osAlias = L"HPUX";
m_osManufacturer = L"Hewlett-Packard Company";
#elif defined(sun)
m_osAlias = L"Solaris";
m_osManufacturer = L"Oracle Corporation";
#endif
#elif defined(aix)
if (m_unameIsValid)
{
m_osName = StrFromUTF8(m_unameInfo.sysname);
// To get "5.3" we must read "5" and "3" from different fields.
string ver(m_unameInfo.version);
ver.append(".");
ver.append(m_unameInfo.release);
m_osVersion = StrFromUTF8(ver);
}
m_osAlias = L"AIX";
m_osManufacturer = L"International Business Machines Corporation";
#elif defined(linux)
vector<wstring> lines;
SCXStream::NLFs nlfs;
#if defined(PF_DISTRO_SUSE)
static const string relFileName = "/etc/SuSE-release";
wifstream relfile(relFileName.c_str());
wstring version(L"");
wstring patchlevel(L"");
SCXStream::ReadAllLines(relfile, lines, nlfs);
if (!lines.empty()) {
m_osName = ExtractOSName(lines[0]);
}
// Set the Linux Caption (get first line of the /etc/SuSE-release file)
m_linuxDistroCaption = lines[0];
if (0 == m_linuxDistroCaption.length())
{
// Fallback - should not normally happen
m_linuxDistroCaption = L"SuSE";
}
// File contains one or more lines looking like this:
// SUSE Linux Enterprise Server 10 (i586)
// VERSION = 10
// PATCHLEVEL = 1
for (size_t i = 0; i<lines.size(); i++)
{
if (StrIsPrefix(StrTrim(lines[i]), L"VERSION", true))
{
wstring::size_type n = lines[i].find_first_of(L"=");
if (n != wstring::npos)
{
version = StrTrim(lines[i].substr(n+1));
}
}
else if (StrIsPrefix(StrTrim(lines[i]), L"PATCHLEVEL", true))
{
wstring::size_type n = lines[i].find_first_of(L"=");
if (n != wstring::npos)
{
patchlevel = StrTrim(lines[i].substr(n+1));
}
}
}
if (version.length() > 0)
{
m_osVersion = version;
if (patchlevel.length() > 0)
{
m_osVersion = version.append(L".").append(patchlevel);
}
}
if (std::wstring::npos != m_osName.find(L"Desktop"))
{
m_osAlias = L"SLED";
}
else
{ // Assume server.
m_osAlias = L"SLES";
}
m_osManufacturer = L"SUSE GmbH";
#elif defined(PF_DISTRO_REDHAT)
static const string relFileName = "/etc/redhat-release";
wifstream relfile(relFileName.c_str());
SCXStream::ReadAllLines(relfile, lines, nlfs);
if (!lines.empty()) {
m_osName = ExtractOSName(lines[0]);
}
// Set the Linux Caption (get first line of the /etc/redhat-release file)
m_linuxDistroCaption = lines[0];
if (0 == m_linuxDistroCaption.length())
{
// Fallback - should not normally happen
m_linuxDistroCaption = L"Red Hat";
}
// File should contain one line that looks like this:
// Red Hat Enterprise Linux Server release 5.1 (Tikanga)
if (lines.size() > 0)
{
wstring::size_type n = lines[0].find_first_of(L"0123456789");
if (n != wstring::npos)
{
wstring::size_type n2 = lines[0].substr(n).find_first_of(L" \t\n\t");
m_osVersion = StrTrim(lines[0].substr(n,n2));
}
}
if ((std::wstring::npos != m_osName.find(L"Client")) // RHED5
|| (std::wstring::npos != m_osName.find(L"Desktop"))) // RHED4
{
m_osAlias = L"RHED";
}
else
{ // Assume server.
m_osAlias = L"RHEL";
}
m_osManufacturer = L"Red Hat, Inc.";
#elif defined(PF_DISTRO_ULINUX)
// The release file is created at agent start time by init.d startup script
// This is done to insure that we can write to the appropriate directory at
// the time (since, at agent run-time, we may not have root privileges).
//
// If we CAN create the file here (if we're running as root), then we'll
// do so here. But in the normal case, this shouldn't be necessary. Only
// in "weird" cases (i.e. starting omiserver by hand, for example).
// Create the release file by running GetLinuxOS.sh script
// (if we have root privileges)
try
{
if ( !SCXFile::Exists(m_deps->getReleasePath()) &&
SCXFile::Exists(m_deps->getScriptPath()) &&
m_deps->isReleasePathWritable() )
{
std::istringstream in;
std::ostringstream out;
std::ostringstream err;
int ret = SCXCoreLib::SCXProcess::Run(m_deps->getScriptPath().c_str(), in, out, err, 10000);
if ( ret || out.str().length() || err.str().length() )
{
wostringstream sout;
sout << L"Unexpected errors running script: " << m_deps->getScriptPath().c_str()
<< L", return code: " << ret
<< L", stdout: " << StrFromUTF8(out.str())
<< L", stderr: " << StrFromUTF8(err.str());
SCX_LOGERROR(m_log, sout.str() );
}
}
}
catch(SCXCoreLib::SCXInterruptedProcessException &e)
{
wstring msg;
msg = L"Timeout running script \"" + m_deps->getScriptPath() +
L"\", " + e.Where() + L'.';
SCX_LOGERROR(m_log, msg );
};
// Look in release file for O/S information
string sFile = StrToUTF8(m_deps->getReleasePath());
wifstream fin(sFile.c_str());
SCXStream::ReadAllLines(fin, lines, nlfs);
if (!lines.empty())
{
ExtractToken(L"OSName", lines, m_osName);
ExtractToken(L"OSVersion", lines, m_osVersion);
ExtractToken(L"OSFullName", lines, m_linuxDistroCaption);
ExtractToken(L"OSAlias", lines, m_osAlias);
ExtractToken(L"OSManufacturer", lines, m_osManufacturer);
}
else
{
m_osAlias = L"Universal";
}
// Behavior for m_osCompatName (method GetOSName) should be as follows:
// PostInstall scripts will first look for SCX-RELEASE file (only on universal kits)
// If found, add "ORIGINAL_KIT_TYPE=Universal" to scxconfig.conf file,
// else add "ORIGINAL_KIT_TYPE=!Universal" to scxconfig.conf file.
// After that is set up, the SCX-RELEASE file is created.
//
// A RHEL system should of OSAlias of "RHEL, SLES system should have "SuSE" (in scx-release)
//
// We need to mimic return values for RHEL and SLES on universal kits that did not
// have a universal kit installed previously, but only for RHEL and SLES kits. In
// all other cases, continue to return "Linux Distribution".
wstring configFilename(m_deps->getConfigPath());
SCXConfigFile configFile(configFilename);
try
{
configFile.LoadConfig();
}
catch(SCXFilePathNotFoundException &e)
{
// Something's whacky with postinstall, so we can't follow algorithm
static SCXCoreLib::LogSuppressor suppressor(SCXCoreLib::eError, SCXCoreLib::eTrace);
wstring logMessage(L"Unable to load configuration file " + configFilename);
SCX_LOG(m_log, suppressor.GetSeverity(logMessage), logMessage);
m_osCompatName = L"Unknown Linux Distribution";
}
if ( m_osCompatName.empty() )
{
wstring kitType;
if ( configFile.GetValue(L"ORIGINAL_KIT_TYPE", kitType) )
{
if ( L"!Universal" == kitType )
{
if ( L"RHEL" == m_osAlias )
{
m_osCompatName = L"Red Hat Distribution";
}
else if ( L"SLES" == m_osAlias )
{
m_osCompatName = L"SuSE Distribution";
}
}
}
if ( m_osCompatName.empty() )
{
m_osCompatName = L"Linux Distribution";
}
}
#else
#error "Linux Platform not supported";
#endif
#elif defined(macos)
m_osAlias = L"MacOS";
m_osManufacturer = L"Apple Inc.";
if (m_unameIsValid)
{
// MacOS is called "Darwin" in uname info, so we hard-code here
m_osName = L"Mac OS";
// This value we could read dynamically from the xml file
// /System/Library/CoreServices/SystemVersion.plist, but that
// file may be named differently based on client/server, and
// reading the plist file would require framework stuff.
//
// Rather than using the plist, we'll use Gestalt, which is an
// API designed to figure out versions of anything and everything.
// Note that use of Gestalt requires the use of framework stuff
// as well, so the Makefiles for MacOS are modified for that.
SInt32 major, minor, bugfix;
if (0 != Gestalt(gestaltSystemVersionMajor, &major)
|| 0 != Gestalt(gestaltSystemVersionMinor, &minor)
|| 0 != Gestalt(gestaltSystemVersionBugFix, &bugfix))
{
throw SCXCoreLib::SCXErrnoException(L"Gestalt", errno, SCXSRCLOCATION);
}
wostringstream sout;
sout << major << L"." << minor << L"." << bugfix;
m_osVersion = sout.str();
}
#else
#error "Platform not supported"
#endif
}
// this is just a workbench. most of the stuff here will go into the Frontend class.
int main(int argc, char **argv) {
ros::init(argc, argv, "okvis_node_synchronous");
google::InitGoogleLogging(argv[0]);
FLAGS_stderrthreshold = 0; // INFO: 0, WARNING: 1, ERROR: 2, FATAL: 3
FLAGS_colorlogtostderr = 1;
if (argc != 3 && argc != 4) {
LOG(ERROR) <<
"Usage: ./" << argv[0] << " configuration-yaml-file bag-to-read-from [skip-first-seconds]";
return -1;
}
okvis::Duration deltaT(0.0);
if (argc == 4) {
deltaT = okvis::Duration(atof(argv[3]));
}
// set up the node
ros::NodeHandle nh("okvis_node");
// publisher
okvis::Publisher publisher(nh);
// read configuration file
std::string configFilename(argv[1]);
okvis::RosParametersReader vio_parameters_reader(configFilename);
okvis::VioParameters parameters;
vio_parameters_reader.getParameters(parameters);
okvis::ThreadedKFVio okvis_estimator(parameters);
okvis_estimator.setFullStateCallback(std::bind(&okvis::Publisher::publishFullStateAsCallback,&publisher,std::placeholders::_1,std::placeholders::_2,std::placeholders::_3,std::placeholders::_4));
okvis_estimator.setLandmarksCallback(std::bind(&okvis::Publisher::publishLandmarksAsCallback,&publisher,std::placeholders::_1,std::placeholders::_2,std::placeholders::_3));
okvis_estimator.setStateCallback(std::bind(&okvis::Publisher::publishStateAsCallback,&publisher,std::placeholders::_1,std::placeholders::_2));
okvis_estimator.setBlocking(true);
publisher.setParameters(parameters); // pass the specified publishing stuff
// extract the folder path
std::string bagname(argv[2]);
size_t pos = bagname.find_last_of("/");
std::string path;
if (pos == std::string::npos)
path = ".";
else
path = bagname.substr(0, pos);
const unsigned int numCameras = parameters.nCameraSystem.numCameras();
// setup files to be written
publisher.setCsvFile(path + "/okvis_estimator_output.csv");
publisher.setLandmarksCsvFile(path + "/okvis_estimator_landmarks.csv");
okvis_estimator.setImuCsvFile(path + "/imu0_data.csv");
for (size_t i = 0; i < numCameras; ++i) {
std::stringstream num;
num << i;
okvis_estimator.setTracksCsvFile(i, path + "/cam" + num.str() + "_tracks.csv");
}
// open the bag
rosbag::Bag bag(argv[2], rosbag::bagmode::Read);
// views on topics. the slash is needs to be correct, it's ridiculous...
std::string imu_topic("/imu0");
rosbag::View view_imu(
bag,
rosbag::TopicQuery(imu_topic));
if (view_imu.size() == 0) {
LOG(ERROR) << "no imu topic";
return -1;
}
rosbag::View::iterator view_imu_iterator = view_imu.begin();
LOG(INFO) << "No. IMU messages: " << view_imu.size();
std::vector<std::shared_ptr<rosbag::View> > view_cams_ptr;
std::vector<rosbag::View::iterator> view_cam_iterators;
std::vector<okvis::Time> times;
okvis::Time latest(0);
for(size_t i=0; i<numCameras;++i) {
std::string camera_topic("/cam"+std::to_string(i)+"/image_raw");
std::shared_ptr<rosbag::View> view_ptr(
new rosbag::View(
bag,
rosbag::TopicQuery(camera_topic)));
if (view_ptr->size() == 0) {
LOG(ERROR) << "no camera topic";
return 1;
}
view_cams_ptr.push_back(view_ptr);
view_cam_iterators.push_back(view_ptr->begin());
sensor_msgs::ImageConstPtr msg1 = view_cam_iterators[i]
->instantiate<sensor_msgs::Image>();
times.push_back(
okvis::Time(msg1->header.stamp.sec, msg1->header.stamp.nsec));
if (times.back() > latest)
latest = times.back();
LOG(INFO) << "No. cam " << i << " messages: " << view_cams_ptr.back()->size();
}
for(size_t i=0; i<numCameras;++i) {
if ((latest - times[i]).toSec() > 0.01)
view_cam_iterators[i]++;
}
int counter = 0;
okvis::Time start(0.0);
while (ros::ok()) {
ros::spinOnce();
okvis_estimator.display();
// check if at the end
if (view_imu_iterator == view_imu.end()){
std::cout << std::endl << "Finished. Press any key to exit." << std::endl << std::flush;
char k = 0;
while(k==0 && ros::ok()){
k = cv::waitKey(1);
ros::spinOnce();
}
return 0;
}
for (size_t i = 0; i < numCameras; ++i) {
if (view_cam_iterators[i] == view_cams_ptr[i]->end()) {
std::cout << std::endl << "Finished. Press any key to exit." << std::endl << std::flush;
char k = 0;
while(k==0 && ros::ok()){
k = cv::waitKey(1);
ros::spinOnce();
}
return 0;
}
}
// add images
okvis::Time t;
for(size_t i=0; i<numCameras;++i) {
sensor_msgs::ImageConstPtr msg1 = view_cam_iterators[i]
->instantiate<sensor_msgs::Image>();
cv::Mat filtered(msg1->height, msg1->width, CV_8UC1);
memcpy(filtered.data, &msg1->data[0], msg1->height * msg1->width);
t = okvis::Time(msg1->header.stamp.sec, msg1->header.stamp.nsec);
if (start == okvis::Time(0.0)) {
start = t;
}
// get all IMU measurements till then
okvis::Time t_imu=start;
do {
sensor_msgs::ImuConstPtr msg = view_imu_iterator
->instantiate<sensor_msgs::Imu>();
Eigen::Vector3d gyr(msg->angular_velocity.x, msg->angular_velocity.y,
msg->angular_velocity.z);
Eigen::Vector3d acc(msg->linear_acceleration.x,
msg->linear_acceleration.y,
msg->linear_acceleration.z);
t_imu = okvis::Time(msg->header.stamp.sec, msg->header.stamp.nsec);
// add the IMU measurement for (blocking) processing
if (t_imu - start > deltaT)
okvis_estimator.addImuMeasurement(t_imu, acc, gyr);
view_imu_iterator++;
} while (view_imu_iterator != view_imu.end() && t_imu <= t);
// add the image to the frontend for (blocking) processing
if (t - start > deltaT)
okvis_estimator.addImage(t, i, filtered);
view_cam_iterators[i]++;
}
++counter;
// display progress
if (counter % 20 == 0) {
std::cout
<< "\rProgress: "
<< int(double(counter) / double(view_cams_ptr.back()->size()) * 100)
<< "% " ;
}
}
std::cout << std::endl;
return 0;
}
