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Impala::Application Namespace Reference

Classes
class	WindowAnnoVidSet
class	WindowBackground
class	ConceptLearnClient
class	DataServer
class	FileServer
class	WindowImBrowse
class	WindowPlay
class	WindowShow
class	WindowShowImSet
class	WindowShowVidSet
class	WindowTrecResult
class	WindowTrecSearch
class	WindowVdiff
class	WindowVidBrowse
Namespaces
namespace	IDash
namespace	Client
namespace	DataTransfer
namespace	DemoCamera2d
namespace	FileClient
namespace	Im
namespace	Repository
namespace	Src
namespace	Table
namespace	Util
namespace	Video
namespace	VidSet
namespace	MediaTable
namespace	VideoExcel
namespace	SDash
namespace	TagsLife
namespace	Videolympics
Functions
Table::SimilarityTableSet *	LearnConceptFromAnnotations (CmdOptions &options, Matrix::DistributedAccess &da, String concept, String modelname, Table::AnnotationTable *annotations, Util::Database *db)
int	RunDistributedLearningEngine (CmdOptions &options)
int	mainActiveLearner (int argc, char **argv)
	ILOG_VAR_INIT (WindowAnnoVidSet, Application)
char	GetKeyBinding (std::string name, std::string dflt)
int	mainAnnoVidSet (int argc, char *argv[])
int	mainBackground (int argc, char *argv[])
	ILOG_VAR_INIT (ConceptLearnClient, Application)
int	mainConceptLearnClient (int argc, char *argv[])
int	mainConstructCodebook (int argc, char *argv[])
void	WriteResults (Util::PropertySet *properties, DataFactory *dataFactory, String concept, ParameterSearcher *searcher)
void	CrossValidate (Util::PropertySet *properties, Training::Factory *trainFactory, DataFactory *dataFactory)
int	mainCrossValidate (int argc, char **argv)
	ILOG_VAR_INIT (DataServer, Impala.Application)
int	mainServer (int argc, char *argv[])
	ILOG_VAR_INIT (FileServer, Impala.Application)
int	mainFileServer (int argc, char *argv[])
int	mainImBrowse (int argc, char *argv[])
int	mainImSet (int argc, char *argv[])
int	mainJobRunner (int argc, char *argv[])
int	mainJobServer (int argc, char *argv[])
int	mainPlay (int argc, char *argv[])
bool	CheckParameteres (CmdOptions &options, RawDataSet *dataset, RawDataSet *dataset2, std::vector< Feature::FeatureDefinition > &featureDefs, std::vector< double > &weights, String resultname)
	This function loops over the command line arguments to find (weight,featureDef)-pairs.
Feature::FeatureTable *	OpenFeatureTable (Feature::FeatureDefinition &featureDef, RawDataSet *dataset)
	opens feature table in MPI mode only node0 reads the table, then it is broadcasted
void	GetPartialTask (int &partcount, int &row, int &column)
	This functions figures out which part of the table this process should process.
void	CheckQuids (Feature::FeatureTable *f, RawDataSet *set, RawDataSet *set2, String resultname, int part, int partcount)
	This function does two things: store the quid table of the part of the matrix processed by this node so the whole table in case of single process if there are more than one feature table, check that the quids are consistent.
Feature::FeatureTable *	GetPartial (Feature::FeatureTable *f, int partnumber, int partcount)
	Split table in subtables depending on this nodes id and the number of nodes if partcount == 1 the the full table is returned.
Matrix::Mat *	ComputeMatrix (Feature::FeatureTable *devel, Feature::FeatureTable *test, String resultname, RawDataSet *set, RawDataSet *set2)
	Input one or two feature tables and out comes the kernel distance matrix.
double	GetAverage (Matrix::Mat *distanceMatrix)
	the average is broadcasted over all nodes
void	WriteInfoFile (int columns, int rows, int partcount, String filepathname, Util::Database *db)
void	WriteAverages (String filepathname, Util::Database *db, std::vector< double > averages)
void	LoadAverages (RawDataSet *set, String filepathname, std::vector< double > &averages)
void	WriteResult (String resultname, Util::Database *db, Matrix::Mat *accumulator)
int	mainPrecomputeKernelMatrix (CmdOptions &options)
Matrix::Mat *	CreateTestMat (int row, int column, int partCount, int totalSize)
void	CreateTestQuids (String resultname, Util::Database *db, int part, int partCount, int totalSize)
int	makeTestMatrix (CmdOptions &options)
int	mainShotSegmentation (int argc, char *argv[])
	ILOG_VAR_INIT_TEMPL_1 (WindowShow, ArrayT, Application)
int	mainShow (int argc, char *argv[])
	ILOG_VAR_INIT (WindowShowImSet, Application)
int	mainShowImSet (int argc, char *argv[])
	ILOG_VAR_INIT (WindowShowVidSet, Application)
int	mainShowVidSet (int argc, char *argv[])
int	TrainModel (Training::Factory *trainFactory, DataFactory *dataFactory, bool distKernel)
int	mainTrainModel (int argc, char **argv)
int	mainTrecResult (int argc, char *argv[])
	ILOG_VAR_INIT (WindowTrecSearch, Application)
int	mainTrecSearch (int argc, char *argv[])
int	mainVdiff (int argc, char *argv[])
int	mainVidBrowse (int argc, char *argv[])
int	mainVideoJobManager (int argc, char *argv[])
const String	cSetName ("test.txt")
Core::VideoSet::VideoSet *	MakeVideoSet (String directory, Core::VideoSet::VideoSet *indexSrc)
	This version creates a dataset that uses the index of src (if src != 0) So it is a 'Fake' dataset in the sense that it doen't have to have a VideoData folder at all, as long as the original has.
Core::VideoSet::VideoSet *	MakeVideoSet (String directory)
int	main (int argc, char **argv)

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