|| || || || || ||

---

Impala::Core::Training::ApplyConcepts Class Reference

This class handles the logic of applying trained models to a dataset. More...

#include <ApplyConcepts.h>

Collaboration diagram for Impala::Core::Training::ApplyConcepts:

[legend]List of all members.

Public Types
typedef Table::ScoreTable	ScoreTable
typedef Feature::FeatureDefinition	FeatureDefinition
typedef Feature::FeatureTable	FeatureTable
typedef Table::KeywordList	KeywordList
typedef Persistency::ModelLocator	ModelLocator
typedef Persistency::FeatureLocator	FeatureLocator
typedef Persistency::SimilarityTableSetLocator	SimilarityTableSetLocator
Public Member Functions
	ApplyConcepts (CmdOptions &options, Database::RawDataSet *dataSet, bool onIndex)
	c'tor reads the following from the command options: 1) read by mainVidSet or mainImSet 2) video/image-set that the models were trained on 3) filename of the concepts for which there are models 4) 'model type' 5) featuredef or precomputed kernel name
virtual	~ApplyConcepts ()
virtual void	SetWalkType (CString walkType)
virtual void	NextContainer (CString container)
Private Member Functions
ApplyConceptsHelper *	MakeHelper (bool isPrecomputed, bool fik)
Private Attributes
ApplyConceptsHelper *	mHelper
KeywordList	mConcepts
ModelLocator	mModelLoc
FeatureLocator	mFeatLoc
SimilarityTableSetLocator	mSimSetLoc
Database::RawDataSet *	mDataSet
Database::RawDataSet *	mAnnoSet
bool	mKernelDataOnly
	ILOG_VAR_DEC

---

Detailed Description

This class handles the logic of applying trained models to a dataset.

It typically works with mainVidSet or mainImSet. Although the code is correct at the moment some code (and the interface) might need to change in the future. Especailly the use of factories can make the code a lot cleaner.

Definition at line 31 of file ApplyConcepts.h.

---

The documentation for this class was generated from the following file:

• Core/Training/ApplyConcepts.h

---