Factory class for the generation of search predictors. More...

#include <cvb/polimago/search_predictor_factory.hpp>

Public Member Functions
	SearchPredictorFactory ()
	Constructor. More...

int	SampleSize () const noexcept
	Gets the sample size that has been used in each training set. More...

void	SetSampleSize (int sampleSize)
	Sets the sample size that has been used in each training set. More...

double	ExtractionRadius () const noexcept
	Gets the radius for extracting positive search instances. More...

void	SetExtractionRadius (double radius)
	Sets the radius for extracting positive search instances. More...

ValueRange< Angle >	AngleRange () const
	Gets the range of angles to be covered during classifier training. More...

void	SetAngleRange (ValueRange< Angle > range)
	Sets the range of angles to be covered during classifier training. More...

ValueRange< double >	ScaleRange () const
	Gets the range of scale factors to be covered during classifier training. Only meaningful if the invariance type RotationScaleTranslation has been set. More...

void	SetScaleRange (ValueRange< double > range)
	Sets the range of scale factors to be covered during classifier training. Only meaningful if the invariance type RotationScaleTranslation has been set. More...

ValueRange< double >	SingularValueRange () const
	Gets the range of permissible singular values to be covered during classifier training. Only meaningful if the invariance type AffineGroup has been set. More...

void	SetSingularValueRange (ValueRange< double > range)
	Sets the range of permissible singular values to be covered during classifier training. Only meaningful if the invariance type AffineGroup has been set. More...

InvarianceType	Invariances () const noexcept
	Gets the invariances to be used for generating the classifier. More...

void	SetInvariances (InvarianceType invariances)
	Sets the invariances to be used for generating the classifier. More...

int	NumClassificationSteps () const noexcept
	Gets the number of classification steps during search operation. More...

void	SetNumClassificationSteps (int numSteps)
	Sets the number of classification steps during search operation. More...

int	FeatureResolutionStep1And2 () const noexcept
	Gets the feature resolution (determines the size of the classification retina) for search step 1 and 2. More...

void	SetFeatureResolutionStep1And2 (int resolution)
	Sets the feature resolution (determines the size of the classification retina) for search step 1 and 2. More...

int	FeatureResolutionRest () const noexcept
	Gets the feature resolution (determines the size of the classification retina) for step 3 and up. More...

void	SetFeatureResolutionRest (int resolution)
	Sets the feature resolution (determines the size of the classification retina) for step 3 and up. More...

void	UseSettingsFromPredictor (const SearchPredictor &clf)
	Copy the predictor generation settings from a predictor. More...

Public Member Functions inherited from PredictorFactoryBase
double	Lambda () const noexcept
	Gets the regularization value to be used for generating the object. More...

void	SetLambda (double lambda)
	Sets the regularization value to be used for generating the object. Possible values range from 0 to 10, good starting values for experiments are usually around 0.01. More...

String	Preprocessing () const
	Get preprocessing code with which the object is to be generated. More...

void	SetPreprocessing (const String &code)
	Set preprocessing code with which the object is to be generated. More...

Static Public Member Functions
static ValueRange< double >	ScaleFactorRangeDefault ()
	Default value for the scale factor range.

static ValueRange< double >	SingularValueRangeDefault ()
	Default value for the singular value range.

static ValueRange< double >	ScaleFactorRange ()
	Acceptable scale factor range for search classifier training.

Static Public Member Functions inherited from PredictorFactoryBase
static ValueRange< double >	LambdaRange ()
	Acceptable scale factor range for search classifier training.

static ValueRange< int >	FeatureResolutionRange ()
	Valid range of feature resolution value.

static constexpr std::array< char, 4 >	PreprocessingValidCharacters ()
	Characters that a preprocessing string may contain.

static String	FormatPreprocessingCode (const String &input)
	Correct a preprocessing code to make sure that no invalid characters are in the code and the code does not exceed the maximum length. More...

Static Public Attributes
static constexpr int	NumClassificationStepsMin = 3
	Minimum classification step count.

static constexpr int	SampleSizeMin = 1
	Absolute minimum value for SampleSize.

Static Public Attributes inherited from PredictorFactoryBase
static constexpr double	LambdaDefault = 0.1
	Default value for lambda.

static constexpr int	FeatureResolutionDefault = 1
	Default value for feature resolution.

static constexpr int	PreprocessingMaxLength = 15
	Maximum length of a preprocessing code (excluding the terminating zero).

Detailed Description

Factory class for the generation of search predictors.

Constructor & Destructor Documentation

◆ SearchPredictorFactory()

SearchPredictorFactory ( )

inline

Constructor.

Exceptions

Any	exception derived from std::exception including CvbException.

Member Function Documentation

◆ AngleRange()

ValueRange< Angle > AngleRange ( ) const

inline

Gets the range of angles to be covered during classifier training.

Returns: The angle range.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ ExtractionRadius()

double ExtractionRadius ( ) const

inlinenoexcept

Gets the radius for extracting positive search instances.

Returns: The extration radius.

Exceptions

Does	not throw any exception.

The unit size is the size of the feature window, i.e. a value of 0.5 means that positive samples can be extracted from withing a range of +/- Feature Window Width and +/- Feature Window Height around each trained instance. Smaller values will necessitate a finer search grid but may yield better results on difficult search tasks.

◆ FeatureResolutionRest()

int FeatureResolutionRest ( ) const

inlinenoexcept

Gets the feature resolution (determines the size of the classification retina) for step 3 and up.

Returns: The feature resolution.

Exceptions

Does	not throw any exception.

◆ FeatureResolutionStep1And2()

int FeatureResolutionStep1And2 ( ) const

inlinenoexcept

Gets the feature resolution (determines the size of the classification retina) for search step 1 and 2.

Returns: The feature resolution.

Exceptions

Does	not throw any exception.

◆ Invariances()

InvarianceType Invariances ( ) const

inlinenoexcept

Gets the invariances to be used for generating the classifier.

Returns: The invariance type.

Exceptions

Does	not throw any exception.

◆ NumClassificationSteps()

int NumClassificationSteps ( ) const

inlinenoexcept

Gets the number of classification steps during search operation.

Returns: The number of steps.

Exceptions

Does	not throw any exception.

◆ SampleSize()

int SampleSize ( ) const

inlinenoexcept

Gets the sample size that has been used in each training set.

Returns: The sample size.

Exceptions

Does	not throw any exception.

◆ ScaleRange()

ValueRange< double > ScaleRange ( ) const

inline

Gets the range of scale factors to be covered during classifier training. Only meaningful if the invariance type RotationScaleTranslation has been set.

Returns: The scale range.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ SetAngleRange()

void SetAngleRange ( ValueRange< Angle > range )

inline

Sets the range of angles to be covered during classifier training.

Parameters

[in] range The angle range.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ SetExtractionRadius()

void SetExtractionRadius ( double radius )

inline

Sets the radius for extracting positive search instances.

Parameters

[in] radius The extration radius.

Exceptions

Any	exception derived from std::exception including CvbException.

The unit size is the size of the feature window, i.e. a value of 0.5 means that positive samples can be extracted from withing a range of +/- Feature Window Width and +/- Feature Window Height around each trained instance. Smaller values will necessitate a finer search grid but may yield better results on difficult search tasks.

◆ SetFeatureResolutionRest()

void SetFeatureResolutionRest ( int resolution )

inline

Sets the feature resolution (determines the size of the classification retina) for step 3 and up.

Parameters

[in] resolution The feature resolution.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ SetFeatureResolutionStep1And2()

void SetFeatureResolutionStep1And2 ( int resolution )

inline

Sets the feature resolution (determines the size of the classification retina) for search step 1 and 2.

Parameters

[in] resolution The feature resolution.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ SetInvariances()

void SetInvariances ( InvarianceType invariances )

inline

Sets the invariances to be used for generating the classifier.

Parameters

[in] invariances The invariance type.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ SetNumClassificationSteps()

void SetNumClassificationSteps ( int numSteps )

inline

Sets the number of classification steps during search operation.

Parameters

[in] numSteps The number of steps.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ SetSampleSize()

void SetSampleSize ( int sampleSize )

inline

Sets the sample size that has been used in each training set.

Parameters

[in] sampleSize The sample size.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ SetScaleRange()

void SetScaleRange ( ValueRange< double > range )

inline

Sets the range of scale factors to be covered during classifier training. Only meaningful if the invariance type RotationScaleTranslation has been set.

Parameters

[in] range The scale range.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ SetSingularValueRange()

void SetSingularValueRange ( ValueRange< double > range )

inline

Sets the range of permissible singular values to be covered during classifier training. Only meaningful if the invariance type AffineGroup has been set.

Parameters

[in] range The singular value range.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ SingularValueRange()

ValueRange< double > SingularValueRange ( ) const

inline

Gets the range of permissible singular values to be covered during classifier training. Only meaningful if the invariance type AffineGroup has been set.

Returns: The singular value range.

Exceptions

Any	exception derived from std::exception including CvbException.

◆ UseSettingsFromPredictor()

void UseSettingsFromPredictor ( const SearchPredictor & clf )

inline

Copy the predictor generation settings from a predictor.

Parameters

[in] clf Predictor to take the settings from.

Exceptions

Any	exception derived from std::exception including CvbException.

Public Member Functions

Static Public Member Functions

Static Public Attributes

Detailed Description

Constructor & Destructor Documentation

◆ SearchPredictorFactory()

Member Function Documentation

◆ AngleRange()

◆ ExtractionRadius()

◆ FeatureResolutionRest()

◆ FeatureResolutionStep1And2()

◆ Invariances()

◆ NumClassificationSteps()

◆ SampleSize()

◆ ScaleRange()

◆ SetAngleRange()

◆ SetExtractionRadius()

◆ SetFeatureResolutionRest()

◆ SetFeatureResolutionStep1And2()

◆ SetInvariances()

◆ SetNumClassificationSteps()

◆ SetSampleSize()

◆ SetScaleRange()

◆ SetSingularValueRange()

◆ SingularValueRange()

◆ UseSettingsFromPredictor()