Artificial Neural Networks - Multi-Layer Perceptrons. More...

#include <opencv2/ml.hpp>

Inheritance diagram for cv::ml::ANN_MLP_ANNEAL:

Public Member Functions
virtual double	getAnnealCoolingRatio () const =0

virtual double	getAnnealFinalT () const =0

virtual double	getAnnealInitialT () const =0

virtual int	getAnnealItePerStep () const =0

virtual void	setAnnealCoolingRatio (double val)=0

virtual void	setAnnealEnergyRNG (const RNG &rng)=0
	Set/initialize anneal RNG. More...

virtual void	setAnnealFinalT (double val)=0

virtual void	setAnnealInitialT (double val)=0

virtual void	setAnnealItePerStep (int val)=0

Public Member Functions inherited from cv::ml::ANN_MLP
double	getAnnealCoolingRatio () const

double	getAnnealFinalT () const

double	getAnnealInitialT () const

int	getAnnealItePerStep () const

virtual double	getBackpropMomentumScale () const =0

virtual double	getBackpropWeightScale () const =0

virtual cv::Mat	getLayerSizes () const =0

virtual double	getRpropDW0 () const =0

virtual double	getRpropDWMax () const =0

virtual double	getRpropDWMin () const =0

virtual double	getRpropDWMinus () const =0

virtual double	getRpropDWPlus () const =0

virtual TermCriteria	getTermCriteria () const =0

virtual int	getTrainMethod () const =0

virtual Mat	getWeights (int layerIdx) const =0

virtual void	setActivationFunction (int type, double param1=0, double param2=0)=0

void	setAnnealCoolingRatio (double val)

void	setAnnealEnergyRNG (const RNG &rng)
	Set/initialize anneal RNG. More...

void	setAnnealFinalT (double val)

void	setAnnealInitialT (double val)

void	setAnnealItePerStep (int val)

virtual void	setBackpropMomentumScale (double val)=0

virtual void	setBackpropWeightScale (double val)=0

virtual void	setLayerSizes (InputArray _layer_sizes)=0

virtual void	setRpropDW0 (double val)=0

virtual void	setRpropDWMax (double val)=0

virtual void	setRpropDWMin (double val)=0

virtual void	setRpropDWMinus (double val)=0

virtual void	setRpropDWPlus (double val)=0

virtual void	setTermCriteria (TermCriteria val)=0

virtual void	setTrainMethod (int method, double param1=0, double param2=0)=0

Public Member Functions inherited from cv::ml::StatModel
virtual float	calcError (const Ptr< TrainData > &data, bool test, OutputArray resp) const
	Computes error on the training or test dataset. More...

virtual bool	empty () const CV_OVERRIDE
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...

virtual int	getVarCount () const =0
	Returns the number of variables in training samples. More...

virtual bool	isClassifier () const =0
	Returns true if the model is classifier. More...

virtual bool	isTrained () const =0
	Returns true if the model is trained. More...

virtual float	predict (InputArray samples, OutputArray results=noArray(), int flags=0) const =0
	Predicts response(s) for the provided sample(s) More...

virtual bool	train (const Ptr< TrainData > &trainData, int flags=0)
	Trains the statistical model. More...

virtual bool	train (InputArray samples, int layout, InputArray responses)
	Trains the statistical model. More...

Public Member Functions inherited from cv::Algorithm
	Algorithm ()

virtual	~Algorithm ()

virtual void	clear ()
	Clears the algorithm state. More...

virtual String	getDefaultName () const

virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage. More...

virtual void	save (const String &filename) const

virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage. More...

void	write (FileStorage &fs, const String &name) const

void	write (const Ptr< FileStorage > &fs, const String &name=String()) const

Additional Inherited Members
Public Types inherited from cv::ml::ANN_MLP
enum	ActivationFunctions { IDENTITY = 0, SIGMOID_SYM = 1, GAUSSIAN = 2, RELU = 3, LEAKYRELU = 4 }

enum	TrainFlags { UPDATE_WEIGHTS = 1, NO_INPUT_SCALE = 2, NO_OUTPUT_SCALE = 4 }

enum	TrainingMethods { BACKPROP =0, RPROP = 1, ANNEAL = 2 }

Public Types inherited from cv::ml::StatModel
enum	Flags { UPDATE_MODEL = 1, RAW_OUTPUT =1, COMPRESSED_INPUT =2, PREPROCESSED_INPUT =4 }

Static Public Member Functions inherited from cv::ml::ANN_MLP
static Ptr< ANN_MLP >	create ()
	Creates empty model. More...

static Ptr< ANN_MLP >	load (const String &filepath)
	Loads and creates a serialized ANN from a file. More...

Static Public Member Functions inherited from cv::ml::StatModel
template<typename _Tp >
static Ptr< _Tp >	train (const Ptr< TrainData > &data, int flags=0)
	Create and train model with default parameters. More...

Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file. More...

template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String. More...

template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node. More...

Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Artificial Neural Networks - Multi-Layer Perceptrons.

See also: Neural Networks

Member Function Documentation

◆ getAnnealCoolingRatio()

virtual double cv::ml::ANN_MLP_ANNEAL::getAnnealCoolingRatio ( ) const

pure virtual

Python:
	cv.ml.ANN_MLP_ANNEAL.getAnnealCoolingRatio(		) ->	retval

ANNEAL: Update cooling ratio. It must be >0 and less than 1. Default value is 0.95.

See also: setAnnealCoolingRatio

◆ getAnnealFinalT()

virtual double cv::ml::ANN_MLP_ANNEAL::getAnnealFinalT ( ) const

pure virtual

Python:
	cv.ml.ANN_MLP_ANNEAL.getAnnealFinalT(		) ->	retval

ANNEAL: Update final temperature. It must be >=0 and less than initialT. Default value is 0.1.

See also: setAnnealFinalT

◆ getAnnealInitialT()

virtual double cv::ml::ANN_MLP_ANNEAL::getAnnealInitialT ( ) const

pure virtual

Python:
	cv.ml.ANN_MLP_ANNEAL.getAnnealInitialT(		) ->	retval

See also: setAnnealInitialT

◆ getAnnealItePerStep()

virtual int cv::ml::ANN_MLP_ANNEAL::getAnnealItePerStep ( ) const

pure virtual

Python:
	cv.ml.ANN_MLP_ANNEAL.getAnnealItePerStep(		) ->	retval

ANNEAL: Update iteration per step. It must be >0 . Default value is 10.

See also: setAnnealItePerStep

◆ setAnnealCoolingRatio()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealCoolingRatio ( double val )

pure virtual

Python:
	cv.ml.ANN_MLP_ANNEAL.setAnnealCoolingRatio(	val	) ->	None

See also: getAnnealCoolingRatio

◆ setAnnealEnergyRNG()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealEnergyRNG ( const RNG & rng )

pure virtual

Set/initialize anneal RNG.

◆ setAnnealFinalT()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealFinalT ( double val )

pure virtual

Python:
	cv.ml.ANN_MLP_ANNEAL.setAnnealFinalT(	val	) ->	None

See also: getAnnealFinalT

◆ setAnnealInitialT()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealInitialT ( double val )

pure virtual

Python:
	cv.ml.ANN_MLP_ANNEAL.setAnnealInitialT(	val	) ->	None

See also: getAnnealInitialT

◆ setAnnealItePerStep()

virtual void cv::ml::ANN_MLP_ANNEAL::setAnnealItePerStep ( int val )

pure virtual

Python:
	cv.ml.ANN_MLP_ANNEAL.setAnnealItePerStep(	val	) ->	None

See also: getAnnealItePerStep

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

opencv2/ml.hpp

Public Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ getAnnealCoolingRatio()

◆ getAnnealFinalT()

◆ getAnnealInitialT()

◆ getAnnealItePerStep()

◆ setAnnealCoolingRatio()

◆ setAnnealEnergyRNG()

◆ setAnnealFinalT()

◆ setAnnealInitialT()

◆ setAnnealItePerStep()