OpenCVForUnity.MlModule.ANN_MLP Class Reference

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

Public Member Functions
double	getAnnealCoolingRatio ()
double	getAnnealFinalT ()
double	getAnnealInitialT ()
int	getAnnealItePerStep ()
double	getBackpropMomentumScale ()
double	getBackpropWeightScale ()
Mat	getLayerSizes ()
double	getRpropDW0 ()
double	getRpropDWMax ()
double	getRpropDWMin ()
double	getRpropDWMinus ()
double	getRpropDWPlus ()
TermCriteria	getTermCriteria ()
double double double epsilon	getTermCriteriaAsValueTuple ()
Vec3d	getTermCriteriaAsVec3d ()
int	getTrainMethod ()
Mat	getWeights (int layerIdx)
void	setActivationFunction (int type)
void	setActivationFunction (int type, double param1)
void	setActivationFunction (int type, double param1, double param2)
void	setAnnealCoolingRatio (double val)
void	setAnnealFinalT (double val)
void	setAnnealInitialT (double val)
void	setAnnealItePerStep (int val)
void	setBackpropMomentumScale (double val)
void	setBackpropWeightScale (double val)
void	setLayerSizes (Mat _layer_sizes)
void	setRpropDW0 (double val)
void	setRpropDWMax (double val)
void	setRpropDWMin (double val)
void	setRpropDWMinus (double val)
void	setRpropDWPlus (double val)
void	setTermCriteria (in Vec3d val)
void	setTermCriteria (in(double type, double maxCount, double epsilon) val)
void	setTermCriteria (TermCriteria val)
void	setTrainMethod (int method)
void	setTrainMethod (int method, double param1)
void	setTrainMethod (int method, double param1, double param2)
Public Member Functions inherited from OpenCVForUnity.MlModule.StatModel
float	calcError (TrainData data, bool test, Mat resp)
	Computes error on the training or test dataset.
override bool	empty ()
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
int	getVarCount ()
	Returns the number of variables in training samples.
bool	isClassifier ()
	Returns true if the model is classifier.
bool	isTrained ()
	Returns true if the model is trained.
virtual float	predict (Mat samples)
	Predicts response(s) for the provided sample(s)
virtual float	predict (Mat samples, Mat results)
	Predicts response(s) for the provided sample(s)
virtual float	predict (Mat samples, Mat results, int flags)
	Predicts response(s) for the provided sample(s)
bool	train (Mat samples, int layout, Mat responses)
	Trains the statistical model.
bool	train (TrainData trainData)
	Trains the statistical model.
bool	train (TrainData trainData, int flags)
	Trains the statistical model.
Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
virtual void	clear ()
	Clears the algorithm state.
virtual string	getDefaultName ()
IntPtr	getNativeObjAddr ()
void	save (string filename)
Public Member Functions inherited from OpenCVForUnity.DisposableObject
void	Dispose ()
void	ThrowIfDisposed ()

Static Public Member Functions
static new ANN_MLP	__fromPtr__ (IntPtr addr)
static ANN_MLP	create ()
	Creates empty model.
static ANN_MLP	load (string filepath)
	Loads and creates a serialized ANN from a file.
Static Public Member Functions inherited from OpenCVForUnity.MlModule.StatModel
static new StatModel	__fromPtr__ (IntPtr addr)
Static Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
static Algorithm	__fromPtr__ (IntPtr addr)
Static Public Member Functions inherited from OpenCVForUnity.DisposableObject
static IntPtr	ThrowIfNullIntPtr (IntPtr ptr)

Public Attributes
double double	maxCount
double	type

Static Public Attributes
const int	ANNEAL = 2
const int	BACKPROP = 0
const int	GAUSSIAN = 2
const int	IDENTITY = 0
const int	LEAKYRELU = 4
const int	NO_INPUT_SCALE = 2
const int	NO_OUTPUT_SCALE = 4
const int	RELU = 3
const int	RPROP = 1
const int	SIGMOID_SYM = 1
const int	UPDATE_WEIGHTS = 1
Static Public Attributes inherited from OpenCVForUnity.MlModule.StatModel
const int	COMPRESSED_INPUT = 2
const int	PREPROCESSED_INPUT = 4
const int	RAW_OUTPUT = 1
const int	UPDATE_MODEL = 1

Protected Member Functions
override void	Dispose (bool disposing)
Protected Member Functions inherited from OpenCVForUnity.MlModule.StatModel
override void	Dispose (bool disposing)
Protected Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject
	DisposableOpenCVObject ()
	DisposableOpenCVObject (bool isEnabledDispose)
	DisposableOpenCVObject (IntPtr ptr)
	DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose)
Protected Member Functions inherited from OpenCVForUnity.DisposableObject
	DisposableObject ()
	DisposableObject (bool isEnabledDispose)

Additional Inherited Members
Package Functions inherited from OpenCVForUnity.MlModule.StatModel
Package Functions inherited from OpenCVForUnity.CoreModule.Algorithm
Package Attributes inherited from OpenCVForUnity.DisposableOpenCVObject
Properties inherited from OpenCVForUnity.DisposableObject
bool	IsDisposed [get, protected set]
bool	IsEnabledDispose [get, set]

Detailed Description

Artificial Neural Networks - Multi-Layer Perceptrons.

Unlike many other models in ML that are constructed and trained at once, in the MLP model these steps are separated. First, a network with the specified topology is created using the non-default constructor or the method ANN_MLP.create. All the weights are set to zeros. Then, the network is trained using a set of input and output vectors. The training procedure can be repeated more than once, that is, the weights can be adjusted based on the new training data.

Additional flags for StatModel.train are available: ANN_MLP::TrainFlags.

See also

ml_intro_ann

Member Function Documentation

__fromPtr__()

static new ANN_MLP OpenCVForUnity.MlModule.ANN_MLP.__fromPtr__ ( IntPtr addr )

static

create()

static ANN_MLP OpenCVForUnity.MlModule.ANN_MLP.create ( )

static

Creates empty model.

Use StatModel.train to train the model, Algorithm::load<ANN_MLP>(filename) to load the pre-trained model. Note that the train method has optional flags: ANN_MLP::TrainFlags.

Dispose()

override void OpenCVForUnity.MlModule.ANN_MLP.Dispose ( bool disposing )

protectedvirtual

Reimplemented from OpenCVForUnity.CoreModule.Algorithm.

getAnnealCoolingRatio()

double OpenCVForUnity.MlModule.ANN_MLP.getAnnealCoolingRatio

(

)

See also

setAnnealCoolingRatio

getAnnealFinalT()

double OpenCVForUnity.MlModule.ANN_MLP.getAnnealFinalT

(

)

See also

setAnnealFinalT

getAnnealInitialT()

double OpenCVForUnity.MlModule.ANN_MLP.getAnnealInitialT

(

)

See also

setAnnealInitialT

getAnnealItePerStep()

int OpenCVForUnity.MlModule.ANN_MLP.getAnnealItePerStep

(

)

See also

setAnnealItePerStep

getBackpropMomentumScale()

double OpenCVForUnity.MlModule.ANN_MLP.getBackpropMomentumScale

(

)

See also

setBackpropMomentumScale

getBackpropWeightScale()

double OpenCVForUnity.MlModule.ANN_MLP.getBackpropWeightScale

(

)

See also

setBackpropWeightScale

getLayerSizes()

Mat OpenCVForUnity.MlModule.ANN_MLP.getLayerSizes

(

)

Integer vector specifying the number of neurons in each layer including the input and output layers. The very first element specifies the number of elements in the input layer. The last element - number of elements in the output layer.

See also

setLayerSizes

getRpropDW0()

double OpenCVForUnity.MlModule.ANN_MLP.getRpropDW0

(

)

See also

setRpropDW0

getRpropDWMax()

double OpenCVForUnity.MlModule.ANN_MLP.getRpropDWMax

(

)

See also

setRpropDWMax

getRpropDWMin()

double OpenCVForUnity.MlModule.ANN_MLP.getRpropDWMin

(

)

See also

setRpropDWMin

getRpropDWMinus()

double OpenCVForUnity.MlModule.ANN_MLP.getRpropDWMinus

(

)

See also

setRpropDWMinus

getRpropDWPlus()

double OpenCVForUnity.MlModule.ANN_MLP.getRpropDWPlus

(

)

See also

setRpropDWPlus

getTermCriteria()

TermCriteria OpenCVForUnity.MlModule.ANN_MLP.getTermCriteria

(

)

See also

setTermCriteria

getTermCriteriaAsValueTuple()

double double double epsilon OpenCVForUnity.MlModule.ANN_MLP.getTermCriteriaAsValueTuple

(

)

getTermCriteriaAsVec3d()

Vec3d OpenCVForUnity.MlModule.ANN_MLP.getTermCriteriaAsVec3d

(

)

See also

setTermCriteria

getTrainMethod()

int OpenCVForUnity.MlModule.ANN_MLP.getTrainMethod

(

)

Returns current training method

getWeights()

Mat OpenCVForUnity.MlModule.ANN_MLP.getWeights

(

int

layerIdx

)

load()

static ANN_MLP OpenCVForUnity.MlModule.ANN_MLP.load ( string filepath )

static

Loads and creates a serialized ANN from a file.

Use ANN::save to serialize and store an ANN to disk. Load the ANN from this file again, by calling this function with the path to the file.

Parameters

filepath

path to serialized ANN

setActivationFunction() [1/3]

void OpenCVForUnity.MlModule.ANN_MLP.setActivationFunction

(

int

type

)

Initialize the activation function for each neuron. Currently the default and the only fully supported activation function is ANN_MLP.SIGMOID_SYM.

Parameters

type	The type of activation function. See ANN_MLP::ActivationFunctions.
param1	The first parameter of the activation function, \(\alpha\). Default value is 0.
param2	The second parameter of the activation function, \(\beta\). Default value is 0.

setActivationFunction() [2/3]

void OpenCVForUnity.MlModule.ANN_MLP.setActivationFunction	(	int	type,
		double	param1 )

Initialize the activation function for each neuron. Currently the default and the only fully supported activation function is ANN_MLP.SIGMOID_SYM.

Parameters

type	The type of activation function. See ANN_MLP::ActivationFunctions.
param1	The first parameter of the activation function, \(\alpha\). Default value is 0.
param2	The second parameter of the activation function, \(\beta\). Default value is 0.

setActivationFunction() [3/3]

void OpenCVForUnity.MlModule.ANN_MLP.setActivationFunction	(	int	type,
		double	param1,
		double	param2 )

Initialize the activation function for each neuron. Currently the default and the only fully supported activation function is ANN_MLP.SIGMOID_SYM.

Parameters

type	The type of activation function. See ANN_MLP::ActivationFunctions.
param1	The first parameter of the activation function, \(\alpha\). Default value is 0.
param2	The second parameter of the activation function, \(\beta\). Default value is 0.

setAnnealCoolingRatio()

void OpenCVForUnity.MlModule.ANN_MLP.setAnnealCoolingRatio

(

double

val

)

See also

getAnnealCoolingRatio

setAnnealFinalT()

void OpenCVForUnity.MlModule.ANN_MLP.setAnnealFinalT

(

double

val

)

See also

getAnnealFinalT

setAnnealInitialT()

void OpenCVForUnity.MlModule.ANN_MLP.setAnnealInitialT

(

double

val

)

See also

getAnnealInitialT

setAnnealItePerStep()

void OpenCVForUnity.MlModule.ANN_MLP.setAnnealItePerStep

(

int

val

)

See also

getAnnealItePerStep

setBackpropMomentumScale()

void OpenCVForUnity.MlModule.ANN_MLP.setBackpropMomentumScale

(

double

val

)

See also

getBackpropMomentumScale

setBackpropWeightScale()

void OpenCVForUnity.MlModule.ANN_MLP.setBackpropWeightScale

(

double

val

)

See also

getBackpropWeightScale

setLayerSizes()

void OpenCVForUnity.MlModule.ANN_MLP.setLayerSizes

(

Mat

_layer_sizes

)

Integer vector specifying the number of neurons in each layer including the input and output layers. The very first element specifies the number of elements in the input layer. The last element - number of elements in the output layer. Default value is empty Mat.

See also

getLayerSizes

setRpropDW0()

void OpenCVForUnity.MlModule.ANN_MLP.setRpropDW0

(

double

val

)

See also

getRpropDW0

setRpropDWMax()

void OpenCVForUnity.MlModule.ANN_MLP.setRpropDWMax

(

double

val

)

See also

getRpropDWMax

setRpropDWMin()

void OpenCVForUnity.MlModule.ANN_MLP.setRpropDWMin

(

double

val

)

See also

getRpropDWMin

setRpropDWMinus()

void OpenCVForUnity.MlModule.ANN_MLP.setRpropDWMinus

(

double

val

)

See also

getRpropDWMinus

setRpropDWPlus()

void OpenCVForUnity.MlModule.ANN_MLP.setRpropDWPlus

(

double

val

)

See also

getRpropDWPlus

setTermCriteria() [1/3]

void OpenCVForUnity.MlModule.ANN_MLP.setTermCriteria

(

in Vec3d

val

)

See also

getTermCriteria

setTermCriteria() [2/3]

void OpenCVForUnity.MlModule.ANN_MLP.setTermCriteria

(

in(double type, double maxCount, double epsilon)

val

)

See also

getTermCriteria

setTermCriteria() [3/3]

void OpenCVForUnity.MlModule.ANN_MLP.setTermCriteria

(

TermCriteria

val

)

See also

getTermCriteria

setTrainMethod() [1/3]

void OpenCVForUnity.MlModule.ANN_MLP.setTrainMethod

(

int

method

)

Sets training method and common parameters.

Parameters

method	Default value is ANN_MLP.RPROP. See ANN_MLP::TrainingMethods.
param1	passed to setRpropDW0 for ANN_MLP.RPROP and to setBackpropWeightScale for ANN_MLP.BACKPROP and to initialT for ANN_MLP.ANNEAL.
param2	passed to setRpropDWMin for ANN_MLP.RPROP and to setBackpropMomentumScale for ANN_MLP.BACKPROP and to finalT for ANN_MLP.ANNEAL.

setTrainMethod() [2/3]

void OpenCVForUnity.MlModule.ANN_MLP.setTrainMethod	(	int	method,
		double	param1 )

Sets training method and common parameters.

Parameters

method	Default value is ANN_MLP.RPROP. See ANN_MLP::TrainingMethods.
param1	passed to setRpropDW0 for ANN_MLP.RPROP and to setBackpropWeightScale for ANN_MLP.BACKPROP and to initialT for ANN_MLP.ANNEAL.
param2	passed to setRpropDWMin for ANN_MLP.RPROP and to setBackpropMomentumScale for ANN_MLP.BACKPROP and to finalT for ANN_MLP.ANNEAL.

setTrainMethod() [3/3]

void OpenCVForUnity.MlModule.ANN_MLP.setTrainMethod	(	int	method,
		double	param1,
		double	param2 )

Sets training method and common parameters.

Parameters

method	Default value is ANN_MLP.RPROP. See ANN_MLP::TrainingMethods.
param1	passed to setRpropDW0 for ANN_MLP.RPROP and to setBackpropWeightScale for ANN_MLP.BACKPROP and to initialT for ANN_MLP.ANNEAL.
param2	passed to setRpropDWMin for ANN_MLP.RPROP and to setBackpropMomentumScale for ANN_MLP.BACKPROP and to finalT for ANN_MLP.ANNEAL.

Member Data Documentation

ANNEAL

const int OpenCVForUnity.MlModule.ANN_MLP.ANNEAL = 2

static

BACKPROP

const int OpenCVForUnity.MlModule.ANN_MLP.BACKPROP = 0

static

GAUSSIAN

const int OpenCVForUnity.MlModule.ANN_MLP.GAUSSIAN = 2

static

IDENTITY

const int OpenCVForUnity.MlModule.ANN_MLP.IDENTITY = 0

static

LEAKYRELU

const int OpenCVForUnity.MlModule.ANN_MLP.LEAKYRELU = 4

static

maxCount

double double OpenCVForUnity.MlModule.ANN_MLP.maxCount

NO_INPUT_SCALE

const int OpenCVForUnity.MlModule.ANN_MLP.NO_INPUT_SCALE = 2

static

NO_OUTPUT_SCALE

const int OpenCVForUnity.MlModule.ANN_MLP.NO_OUTPUT_SCALE = 4

static

RELU

const int OpenCVForUnity.MlModule.ANN_MLP.RELU = 3

static

RPROP

const int OpenCVForUnity.MlModule.ANN_MLP.RPROP = 1

static

SIGMOID_SYM

const int OpenCVForUnity.MlModule.ANN_MLP.SIGMOID_SYM = 1

static

type

double OpenCVForUnity.MlModule.ANN_MLP.type

See also

setTermCriteria

UPDATE_WEIGHTS

const int OpenCVForUnity.MlModule.ANN_MLP.UPDATE_WEIGHTS = 1

static

---

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

• OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/ml/ANN_MLP.cs
• OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/ml/ANN_MLP_Struct.cs
• OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/ml/ANN_MLP_ValueTuple.cs