GestureRecognitionToolkit  Version: 0.1.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
ClassLabelFilter Class Reference

#include <ClassLabelFilter.h>

Inheritance diagram for ClassLabelFilter:
PostProcessing MLBase GRTBase Observer< TrainingResult > Observer< TestInstanceResult >

Public Member Functions

 ClassLabelFilter (UINT minimumCount=1, UINT bufferSize=1)
 
 ClassLabelFilter (const ClassLabelFilter &rhs)
 
virtual ~ClassLabelFilter ()
 
ClassLabelFilteroperator= (const ClassLabelFilter &rhs)
 
virtual bool deepCopyFrom (const PostProcessing *postProcessing)
 
virtual bool process (const VectorDouble &inputVector)
 
virtual bool reset ()
 
virtual bool saveModelToFile (std::string filename) const
 
virtual bool saveModelToFile (std::fstream &file) const
 
virtual bool loadModelFromFile (std::string filename)
 
virtual bool loadModelFromFile (std::fstream &file)
 
bool init (UINT minimumCount, UINT bufferSize)
 
UINT filter (UINT predictedClassLabel)
 
UINT getFilteredClassLabel ()
 
bool setMinimumCount (UINT minimumCount)
 
bool setBufferSize (UINT bufferSize)
 
- Public Member Functions inherited from PostProcessing
 PostProcessing (void)
 
virtual ~PostProcessing (void)
 
bool copyBaseVariables (const PostProcessing *postProcessingModule)
 
std::string getPostProcessingType () const
 
UINT getPostProcessingInputMode () const
 
UINT getPostProcessingOutputMode () const
 
UINT getNumInputDimensions () const
 
UINT getNumOutputDimensions () const
 
bool getInitialized () const
 
bool getIsPostProcessingInputModePredictedClassLabel () const
 
bool getIsPostProcessingInputModeClassLikelihoods () const
 
bool getIsPostProcessingOutputModePredictedClassLabel () const
 
bool getIsPostProcessingOutputModeClassLikelihoods () const
 
VectorFloat getProcessedData () const
 
PostProcessingcreateNewInstance () const
 
- Public Member Functions inherited from MLBase
 MLBase (void)
 
virtual ~MLBase (void)
 
bool copyMLBaseVariables (const MLBase *mlBase)
 
virtual bool train (ClassificationData trainingData)
 
virtual bool train_ (ClassificationData &trainingData)
 
virtual bool train (RegressionData trainingData)
 
virtual bool train_ (RegressionData &trainingData)
 
virtual bool train (TimeSeriesClassificationData trainingData)
 
virtual bool train_ (TimeSeriesClassificationData &trainingData)
 
virtual bool train (ClassificationDataStream trainingData)
 
virtual bool train_ (ClassificationDataStream &trainingData)
 
virtual bool train (UnlabelledData trainingData)
 
virtual bool train_ (UnlabelledData &trainingData)
 
virtual bool train (MatrixFloat data)
 
virtual bool train_ (MatrixFloat &data)
 
virtual bool predict (VectorFloat inputVector)
 
virtual bool predict_ (VectorFloat &inputVector)
 
virtual bool predict (MatrixFloat inputMatrix)
 
virtual bool predict_ (MatrixFloat &inputMatrix)
 
virtual bool map (VectorFloat inputVector)
 
virtual bool map_ (VectorFloat &inputVector)
 
virtual bool clear ()
 
virtual bool print () const
 
virtual bool save (const std::string filename) const
 
virtual bool load (const std::string filename)
 
virtual bool getModel (std::ostream &stream) const
 
Float scale (const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)
 
virtual std::string getModelAsString () const
 
DataType getInputType () const
 
DataType getOutputType () const
 
UINT getBaseType () const
 
UINT getNumInputFeatures () const
 
UINT getNumInputDimensions () const
 
UINT getNumOutputDimensions () const
 
UINT getMinNumEpochs () const
 
UINT getMaxNumEpochs () const
 
UINT getValidationSetSize () const
 
UINT getNumTrainingIterationsToConverge () const
 
Float getMinChange () const
 
Float getLearningRate () const
 
Float getRootMeanSquaredTrainingError () const
 
Float getTotalSquaredTrainingError () const
 
Float getValidationSetAccuracy () const
 
VectorFloat getValidationSetPrecision () const
 
VectorFloat getValidationSetRecall () const
 
bool getUseValidationSet () const
 
bool getRandomiseTrainingOrder () const
 
bool getTrained () const
 
bool getModelTrained () const
 
bool getScalingEnabled () const
 
bool getIsBaseTypeClassifier () const
 
bool getIsBaseTypeRegressifier () const
 
bool getIsBaseTypeClusterer () const
 
bool enableScaling (const bool useScaling)
 
bool setMaxNumEpochs (const UINT maxNumEpochs)
 
bool setMinNumEpochs (const UINT minNumEpochs)
 
bool setMinChange (const Float minChange)
 
bool setLearningRate (const Float learningRate)
 
bool setUseValidationSet (const bool useValidationSet)
 
bool setValidationSetSize (const UINT validationSetSize)
 
bool setRandomiseTrainingOrder (const bool randomiseTrainingOrder)
 
bool setTrainingLoggingEnabled (const bool loggingEnabled)
 
bool registerTrainingResultsObserver (Observer< TrainingResult > &observer)
 
bool registerTestResultsObserver (Observer< TestInstanceResult > &observer)
 
bool removeTrainingResultsObserver (const Observer< TrainingResult > &observer)
 
bool removeTestResultsObserver (const Observer< TestInstanceResult > &observer)
 
bool removeAllTrainingObservers ()
 
bool removeAllTestObservers ()
 
bool notifyTrainingResultsObservers (const TrainingResult &data)
 
bool notifyTestResultsObservers (const TestInstanceResult &data)
 
MLBasegetMLBasePointer ()
 
const MLBasegetMLBasePointer () const
 
Vector< TrainingResult > getTrainingResults () const
 
- Public Member Functions inherited from GRTBase
 GRTBase (void)
 
virtual ~GRTBase (void)
 
bool copyGRTBaseVariables (const GRTBase *GRTBase)
 
std::string getClassType () const
 
std::string getLastWarningMessage () const
 
std::string getLastErrorMessage () const
 
std::string getLastInfoMessage () const
 
bool setInfoLoggingEnabled (const bool loggingEnabled)
 
bool setWarningLoggingEnabled (const bool loggingEnabled)
 
bool setErrorLoggingEnabled (const bool loggingEnabled)
 
GRTBasegetGRTBasePointer ()
 
const GRTBasegetGRTBasePointer () const
 
- Public Member Functions inherited from Observer< TrainingResult >
virtual void notify (const TrainingResult &data)
 
- Public Member Functions inherited from Observer< TestInstanceResult >
virtual void notify (const TestInstanceResult &data)
 

Protected Attributes

UINT filteredClassLabel
 The most recent filtered class label value.
 
UINT minimumCount
 The minimum count sets the minimum number of class label values that must be present in the class labels buffer for that class label value to be output by the Class Label Filter.
 
UINT bufferSize
 The size of the Class Label Filter buffer.
 
CircularBuffer< UINT > buffer
 The class label filter buffer.
 
- Protected Attributes inherited from PostProcessing
std::string postProcessingType
 
bool initialized
 
UINT postProcessingInputMode
 
UINT postProcessingOutputMode
 
VectorFloat processedData
 
- Protected Attributes inherited from MLBase
bool trained
 
bool useScaling
 
DataType inputType
 
DataType outputType
 
UINT baseType
 
UINT numInputDimensions
 
UINT numOutputDimensions
 
UINT numTrainingIterationsToConverge
 
UINT minNumEpochs
 
UINT maxNumEpochs
 
UINT validationSetSize
 
Float learningRate
 
Float minChange
 
Float rootMeanSquaredTrainingError
 
Float totalSquaredTrainingError
 
Float validationSetAccuracy
 
bool useValidationSet
 
bool randomiseTrainingOrder
 
VectorFloat validationSetPrecision
 
VectorFloat validationSetRecall
 
Random random
 
std::vector< TrainingResult > trainingResults
 
TrainingResultsObserverManager trainingResultsObserverManager
 
TestResultsObserverManager testResultsObserverManager
 
- Protected Attributes inherited from GRTBase
std::string classType
 
DebugLog debugLog
 
ErrorLog errorLog
 
InfoLog infoLog
 
TrainingLog trainingLog
 
TestingLog testingLog
 
WarningLog warningLog
 

Static Protected Attributes

static RegisterPostProcessingModule< ClassLabelFilterregisterModule
 

Additional Inherited Members

- Public Types inherited from PostProcessing
enum  PostprocessingInputModes { INPUT_MODE_NOT_SET =0, INPUT_MODE_PREDICTED_CLASS_LABEL, INPUT_MODE_CLASS_LIKELIHOODS }
 
enum  PostprocessingOutputModes { OUTPUT_MODE_NOT_SET =0, OUTPUT_MODE_PREDICTED_CLASS_LABEL, OUTPUT_MODE_CLASS_LIKELIHOODS }
 
typedef std::map< std::string, PostProcessing *(*)() > StringPostProcessingMap
 
- Public Types inherited from MLBase
enum  BaseTypes { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER }
 
- Static Public Member Functions inherited from PostProcessing
static PostProcessingcreateInstanceFromString (std::string const &postProcessingType)
 
- Static Public Member Functions inherited from GRTBase
static std::string getGRTVersion (bool returnRevision=true)
 
static std::string getGRTRevison ()
 
- Protected Member Functions inherited from PostProcessing
bool init ()
 
bool savePostProcessingSettingsToFile (std::fstream &file) const
 
bool loadPostProcessingSettingsFromFile (std::fstream &file)
 
- Protected Member Functions inherited from MLBase
bool saveBaseSettingsToFile (std::fstream &file) const
 
bool loadBaseSettingsFromFile (std::fstream &file)
 
- Protected Member Functions inherited from GRTBase
Float SQR (const Float &x) const
 
- Static Protected Member Functions inherited from PostProcessing
static StringPostProcessingMapgetMap ()
 

Detailed Description

GRT MIT License Copyright (c) <2012> <Nicholas Gillian, Media Lab, MIT>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Definition at line 41 of file ClassLabelFilter.h.

Constructor & Destructor Documentation

ClassLabelFilter::ClassLabelFilter ( UINT  minimumCount = 1,
UINT  bufferSize = 1 
)

Default Constructor. Sets the minimumCount and bufferSize parameters. The minimum count sets the minimum number of class label values that must be present in the class labels buffer for that class label value to be output by the Class Label Filter. The size of the class labels buffer is set by the buffer size parameter. If there is more than one type of class label in the buffer then the class label with the maximum number of instances will be output. If the maximum number of instances for any class label in the buffer is less than the minimum count parameter then the Class Label Filter will output the default null rejection class label of 0.

Parameters
minimumCountsets the minimumCount value. Default value minimumCount=1
bufferSizesets the size of the class labels buffer. Default value bufferSize=1

Definition at line 28 of file ClassLabelFilter.cpp.

ClassLabelFilter::ClassLabelFilter ( const ClassLabelFilter rhs)

Copy Constructor.

Copies the values from the rhs ClassLabelFilter to this instance of the ClassLabelFilter.

Parameters
rhsthe rhs from which the values will be copied to this this instance of the ClassLabelFilter.

Definition at line 39 of file ClassLabelFilter.cpp.

ClassLabelFilter::~ClassLabelFilter ( )
virtual

Default Destructor

Definition at line 59 of file ClassLabelFilter.cpp.

Member Function Documentation

bool ClassLabelFilter::deepCopyFrom ( const PostProcessing postProcessing)
virtual

Sets the PostProcessing deepCopyFrom function, overwriting the base PostProcessing function. This function is used to deep copy the values from the input pointer to this instance of the PostProcessing module. This function is called by the GestureRecognitionPipeline when the user adds a new PostProcessing module to the pipeline.

Parameters
postProcessinga pointer to another instance of a ClassLabelFilter, the values of that instance will be cloned to this instance
Returns
true if the deep copy was successful, false otherwise

Reimplemented from PostProcessing.

Definition at line 79 of file ClassLabelFilter.cpp.

UINT ClassLabelFilter::filter ( UINT  predictedClassLabel)

This is the main filter function which filters the input predictedClassLabel.

Parameters
predictedClassLabelthe predictedClassLabel which should be filtered return returns the filtered class label

Definition at line 155 of file ClassLabelFilter.cpp.

UINT ClassLabelFilter::getFilteredClassLabel ( )
inline

Get the most recently filtered class label value.

Returns
returns the filtered class label

Definition at line 165 of file ClassLabelFilter.h.

bool ClassLabelFilter::init ( UINT  minimumCount,
UINT  bufferSize 
)

This function initializes the ClassLabelFilter.

Parameters
minimumCountsets the minimumCount value
bufferSizesets the size of the class labels buffer
Returns
returns true if the ClassLabelFilter was initialized, false otherwise

Definition at line 128 of file ClassLabelFilter.cpp.

bool ClassLabelFilter::loadModelFromFile ( std::string  filename)
virtual

This loads the post processing settings from a file. This overrides the loadSettingsFromFile function in the PostProcessing base class.

Parameters
filenamethe name of the file to load the settings from
Returns
returns true if the settings were loaded successfully, false otherwise

Reimplemented from PostProcessing.

Definition at line 244 of file ClassLabelFilter.cpp.

bool ClassLabelFilter::loadModelFromFile ( std::fstream &  file)
virtual

This loads the post processing settings from a file. This overrides the loadSettingsFromFile function in the PostProcessing base class.

Parameters
filenamethe name of the file to load the settings from
Returns
returns true if the settings were loaded successfully, false otherwise

Reimplemented from PostProcessing.

Definition at line 260 of file ClassLabelFilter.cpp.

ClassLabelFilter & ClassLabelFilter::operator= ( const ClassLabelFilter rhs)

Assigns the equals operator setting how the values from the rhs instance will be copied to this instance.

Parameters
rhsthe rhs instance from which the values will be copied to this this instance of the ClassLabelFilter
Returns
returns a reference to this instance of the ClassLabelFilter

Definition at line 63 of file ClassLabelFilter.cpp.

bool ClassLabelFilter::process ( const VectorDouble inputVector)
virtual

Sets the PostProcessing process function, overwriting the base PostProcessing function. This function is called by the GestureRecognitionPipeline when any new input data needs to be processed (during the prediction phase for example). This function calls the ClassLabelFilter's filter(...) function.

Parameters
inputVectorthe inputVector that should be processed. This should be a 1-dimensional vector containing a predicted class label
Returns
true if the data was processed, false otherwise

Reimplemented from PostProcessing.

Definition at line 100 of file ClassLabelFilter.cpp.

bool ClassLabelFilter::reset ( )
virtual

Sets the PostProcessing reset function, overwriting the base PostProcessing function. This function is called by the GestureRecognitionPipeline when the pipelines main reset() function is called. This function resets the ClassLabelFilter by re-initiliazing the instance.

Returns
true if the ClassLabelFilter was reset, false otherwise

Reimplemented from PostProcessing.

Definition at line 117 of file ClassLabelFilter.cpp.

bool ClassLabelFilter::saveModelToFile ( std::string  filename) const
virtual

This saves the post processing settings to a file. This overrides the saveSettingsToFile function in the PostProcessing base class.

Parameters
filenamethe name of the file to save the settings to
Returns
returns true if the settings were saved successfully, false otherwise

Reimplemented from PostProcessing.

Definition at line 208 of file ClassLabelFilter.cpp.

bool ClassLabelFilter::saveModelToFile ( std::fstream &  file) const
virtual

This saves the post processing settings to a file. This overrides the saveSettingsToFile function in the PostProcessing base class.

Parameters
filenamethe name of the file to save the settings to
Returns
returns true if the settings were saved successfully, false otherwise

Reimplemented from PostProcessing.

Definition at line 228 of file ClassLabelFilter.cpp.

bool ClassLabelFilter::setBufferSize ( UINT  bufferSize)

Sets the bufferSize parameter.

The bufferSize parameter controls the size of the class labels buffer. If the Class Label Filter has been initialized then the module will be reset.

Parameters
bufferSizethe new bufferSize parameter
Returns
returns true if the bufferSize parameter was updated, false otherwise

Definition at line 319 of file ClassLabelFilter.cpp.

bool ClassLabelFilter::setMinimumCount ( UINT  minimumCount)

Sets the minimumCount parameter.

The minimumCount parameter controls how many class labels need to be present in the class labels buffer for that class label to be output by the filter. If the Class Label Filter has been initialized then the module will be reset.

Parameters
minimumCountthe new minimumCount parameter
Returns
returns true if the minimumCount parameter was updated, false otherwise

Definition at line 311 of file ClassLabelFilter.cpp.


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