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GestureRecognitionToolkit
Version: 1.0 Revision: 04-03-15
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
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Public Types | |
typedef std::map< string, PreProcessing *(*)() > | StringPreProcessingMap |
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enum | BaseTypes { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER } |
Public Member Functions | |
PreProcessing (void) | |
virtual | ~PreProcessing (void) |
virtual bool | deepCopyFrom (const PreProcessing *rhs) |
bool | copyBaseVariables (const PreProcessing *preProcessingModule) |
virtual bool | process (const VectorDouble &inputVector) |
virtual bool | reset () |
virtual bool | clear () |
virtual bool | saveModelToFile (string filename) const |
virtual bool | loadModelFromFile (string filename) |
virtual bool | saveModelToFile (fstream &file) const |
virtual bool | loadModelFromFile (fstream &file) |
string | getPreProcessingType () const |
UINT | getNumInputDimensions () const |
UINT | getNumOutputDimensions () const |
bool | getInitialized () const |
VectorDouble | getProcessedData () const |
PreProcessing * | createNewInstance () const |
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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 (TimeSeriesClassificationDataStream trainingData) |
virtual bool | train_ (TimeSeriesClassificationDataStream &trainingData) |
virtual bool | train (UnlabelledData trainingData) |
virtual bool | train_ (UnlabelledData &trainingData) |
virtual bool | train (MatrixDouble data) |
virtual bool | train_ (MatrixDouble &data) |
virtual bool | predict (VectorDouble inputVector) |
virtual bool | predict_ (VectorDouble &inputVector) |
virtual bool | predict (MatrixDouble inputMatrix) |
virtual bool | predict_ (MatrixDouble &inputMatrix) |
virtual bool | map (VectorDouble inputVector) |
virtual bool | map_ (VectorDouble &inputVector) |
virtual bool | print () const |
virtual bool | save (const string filename) const |
virtual bool | load (const string filename) |
virtual bool | getModel (ostream &stream) const |
double | scale (const double &x, const double &minSource, const double &maxSource, const double &minTarget, const double &maxTarget, const bool constrain=false) |
virtual string | getModelAsString () 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 |
double | getMinChange () const |
double | getLearningRate () const |
double | getRootMeanSquaredTrainingError () const |
double | getTotalSquaredTrainingError () 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 (bool useScaling) |
bool | setMaxNumEpochs (const UINT maxNumEpochs) |
bool | setMinNumEpochs (const UINT minNumEpochs) |
bool | setMinChange (const double minChange) |
bool | setLearningRate (double learningRate) |
bool | setUseValidationSet (const bool useValidationSet) |
bool | setValidationSetSize (const UINT validationSetSize) |
bool | setRandomiseTrainingOrder (const bool randomiseTrainingOrder) |
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) |
MLBase * | getMLBasePointer () |
const MLBase * | getMLBasePointer () const |
vector< TrainingResult > | getTrainingResults () const |
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GRTBase (void) | |
virtual | ~GRTBase (void) |
bool | copyGRTBaseVariables (const GRTBase *GRTBase) |
string | getClassType () const |
string | getLastWarningMessage () const |
string | getLastErrorMessage () const |
string | getLastInfoMessage () const |
GRTBase * | getGRTBasePointer () |
const GRTBase * | getGRTBasePointer () const |
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virtual void | notify (const TrainingResult &data) |
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virtual void | notify (const TestInstanceResult &data) |
Static Public Member Functions | |
static PreProcessing * | createInstanceFromString (string const &preProcessingType) |
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static string | getGRTVersion (bool returnRevision=true) |
static string | getGRTRevison () |
Protected Member Functions | |
bool | init () |
bool | savePreProcessingSettingsToFile (fstream &file) const |
bool | loadPreProcessingSettingsFromFile (fstream &file) |
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bool | saveBaseSettingsToFile (fstream &file) const |
bool | loadBaseSettingsFromFile (fstream &file) |
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double | SQR (const double &x) const |
Static Protected Member Functions | |
static StringPreProcessingMap * | getMap () |
Protected Attributes | |
string | preProcessingType |
bool | initialized |
VectorDouble | processedData |
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bool | trained |
bool | useScaling |
UINT | baseType |
UINT | numInputDimensions |
UINT | numOutputDimensions |
UINT | numTrainingIterationsToConverge |
UINT | minNumEpochs |
UINT | maxNumEpochs |
UINT | validationSetSize |
double | learningRate |
double | minChange |
double | rootMeanSquaredTrainingError |
double | totalSquaredTrainingError |
bool | useValidationSet |
bool | randomiseTrainingOrder |
Random | random |
vector< TrainingResult > | trainingResults |
TrainingResultsObserverManager | trainingResultsObserverManager |
TestResultsObserverManager | testResultsObserverManager |
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string | classType |
DebugLog | debugLog |
ErrorLog | errorLog |
InfoLog | infoLog |
TrainingLog | trainingLog |
TestingLog | testingLog |
WarningLog | warningLog |
Definition at line 38 of file PreProcessing.h.
typedef std::map< string, PreProcessing*(*)() > GRT::PreProcessing::StringPreProcessingMap |
This typedef defines a map between a string and a PreProcessing pointer.
Definition at line 160 of file PreProcessing.h.
GRT::PreProcessing::PreProcessing | ( | void | ) |
Default Constructor
Definition at line 37 of file PreProcessing.cpp.
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virtual |
Default Destructor
Definition at line 45 of file PreProcessing.cpp.
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This is the main clear interface for all the GRT preprocessing modules. This should be overwritten by the derived class. It will completely clear the module, removing any IO values setting and all the base variables to their default values.
Reimplemented from GRT::MLBase.
Reimplemented in GRT::FIRFilter.
Definition at line 84 of file PreProcessing.cpp.
bool GRT::PreProcessing::copyBaseVariables | ( | const PreProcessing * | preProcessingModule | ) |
This copies the PreProcessing variables from preProcessing to the instance that calls the function.
const | PreProcessing *preProcessing: a pointer to a pre processing module from which the values will be copied |
Definition at line 52 of file PreProcessing.cpp.
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static |
This static function will dynamically create a new PreProcessing instance from a string.
string | const &preProcessingType: the name of the PreProcessing class you want to dynamically create |
Definition at line 28 of file PreProcessing.cpp.
PreProcessing * GRT::PreProcessing::createNewInstance | ( | ) | const |
This static function will dynamically create a new PreProcessing instance based on the type of this instance
Definition at line 187 of file PreProcessing.cpp.
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inlinevirtual |
This is the base deepCopyFrom function for the PreProcessing modules. This function should be overwritten by the derived class.
const | PreProcessing *preProcessing: a pointer to the PreProcessing base class, this should be pointing to another instance of a matching derived class |
Reimplemented in GRT::LowPassFilter, GRT::HighPassFilter, GRT::Derivative, GRT::FIRFilter, GRT::SavitzkyGolayFilter, GRT::DeadZone, GRT::DoubleMovingAverageFilter, GRT::MedianFilter, GRT::MovingAverageFilter, and GRT::LeakyIntegrator.
Definition at line 57 of file PreProcessing.h.
bool GRT::PreProcessing::getInitialized | ( | ) | const |
Returns true if the pre processing module has been initialized correctly.
Definition at line 203 of file PreProcessing.cpp.
UINT GRT::PreProcessing::getNumInputDimensions | ( | ) | const |
Returns the size of the input vector expected by the pre processing module.
Definition at line 195 of file PreProcessing.cpp.
UINT GRT::PreProcessing::getNumOutputDimensions | ( | ) | const |
Returns the size of the vector that will be computed by the pre processing module.
Definition at line 199 of file PreProcessing.cpp.
string GRT::PreProcessing::getPreProcessingType | ( | ) | const |
Definition at line 191 of file PreProcessing.cpp.
VectorDouble GRT::PreProcessing::getProcessedData | ( | ) | const |
Definition at line 207 of file PreProcessing.cpp.
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protected |
Initializes the base preprocessing module, this will resize the processedData vector and get the instance ready for preprocessing new data. The inheriting class must first initialize the module before calling this function.
Definition at line 92 of file PreProcessing.cpp.
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This saves the preprocessing settings to a file. This function should be overwritten by the derived class.
fstream | &file: a reference to the file to save the settings to |
Reimplemented from GRT::MLBase.
Reimplemented in GRT::FIRFilter, GRT::LowPassFilter, GRT::HighPassFilter, GRT::Derivative, GRT::SavitzkyGolayFilter, GRT::DeadZone, GRT::DoubleMovingAverageFilter, GRT::MedianFilter, and GRT::MovingAverageFilter.
Definition at line 123 of file PreProcessing.cpp.
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inlinevirtual |
This loads the preprocessing settings from a file. This function should be overwritten by the derived class.
fstream | &file: a reference to the file to load the settings from |
Reimplemented from GRT::MLBase.
Reimplemented in GRT::FIRFilter, GRT::LowPassFilter, GRT::HighPassFilter, GRT::Derivative, GRT::SavitzkyGolayFilter, GRT::DeadZone, GRT::DoubleMovingAverageFilter, GRT::MedianFilter, GRT::MovingAverageFilter, and GRT::LeakyIntegrator.
Definition at line 124 of file PreProcessing.h.
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protected |
Loads the core preprocessing settings from a file.
Definition at line 155 of file PreProcessing.cpp.
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inlinevirtual |
This is the main processing interface for all the pre processing modules and should be overwritten by the inheriting class.
const | VectorDouble &inputVector: a vector containing the data that should be processed |
Reimplemented in GRT::LowPassFilter, GRT::HighPassFilter, GRT::Derivative, GRT::FIRFilter, GRT::SavitzkyGolayFilter, GRT::DeadZone, GRT::DoubleMovingAverageFilter, GRT::MedianFilter, GRT::MovingAverageFilter, and GRT::LeakyIntegrator.
Definition at line 73 of file PreProcessing.h.
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virtual |
This is the main reset interface for all the GRT preprocessing modules. This should be overwritten by the derived class.
Reimplemented from GRT::MLBase.
Reimplemented in GRT::LowPassFilter, GRT::HighPassFilter, GRT::Derivative, GRT::FIRFilter, GRT::SavitzkyGolayFilter, GRT::DeadZone, GRT::DoubleMovingAverageFilter, GRT::MedianFilter, GRT::MovingAverageFilter, and GRT::LeakyIntegrator.
Definition at line 75 of file PreProcessing.cpp.
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virtual |
This saves the preprocessing settings to a file. This function should be overwritten by the derived class.
const | string filename: the filename to save the settings to |
Reimplemented from GRT::MLBase.
Reimplemented in GRT::FIRFilter, GRT::LowPassFilter, GRT::HighPassFilter, GRT::Derivative, GRT::SavitzkyGolayFilter, GRT::DeadZone, GRT::DoubleMovingAverageFilter, GRT::MedianFilter, and GRT::MovingAverageFilter.
Definition at line 109 of file PreProcessing.cpp.
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inlinevirtual |
This saves the preprocessing settings to a file. This function should be overwritten by the derived class.
fstream | &file: a reference to the file to save the settings to |
Reimplemented from GRT::MLBase.
Reimplemented in GRT::FIRFilter, GRT::LowPassFilter, GRT::HighPassFilter, GRT::Derivative, GRT::SavitzkyGolayFilter, GRT::DeadZone, GRT::DoubleMovingAverageFilter, GRT::MedianFilter, GRT::MovingAverageFilter, and GRT::LeakyIntegrator.
Definition at line 115 of file PreProcessing.h.
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protected |
Saves the core preprocessing settings to a file.
Definition at line 138 of file PreProcessing.cpp.