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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 Member Functions | |
FiniteStateMachine (const UINT numParticles=200, const UINT numClustersPerState=20, const double stateTransitionSmoothingCoeff=0.0, const double measurementNoise=10.0) | |
FiniteStateMachine (const FiniteStateMachine &rhs) | |
virtual | ~FiniteStateMachine (void) |
FiniteStateMachine & | operator= (const FiniteStateMachine &rhs) |
virtual bool | deepCopyFrom (const Classifier *classifier) |
virtual bool | train_ (ClassificationData &trainingData) |
virtual bool | train_ (TimeSeriesClassificationData &trainingData) |
virtual bool | train_ (TimeSeriesClassificationDataStream &data) |
virtual bool | predict_ (VectorDouble &inputVector) |
virtual bool | reset () |
virtual bool | clear () |
virtual bool | print () const |
virtual bool | saveModelToFile (fstream &file) const |
virtual bool | loadModelFromFile (fstream &file) |
bool | setNumParticles (const UINT numParticles) |
bool | setNumClustersPerState (const UINT numClustersPerState) |
bool | setStateTransitionSmoothingCoeff (const double stateTransitionSmoothingCoeff) |
bool | setMeasurementNoise (const double measurementNoise) |
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Classifier (void) | |
virtual | ~Classifier (void) |
bool | copyBaseVariables (const Classifier *classifier) |
string | getClassifierType () const |
bool | getSupportsNullRejection () const |
bool | getNullRejectionEnabled () const |
double | getNullRejectionCoeff () const |
double | getMaximumLikelihood () const |
double | getBestDistance () const |
double | getPhase () const |
virtual UINT | getNumClasses () const |
UINT | getClassLabelIndexValue (UINT classLabel) const |
UINT | getPredictedClassLabel () const |
VectorDouble | getClassLikelihoods () const |
VectorDouble | getClassDistances () const |
VectorDouble | getNullRejectionThresholds () const |
vector< UINT > | getClassLabels () const |
vector< MinMax > | getRanges () const |
bool | enableNullRejection (bool useNullRejection) |
virtual bool | setNullRejectionCoeff (double nullRejectionCoeff) |
virtual bool | setNullRejectionThresholds (VectorDouble newRejectionThresholds) |
virtual bool | recomputeNullRejectionThresholds () |
bool | getTimeseriesCompatible () const |
Classifier * | createNewInstance () const |
Classifier * | deepCopy () const |
const Classifier * | getClassifierPointer () const |
const Classifier & | getBaseClassifier () const |
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MLBase (void) | |
virtual | ~MLBase (void) |
bool | copyMLBaseVariables (const MLBase *mlBase) |
virtual bool | train (ClassificationData trainingData) |
virtual bool | train (RegressionData trainingData) |
virtual bool | train_ (RegressionData &trainingData) |
virtual bool | train (TimeSeriesClassificationData 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 (MatrixDouble inputMatrix) |
virtual bool | predict_ (MatrixDouble &inputMatrix) |
virtual bool | map (VectorDouble inputVector) |
virtual bool | map_ (VectorDouble &inputVector) |
virtual bool | save (const string filename) const |
virtual bool | load (const string filename) |
virtual bool | saveModelToFile (string filename) const |
virtual bool | loadModelFromFile (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) |
Protected Member Functions | |
bool | recomputePT () |
bool | recomputePE () |
bool | initParticles () |
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bool | saveBaseSettingsToFile (fstream &file) const |
bool | loadBaseSettingsFromFile (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 |
Protected Attributes | |
UINT | numParticles |
UINT | numClustersPerState |
double | stateTransitionSmoothingCoeff |
double | measurementNoise |
FSMParticleFilter | particles |
MatrixDouble | stateTransitions |
vector< MatrixDouble > | stateEmissions |
vector< vector< IndexedDouble > > | pt |
This stores the stateTransitions matrix in a format more efficient for the particle filter. | |
vector< vector< VectorDouble > > | pe |
This stores the stateEmissions model in a format more efficient for the particle filter. | |
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string | classifierType |
bool | supportsNullRejection |
bool | useNullRejection |
UINT | numClasses |
UINT | predictedClassLabel |
UINT | classifierMode |
double | nullRejectionCoeff |
double | maxLikelihood |
double | bestDistance |
double | phase |
VectorDouble | classLikelihoods |
VectorDouble | classDistances |
VectorDouble | nullRejectionThresholds |
vector< UINT > | classLabels |
vector< MinMax > | ranges |
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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 |
Static Protected Attributes | |
static RegisterClassifierModule< FiniteStateMachine > | registerModule |
Additional Inherited Members | |
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typedef std::map< string, Classifier *(*)() > | StringClassifierMap |
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enum | BaseTypes { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER } |
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static Classifier * | createInstanceFromString (string const &classifierType) |
static vector< string > | getRegisteredClassifiers () |
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static string | getGRTVersion (bool returnRevision=true) |
static string | getGRTRevison () |
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enum | ClassifierModes { STANDARD_CLASSIFIER_MODE =0, TIMESERIES_CLASSIFIER_MODE } |
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static StringClassifierMap * | getMap () |
Definition at line 36 of file FiniteStateMachine.h.
GRT::FiniteStateMachine::FiniteStateMachine | ( | const UINT | numParticles = 200 , |
const UINT | numClustersPerState = 20 , |
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const double | stateTransitionSmoothingCoeff = 0.0 , |
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const double | measurementNoise = 10.0 |
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Default constructor.
Definition at line 28 of file FiniteStateMachine.cpp.
GRT::FiniteStateMachine::FiniteStateMachine | ( | const FiniteStateMachine & | rhs | ) |
Defines the copy constructor.
const | FiniteStateMachine &random: the instance from which all the data will be copied into this instance |
Definition at line 48 of file FiniteStateMachine.cpp.
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virtual |
Default Destructor
Definition at line 59 of file FiniteStateMachine.cpp.
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This overrides the clear function in the Classifier base class. It will completely clear the ML module, removing any trained model and setting all the base variables to their default values.
Reimplemented from GRT::Classifier.
Definition at line 345 of file FiniteStateMachine.cpp.
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This is required for the Gesture Recognition Pipeline for when the pipeline.setClassifier(...) method is called. It clones the data from the Base Class Classifier pointer (which should be pointing to an FiniteStateMachine instance) into this instance
Classifier | *classifier: a pointer to the Classifier Base Class, this should be pointing to another FiniteStateMachine instance |
Reimplemented from GRT::Classifier.
Definition at line 87 of file FiniteStateMachine.cpp.
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This loads a trained FiniteStateMachine model from a file. This overrides the loadModelFromFile function in the Classifier base class.
fstream | &file: a reference to the file the FiniteStateMachine model will be loaded from |
Reimplemented from GRT::MLBase.
Definition at line 441 of file FiniteStateMachine.cpp.
FiniteStateMachine & GRT::FiniteStateMachine::operator= | ( | const FiniteStateMachine & | rhs | ) |
Defines how the data from the rhs FPSM should be copied to this FPSM
const | FPSM &rhs: another instance of a FPSM |
Definition at line 63 of file FiniteStateMachine.cpp.
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This predicts the class of the inputVector. This overrides the predict function in the Classifier base class.
VectorDouble | inputVector: the input vector to classify |
Reimplemented from GRT::MLBase.
Definition at line 279 of file FiniteStateMachine.cpp.
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This overrides the print function in the Classifier base class. It will print the current model and settings to the infoLog.
Reimplemented from GRT::MLBase.
Definition at line 360 of file FiniteStateMachine.cpp.
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This resets the FiniteStateMachine.
If a model has been trained then this will randomize the current state and reset all the particles.
Reimplemented from GRT::Classifier.
Definition at line 332 of file FiniteStateMachine.cpp.
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This saves the trained FiniteStateMachine model to a file. This overrides the saveModelToFile function in the Classifier base class.
fstream | &file: a reference to the file the FiniteStateMachine model will be saved to |
Reimplemented from GRT::MLBase.
Definition at line 390 of file FiniteStateMachine.cpp.
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This trains the FiniteStateMachine model, using the labelled classification data. This overrides the train function in the Classifier base class. It converts the data into a TimeSeriesClassificationDataStream format and calls that train_ function.
ClassificationData | trainingData: a reference to the training data |
Reimplemented from GRT::MLBase.
Definition at line 120 of file FiniteStateMachine.cpp.
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This trains the FiniteStateMachine model, using the labelled timeseries classification data. This overrides the train function in the Classifier base class. It converts the data into a TimeSeriesClassificationDataStream format and calls that train_ function.
TimeSeriesClassificationData | trainingData: a reference to the training data |
Reimplemented from GRT::MLBase.
Definition at line 149 of file FiniteStateMachine.cpp.
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This is the main training function for the FiniteStateMachine model, using the TimeSeriesClassificationDataStream data. This overrides the train function in the Classifier base class.
TimeSeriesClassificationDataStream | trainingData: a reference to the training data |
Reimplemented from GRT::MLBase.
Definition at line 180 of file FiniteStateMachine.cpp.