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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 | |
enum | SearchStates { SEARCHING_FOR_MOVEMENT =0, SEARCHING_FOR_NO_MOVEMENT, SEARCH_TIMEOUT } |
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enum | BaseTypes { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER } |
Public Member Functions | |
MovementDetector (const UINT numDimensions=1, const double upperThreshold=1, const double lowerThreshold=0.9, const double gamma=0.95, const UINT searchTimeout=0) | |
virtual bool | predict_ (VectorDouble &input) |
virtual bool | clear () |
virtual bool | reset () |
virtual bool | saveModelToFile (fstream &file) const |
virtual bool | loadModelFromFile (fstream &file) |
double | getUpperThreshold () const |
double | getLowerThreshold () const |
double | getMovementIndex () const |
double | getGamma () const |
bool | getMovementDetected () const |
bool | getNoMovementDetect () const |
UINT | getState () const |
UINT | getSearchTimeout () const |
bool | setUpperThreshold (const double upperThreshold) |
bool | setLowerThreshold (const double lowerThreshold) |
bool | setGamma (const double gamma) |
bool | setSearchTimeout (const UINT searchTimeout) |
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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 (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 | 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 Attributes | |
UINT | state |
UINT | searchTimeout |
double | upperThreshold |
double | lowerThreshold |
double | movementIndex |
double | gamma |
bool | firstSample |
bool | movementDetected |
bool | noMovementDetected |
Timer | searchTimer |
VectorDouble | lastSample |
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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 |
Additional Inherited Members | |
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static string | getGRTVersion (bool returnRevision=true) |
static string | getGRTRevison () |
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bool | saveBaseSettingsToFile (fstream &file) const |
bool | loadBaseSettingsFromFile (fstream &file) |
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double | SQR (const double &x) const |
Definition at line 38 of file MovementDetector.h.
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virtual |
This overrides the clear function in the ML 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::MLBase.
Definition at line 84 of file MovementDetector.cpp.
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virtual |
This loads a trained MovementDetector model from a file. This overrides the loadModelFromFile function in the ML base class.
fstream | &file: a reference to the file the MovementDetector model will be loaded from |
Reimplemented from GRT::MLBase.
Definition at line 126 of file MovementDetector.cpp.
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virtual |
This is the main prediction interface for all the GRT machine learning algorithms. This should be overwritten by the derived class.
VectorDouble | &inputVector: a reference to the input vector for prediction |
Reimplemented from GRT::MLBase.
Definition at line 29 of file MovementDetector.cpp.
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virtual |
This overrides the reset function in the ML base class. It will reset the MovementDetector, setting the state back to the search timeout and resetting the movementIndex to zero.
Reimplemented from GRT::MLBase.
Definition at line 94 of file MovementDetector.cpp.
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virtual |
This saves the trained MovementDetector model to a file. This overrides the saveModelToFile function in the ML base class.
fstream | &file: a reference to the file the MovementDetector model will be saved to |
Reimplemented from GRT::MLBase.
Definition at line 106 of file MovementDetector.cpp.