![]() |
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.
|
Public Member Functions | |
MovementIndex (UINT bufferLength=100, UINT numDimensions=1) | |
MovementIndex (const MovementIndex &rhs) | |
virtual | ~MovementIndex () |
MovementIndex & | operator= (const MovementIndex &rhs) |
virtual bool | deepCopyFrom (const FeatureExtraction *featureExtraction) |
virtual bool | computeFeatures (const VectorDouble &inputVector) |
virtual bool | reset () |
virtual bool | saveModelToFile (string filename) const |
virtual bool | loadModelFromFile (string filename) |
virtual bool | saveModelToFile (fstream &file) const |
virtual bool | loadModelFromFile (fstream &file) |
bool | init (UINT bufferLength, UINT numDimensions) |
VectorDouble | update (double x) |
VectorDouble | update (const VectorDouble &x) |
CircularBuffer< VectorDouble > | getData () |
![]() | |
FeatureExtraction () | |
virtual | ~FeatureExtraction () |
bool | copyBaseVariables (const FeatureExtraction *featureExtractionModule) |
virtual bool | clear () |
string | getFeatureExtractionType () const |
UINT | getNumInputDimensions () const |
UINT | getNumOutputDimensions () const |
bool | getInitialized () const |
bool | getFeatureDataReady () const |
VectorDouble | getFeatureVector () const |
FeatureExtraction * | createNewInstance () const |
![]() | |
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 |
![]() | |
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 |
![]() | |
virtual void | notify (const TrainingResult &data) |
![]() | |
virtual void | notify (const TestInstanceResult &data) |
Protected Attributes | |
UINT | bufferLength |
CircularBuffer< vector< double > > | dataBuffer |
![]() | |
string | featureExtractionType |
bool | initialized |
bool | featureDataReady |
VectorDouble | featureVector |
![]() | |
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 |
![]() | |
string | classType |
DebugLog | debugLog |
ErrorLog | errorLog |
InfoLog | infoLog |
TrainingLog | trainingLog |
TestingLog | testingLog |
WarningLog | warningLog |
Static Protected Attributes | |
static RegisterFeatureExtractionModule< MovementIndex > | registerModule |
Additional Inherited Members | |
![]() | |
typedef std::map< string, FeatureExtraction *(*)() > | StringFeatureExtractionMap |
![]() | |
enum | BaseTypes { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER } |
![]() | |
static FeatureExtraction * | createInstanceFromString (string const &featureExtractionType) |
![]() | |
static string | getGRTVersion (bool returnRevision=true) |
static string | getGRTRevison () |
![]() | |
bool | init () |
bool | saveFeatureExtractionSettingsToFile (fstream &file) const |
bool | loadFeatureExtractionSettingsFromFile (fstream &file) |
![]() | |
bool | saveBaseSettingsToFile (fstream &file) const |
bool | loadBaseSettingsFromFile (fstream &file) |
![]() | |
double | SQR (const double &x) const |
![]() | |
static StringFeatureExtractionMap * | getMap () |
Definition at line 41 of file MovementIndex.h.
GRT::MovementIndex::MovementIndex | ( | UINT | bufferLength = 100 , |
UINT | numDimensions = 1 |
||
) |
Default Constructor. Sets the buffer length and the number of input dimensions.
UINT | bufferLength: the size of the buffer that will hold the last N samples used to compute the movement index |
UINT | numDimensions: sets the number of dimensions |
Definition at line 28 of file MovementIndex.cpp.
GRT::MovementIndex::MovementIndex | ( | const MovementIndex & | rhs | ) |
Copy constructor, copies the MovementIndex from the rhs instance to this instance.
const | MovementIndex &rhs: another instance of the MovementIndex class from which the data will be copied to this instance |
Definition at line 38 of file MovementIndex.cpp.
|
virtual |
Default Destructor
Definition at line 50 of file MovementIndex.cpp.
|
virtual |
Sets the FeatureExtraction computeFeatures function, overwriting the base FeatureExtraction 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 MovementIndex's update function.
const | VectorDouble &inputVector: the inputVector that should be processed. Must have the same dimensionality as the FeatureExtraction module |
Reimplemented from GRT::FeatureExtraction.
Definition at line 82 of file MovementIndex.cpp.
|
virtual |
Sets the FeatureExtraction deepCopyFrom function, overwriting the base FeatureExtraction function. This function is used to deep copy the values from the input pointer to this instance of the FeatureExtraction module. This function is called by the GestureRecognitionPipeline when the user adds a new FeatureExtraction module to the pipeleine.
const | FeatureExtraction *featureExtraction: a pointer to another instance of a MovementIndex, the values of that instance will be cloned to this instance |
Reimplemented from GRT::FeatureExtraction.
Definition at line 65 of file MovementIndex.cpp.
CircularBuffer< vector< double > > GRT::MovementIndex::getData | ( | ) |
Gets the current values in the data buffer. An empty circular buffer will be returned if the feature extraction module has not been initialized.
Definition at line 275 of file MovementIndex.cpp.
bool GRT::MovementIndex::init | ( | UINT | bufferLength, |
UINT | numDimensions | ||
) |
Initializes the MovementIndex. This sets the bufferLength and the number of input dimensions.
UINT | bufferLength: the size of the buffer that will hold the last N samples used to compute the movement index |
UINT | numDimensions: sets the number of dimensions |
Definition at line 191 of file MovementIndex.cpp.
|
virtual |
This saves the feature extraction settings to a file.
fstream | &file: a reference to the file to save the settings to |
Reimplemented from GRT::MLBase.
Definition at line 120 of file MovementIndex.cpp.
|
virtual |
This loads the feature extraction settings from a file. This overrides the loadSettingsFromFile function in the FeatureExtraction base class.
fstream | &file: a reference to the file to load the settings from |
Reimplemented from GRT::FeatureExtraction.
Definition at line 157 of file MovementIndex.cpp.
MovementIndex & GRT::MovementIndex::operator= | ( | const MovementIndex & | rhs | ) |
Sets the equals operator, copies the data from the rhs instance to this instance.
const | MovementIndex &rhs: another instance of the MovementIndex class from which the data will be copied to this instance |
Definition at line 54 of file MovementIndex.cpp.
|
virtual |
Sets the FeatureExtraction reset function, overwriting the base FeatureExtraction function. This function is called by the GestureRecognitionPipeline when the pipelines main reset() function is called. This function resets the feature extraction by re-initiliazing the instance.
Reimplemented from GRT::FeatureExtraction.
Definition at line 99 of file MovementIndex.cpp.
|
virtual |
This saves the feature extraction settings to a file.
const | string filename: the filename to save the settings to |
Reimplemented from GRT::MLBase.
Definition at line 106 of file MovementIndex.cpp.
|
virtual |
This saves the feature extraction settings to a file. This overrides the saveSettingsToFile function in the FeatureExtraction base class.
fstream | &file: a reference to the file to save the settings to |
Reimplemented from GRT::FeatureExtraction.
Definition at line 135 of file MovementIndex.cpp.
vector< double > GRT::MovementIndex::update | ( | double | x | ) |
Computes the features from the input, this should only be called if the dimensionality of this instance was set to 1.
double | x: the value to compute features from, this should only be called if the dimensionality of the filter was set to 1 |
Definition at line 223 of file MovementIndex.cpp.
VectorDouble GRT::MovementIndex::update | ( | const VectorDouble & | x | ) |
Computes the features from the input, the dimensionality of x should match that of this instance.
const | VectorDouble &x: a vector containing the values to be processed, must be the same size as the numInputDimensions |