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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 | |
TimeDomainFeatures (UINT bufferLength=100, UINT numFrames=10, UINT numDimensions=1, bool offsetInput=false, bool useMean=true, bool useStdDev=true, bool useEuclideanNorm=true, bool useRMS=true) | |
TimeDomainFeatures (const TimeDomainFeatures &rhs) | |
virtual | ~TimeDomainFeatures () |
TimeDomainFeatures & | operator= (const TimeDomainFeatures &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 numFrames, UINT numDimensions, bool offsetInput, bool useMean, bool useStdDev, bool useEuclideanNorm, bool useRMS) |
VectorDouble | update (double x) |
VectorDouble | update (const VectorDouble &x) |
CircularBuffer< VectorDouble > | getBufferData () |
const CircularBuffer< VectorDouble > & | getBufferData () const |
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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 |
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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) |
Protected Attributes | |
UINT | bufferLength |
UINT | numFrames |
bool | offsetInput |
bool | useMean |
bool | useStdDev |
bool | useEuclideanNorm |
bool | useRMS |
CircularBuffer< VectorDouble > | dataBuffer |
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string | featureExtractionType |
bool | initialized |
bool | featureDataReady |
VectorDouble | featureVector |
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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 RegisterFeatureExtractionModule< TimeDomainFeatures > | registerModule |
Additional Inherited Members | |
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typedef std::map< string, FeatureExtraction *(*)() > | StringFeatureExtractionMap |
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enum | BaseTypes { BASE_TYPE_NOT_SET =0, CLASSIFIER, REGRESSIFIER, CLUSTERER } |
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static FeatureExtraction * | createInstanceFromString (string const &featureExtractionType) |
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static string | getGRTVersion (bool returnRevision=true) |
static string | getGRTRevison () |
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bool | init () |
bool | saveFeatureExtractionSettingsToFile (fstream &file) const |
bool | loadFeatureExtractionSettingsFromFile (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 |
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static StringFeatureExtractionMap * | getMap () |
Definition at line 37 of file TimeDomainFeatures.h.
GRT::TimeDomainFeatures::TimeDomainFeatures | ( | const TimeDomainFeatures & | rhs | ) |
Copy constructor, copies the TimeDomainFeatures from the rhs instance to this instance.
const | TimeDomainFeatures &rhs: another instance of the TimeDomainFeatures class from which the data will be copied to this instance |
Definition at line 39 of file TimeDomainFeatures.cpp.
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Default Destructor
Definition at line 51 of file TimeDomainFeatures.cpp.
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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 TimeDomainFeatures'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 89 of file TimeDomainFeatures.cpp.
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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 pipeline.
FeatureExtraction | *featureExtraction: a pointer to another instance of a TimeDomainFeatures, the values of that instance will be cloned to this instance |
Reimplemented from GRT::FeatureExtraction.
Definition at line 72 of file TimeDomainFeatures.cpp.
CircularBuffer< VectorDouble > GRT::TimeDomainFeatures::getBufferData | ( | ) |
Get the circular buffer.
Definition at line 440 of file TimeDomainFeatures.cpp.
const CircularBuffer< VectorDouble > & GRT::TimeDomainFeatures::getBufferData | ( | ) | const |
Gets a reference to the circular buffer.
Definition at line 447 of file TimeDomainFeatures.cpp.
bool GRT::TimeDomainFeatures::init | ( | UINT | bufferLength, |
UINT | numFrames, | ||
UINT | numDimensions, | ||
bool | offsetInput, | ||
bool | useMean, | ||
bool | useStdDev, | ||
bool | useEuclideanNorm, | ||
bool | useRMS | ||
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Initializes the MovementTrajectoryFeatures
Definition at line 252 of file TimeDomainFeatures.cpp.
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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 127 of file TimeDomainFeatures.cpp.
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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 170 of file TimeDomainFeatures.cpp.
TimeDomainFeatures & GRT::TimeDomainFeatures::operator= | ( | const TimeDomainFeatures & | rhs | ) |
Sets the equals operator, copies the data from the rhs instance to this instance.
const | TimeDomainFeatures &rhs: another instance of the TimeDomainFeatures class from which the data will be copied to this instance |
Definition at line 55 of file TimeDomainFeatures.cpp.
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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 106 of file TimeDomainFeatures.cpp.
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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 113 of file TimeDomainFeatures.cpp.
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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 142 of file TimeDomainFeatures.cpp.
VectorDouble GRT::TimeDomainFeatures::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 307 of file TimeDomainFeatures.cpp.
VectorDouble GRT::TimeDomainFeatures::update | ( | const VectorDouble & | x | ) |
Computes the features from the input, the dimensionality of x should match that of this instance.
const | vector<double> &x: a vector containing the values to be processed, must be the same size as the numInputDimensions |
Definition at line 311 of file TimeDomainFeatures.cpp.