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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 | |
FFTFeatures (UINT fftWindowSize=512, UINT numChannelsInFFTSignal=1, bool computeMaxFreqFeature=true, bool computeMaxFreqSpectrumRatio=true, bool computeCentroidFeature=true, bool computeTopNFreqFeatures=true, UINT N=10) | |
FFTFeatures (const FFTFeatures &rhs) | |
virtual | ~FFTFeatures (void) |
FFTFeatures & | operator= (const FFTFeatures &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 fftWindowSize, UINT numChannelsInFFTSignal, bool computeMaxFreqFeature, bool computeMaxFreqSpectrumRatio, bool computeCentroidFeature, bool computeTopNFreqFeatures, UINT N) |
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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 | fftWindowSize |
UINT | numChannelsInFFTSignal |
bool | computeMaxFreqFeature |
bool | computeMaxFreqSpectrumRatio |
bool | computeCentroidFeature |
bool | computeTopNFreqFeatures |
UINT | N |
double | maxFreqFeature |
double | maxFreqSpectrumRatio |
double | centroidFeature |
VectorDouble | topNFreqFeatures |
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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< FFTFeatures > | 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 FFTFeatures.h.
GRT::FFTFeatures::FFTFeatures | ( | UINT | fftWindowSize = 512 , |
UINT | numChannelsInFFTSignal = 1 , |
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bool | computeMaxFreqFeature = true , |
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bool | computeMaxFreqSpectrumRatio = true , |
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bool | computeCentroidFeature = true , |
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bool | computeTopNFreqFeatures = true , |
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UINT | N = 10 |
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Default Constructor, sets the default settings for the FFTFeatures module. The fftWindowSize and numChannelsInFFTSignal parameters should match the settings of the FFT module that will be used as input to this module.
UINT | fftWindowSize: the window size of the FFT that will be used as input to this module. Default value = 512 |
UINT | numChannelsInFFTSignal: this is the number of channels (i.e. input dimensions) to the FFT module. Default value = 1 |
bool | computeMaxFreqFeature: sets if the maximum frequency feature will be included in the feature vector. Default value = true |
bool | computeMaxFreqSpectrumRatio: sets if the maximum-frequency spectrum-frequency ratio feature will be included in the feature vector. Default value = true |
bool | computeCentroidFeature: sets if the centroid frequency feature will be included in the feature vector. Default value = true |
bool | computeTopNFreqFeatures: sets if the top N frequency feature will be included in the feature vector. Default value = true |
bool | N: sets if size of N for the top N frequency features. Default value = 10 |
Definition at line 30 of file FFTFeatures.cpp.
GRT::FFTFeatures::FFTFeatures | ( | const FFTFeatures & | rhs | ) |
Copy Constructor, copies the FFTFeatures from the rhs instance to this instance
const | FFTFeatures &rhs: another instance of the FFTFeatures class from which the data will be copied to this instance |
Definition at line 44 of file FFTFeatures.cpp.
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Default Destructor
Definition at line 57 of file FFTFeatures.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).
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 269 of file FFTFeatures.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 an FFTFeatures, the values of that instance will be cloned to this instance |
Reimplemented from GRT::FeatureExtraction.
Definition at line 80 of file FFTFeatures.cpp.
bool GRT::FFTFeatures::init | ( | UINT | fftWindowSize, |
UINT | numChannelsInFFTSignal, | ||
bool | computeMaxFreqFeature, | ||
bool | computeMaxFreqSpectrumRatio, | ||
bool | computeCentroidFeature, | ||
bool | computeTopNFreqFeatures, | ||
UINT | N | ||
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Initializes the FFTFeatures. Should be called before calling the computeFFT(...) or computeFeatures(...) methods. This function is automatically called by the constructor.
UINT | fftWindowSize: the window size of the FFT that will be used as input to this module. Default value = FFT::FFT_WINDOW_SIZE_512 |
UINT | numChannelsInFFTSignal: the size of the FFT feature vector that will be used as input to this module. Default value = 1 |
bool | computeMaxFreqFeature: sets if the maximum frequency feature will be included in the feature vector. Default value = true |
bool | computeMaxFreqSpectrumRatio: sets if the maximum-frequency spectrum-frequency ratio feature will be included in the feature vector. Default value = true |
bool | computeCentroidFeature: sets if the centroid frequency feature will be included in the feature vector. Default value = true |
bool | computeTopNFreqFeatures: sets if the top N frequency feature will be included in the feature vector. Default value = true |
bool | N: sets if size of N for the top N frequency features. Default value = 10 |
Definition at line 231 of file FFTFeatures.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 111 of file FFTFeatures.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 154 of file FFTFeatures.cpp.
FFTFeatures & GRT::FFTFeatures::operator= | ( | const FFTFeatures & | rhs | ) |
Sets the equals operator, copies the data from the rhs instance to this instance
const | FFTFeatures &rhs: another instance of the FFTFeatures class from which the data will be copied to this instance |
Definition at line 61 of file FFTFeatures.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 FFTFeatures by re-initiliazing the instance.
Reimplemented from GRT::FeatureExtraction.
Definition at line 346 of file FFTFeatures.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 97 of file FFTFeatures.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 126 of file FFTFeatures.cpp.