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GestureRecognitionToolkit
Version: 0.1.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
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GestureRecognitionToolkit
Version: 0.1.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
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This is the complete list of members for FFT, including all inherited members.
| BARTLETT_WINDOW enum value (defined in FFT) | FFT | |
| BASE_TYPE_NOT_SET enum value (defined in MLBase) | MLBase | |
| baseType (defined in MLBase) | MLBase | protected |
| BaseTypes enum name (defined in MLBase) | MLBase | |
| CLASSIFIER enum value (defined in MLBase) | MLBase | |
| classType (defined in GRTBase) | GRTBase | protected |
| clear() | FFT | virtual |
| CLUSTERER enum value (defined in MLBase) | MLBase | |
| computeFeatures(const VectorFloat &inputVector) | FFT | virtual |
| computeFeatures(const MatrixFloat &inputMatrix) | FFT | virtual |
| computeMagnitude | FFT | protected |
| computePhase | FFT | protected |
| copyBaseVariables(const FeatureExtraction *featureExtractionModule) | FeatureExtraction | |
| copyGRTBaseVariables(const GRTBase *GRTBase) | GRTBase | |
| copyMLBaseVariables(const MLBase *mlBase) | MLBase | |
| createInstanceFromString(const std::string &featureExtractionType) (defined in FeatureExtraction) | FeatureExtraction | static |
| createNewInstance() const | FeatureExtraction | |
| dataBuffer | FFT | protected |
| dataBufferSize | FFT | protected |
| debugLog (defined in GRTBase) | GRTBase | protected |
| deepCopyFrom(const FeatureExtraction *featureExtraction) | FFT | virtual |
| enableScaling(const bool useScaling) | MLBase | |
| errorLog (defined in GRTBase) | GRTBase | protected |
| featureDataReady (defined in FeatureExtraction) | FeatureExtraction | protected |
| FeatureExtraction() | FeatureExtraction | |
| featureExtractionType (defined in FeatureExtraction) | FeatureExtraction | protected |
| featureMatrix (defined in FeatureExtraction) | FeatureExtraction | protected |
| featureVector (defined in FeatureExtraction) | FeatureExtraction | protected |
| FFT(UINT fftWindowSize=512, UINT hopSize=1, UINT numDimensions=1, UINT fftWindowFunction=RECTANGULAR_WINDOW, bool computeMagnitude=true, bool computePhase=true) | FFT | |
| FFT(const FFT &rhs) | FFT | |
| fft | FFT | protected |
| fftWindowFunction | FFT | protected |
| FFTWindowFunctionOptions enum name (defined in FFT) | FFT | |
| fftWindowSize | FFT | protected |
| getBaseType() const | MLBase | |
| getClassType() const | GRTBase | |
| getComputeMagnitude() | FFT | inline |
| getComputePhase() | FFT | inline |
| getDataBufferSize() | FFT | |
| getFeatureDataReady() const | FeatureExtraction | |
| getFeatureExtractionType() const | FeatureExtraction | |
| getFeatureMatrix() const | FeatureExtraction | |
| getFeatureVector() const | FeatureExtraction | |
| getFFTResults() | FFT | inline |
| getFFTResultsPtr() | FFT | inline |
| getFFTWindowFunction() | FFT | |
| getFFTWindowSize() | FFT | |
| getFrequencyBins(const unsigned int sampleRate) (defined in FFT) | FFT | |
| getGRTBasePointer() | GRTBase | |
| getGRTBasePointer() const | GRTBase | |
| getGRTRevison() | GRTBase | static |
| getGRTVersion(bool returnRevision=true) | GRTBase | static |
| getHopCounter() | FFT | |
| getHopSize() | FFT | |
| getInitialized() const | FeatureExtraction | |
| getInputType() const | MLBase | |
| getIsBaseTypeClassifier() const | MLBase | |
| getIsBaseTypeClusterer() const | MLBase | |
| getIsBaseTypeRegressifier() const | MLBase | |
| getLastErrorMessage() const | GRTBase | |
| getLastInfoMessage() const | GRTBase | |
| getLastWarningMessage() const | GRTBase | |
| getLearningRate() const | MLBase | |
| getMap() (defined in FeatureExtraction) | FeatureExtraction | inlineprotectedstatic |
| getMaxNumEpochs() const | MLBase | |
| getMinChange() const | MLBase | |
| getMinNumEpochs() const | MLBase | |
| getMLBasePointer() | MLBase | |
| getMLBasePointer() const | MLBase | |
| getModel(std::ostream &stream) const | MLBase | virtual |
| getModelAsString() const | MLBase | virtual |
| getModelTrained() const | MLBase | |
| getNumInputDimensions() const | FeatureExtraction | |
| getNumInputFeatures() const | MLBase | |
| getNumOutputDimensions() const | FeatureExtraction | |
| getNumTrainingIterationsToConverge() const | MLBase | |
| getOutputType() const | MLBase | |
| getRandomiseTrainingOrder() const | MLBase | |
| getRootMeanSquaredTrainingError() const | MLBase | |
| getScalingEnabled() const | MLBase | |
| getTotalSquaredTrainingError() const | MLBase | |
| getTrained() const | MLBase | |
| getTrainingResults() const | MLBase | |
| getUseValidationSet() const | MLBase | |
| getValidationSetAccuracy() const | MLBase | |
| getValidationSetPrecision() const | MLBase | |
| getValidationSetRecall() const | MLBase | |
| getValidationSetSize() const | MLBase | |
| GRTBase(void) | GRTBase | |
| HAMMING_WINDOW enum value (defined in FFT) | FFT | |
| HANNING_WINDOW enum value (defined in FFT) | FFT | |
| hopCounter | FFT | protected |
| hopSize | FFT | protected |
| infoLog (defined in GRTBase) | GRTBase | protected |
| init(UINT fftWindowSize, UINT hopSize, UINT numDimensions, UINT windowFunction, bool computeMagnitude, bool computePhase, DataType inputType=DATA_TYPE_VECTOR, DataType outputType=DATA_TYPE_VECTOR) | FFT | |
| FeatureExtraction::init() | FeatureExtraction | protected |
| initialized (defined in FeatureExtraction) | FeatureExtraction | protected |
| inputType (defined in MLBase) | MLBase | protected |
| isPowerOfTwo(UINT x) | FFT | protected |
| learningRate (defined in MLBase) | MLBase | protected |
| load(const std::string filename) | MLBase | virtual |
| loadBaseSettingsFromFile(std::fstream &file) | MLBase | protected |
| loadFeatureExtractionSettingsFromFile(std::fstream &file) | FeatureExtraction | protected |
| loadModelFromFile(std::fstream &file) | FFT | virtual |
| MLBase::loadModelFromFile(std::string filename) | MLBase | virtual |
| map(VectorFloat inputVector) | MLBase | virtual |
| map_(VectorFloat &inputVector) | MLBase | virtual |
| maxNumEpochs (defined in MLBase) | MLBase | protected |
| minChange (defined in MLBase) | MLBase | protected |
| minNumEpochs (defined in MLBase) | MLBase | protected |
| MLBase(void) | MLBase | |
| notify(const TrainingResult &data) (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inlinevirtual |
| notify(const TestInstanceResult &data) (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inlinevirtual |
| notifyTestResultsObservers(const TestInstanceResult &data) | MLBase | |
| notifyTrainingResultsObservers(const TrainingResult &data) | MLBase | |
| numInputDimensions (defined in MLBase) | MLBase | protected |
| numOutputDimensions (defined in MLBase) | MLBase | protected |
| numTrainingIterationsToConverge (defined in MLBase) | MLBase | protected |
| Observer() (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inline |
| Observer() (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inline |
| operator=(const FFT &rhs) | FFT | |
| outputType (defined in MLBase) | MLBase | protected |
| predict(VectorFloat inputVector) | MLBase | virtual |
| predict(MatrixFloat inputMatrix) | MLBase | virtual |
| predict_(VectorFloat &inputVector) | MLBase | virtual |
| predict_(MatrixFloat &inputMatrix) | MLBase | virtual |
| print() const | MLBase | virtual |
| random (defined in MLBase) | MLBase | protected |
| randomiseTrainingOrder (defined in MLBase) | MLBase | protected |
| RECTANGULAR_WINDOW enum value (defined in FFT) | FFT | |
| registerModule (defined in FFT) | FFT | protectedstatic |
| registerTestResultsObserver(Observer< TestInstanceResult > &observer) | MLBase | |
| registerTrainingResultsObserver(Observer< TrainingResult > &observer) | MLBase | |
| REGRESSIFIER enum value (defined in MLBase) | MLBase | |
| removeAllTestObservers() | MLBase | |
| removeAllTrainingObservers() | MLBase | |
| removeTestResultsObserver(const Observer< TestInstanceResult > &observer) | MLBase | |
| removeTrainingResultsObserver(const Observer< TrainingResult > &observer) | MLBase | |
| reset() | FFT | virtual |
| rootMeanSquaredTrainingError (defined in MLBase) | MLBase | protected |
| save(const std::string filename) const | MLBase | virtual |
| saveBaseSettingsToFile(std::fstream &file) const | MLBase | protected |
| saveFeatureExtractionSettingsToFile(std::fstream &file) const | FeatureExtraction | protected |
| saveModelToFile(std::fstream &file) const | FFT | virtual |
| MLBase::saveModelToFile(std::string filename) const | MLBase | virtual |
| scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false) | MLBase | inline |
| setComputeMagnitude(bool computeMagnitude) | FFT | |
| setComputePhase(bool computePhase) | FFT | |
| setErrorLoggingEnabled(const bool loggingEnabled) | GRTBase | |
| setFFTWindowFunction(UINT fftWindowFunction) | FFT | |
| setFFTWindowSize(UINT fftWindowSize) | FFT | |
| setHopSize(UINT hopSize) | FFT | |
| setInfoLoggingEnabled(const bool loggingEnabled) | GRTBase | |
| setLearningRate(const Float learningRate) | MLBase | |
| setMaxNumEpochs(const UINT maxNumEpochs) | MLBase | |
| setMinChange(const Float minChange) | MLBase | |
| setMinNumEpochs(const UINT minNumEpochs) | MLBase | |
| setRandomiseTrainingOrder(const bool randomiseTrainingOrder) | MLBase | |
| setTrainingLoggingEnabled(const bool loggingEnabled) | MLBase | |
| setUseValidationSet(const bool useValidationSet) | MLBase | |
| setValidationSetSize(const UINT validationSetSize) | MLBase | |
| setWarningLoggingEnabled(const bool loggingEnabled) | GRTBase | |
| SQR(const Float &x) const (defined in GRTBase) | GRTBase | inlineprotected |
| StringFeatureExtractionMap typedef | FeatureExtraction | |
| tempBuffer | FFT | protected |
| testingLog (defined in GRTBase) | GRTBase | protected |
| testResultsObserverManager (defined in MLBase) | MLBase | protected |
| totalSquaredTrainingError (defined in MLBase) | MLBase | protected |
| train(ClassificationData trainingData) | MLBase | virtual |
| train(RegressionData trainingData) | MLBase | virtual |
| train(TimeSeriesClassificationData trainingData) | MLBase | virtual |
| train(ClassificationDataStream trainingData) | MLBase | virtual |
| train(UnlabelledData trainingData) | MLBase | virtual |
| train(MatrixFloat data) | MLBase | virtual |
| train_(ClassificationData &trainingData) | MLBase | virtual |
| train_(RegressionData &trainingData) | MLBase | virtual |
| train_(TimeSeriesClassificationData &trainingData) | MLBase | virtual |
| train_(ClassificationDataStream &trainingData) | MLBase | virtual |
| train_(UnlabelledData &trainingData) | MLBase | virtual |
| train_(MatrixFloat &data) | MLBase | virtual |
| trained (defined in MLBase) | MLBase | protected |
| trainingLog (defined in GRTBase) | GRTBase | protected |
| trainingResults (defined in MLBase) | MLBase | protected |
| trainingResultsObserverManager (defined in MLBase) | MLBase | protected |
| update(const Float x) | FFT | |
| update(const VectorFloat &x) | FFT | |
| update(const MatrixFloat &x) | FFT | |
| useScaling (defined in MLBase) | MLBase | protected |
| useValidationSet (defined in MLBase) | MLBase | protected |
| validateFFTWindowFunction(UINT fftWindowFunction) (defined in FFT) | FFT | protected |
| validationSetAccuracy (defined in MLBase) | MLBase | protected |
| validationSetPrecision (defined in MLBase) | MLBase | protected |
| validationSetRecall (defined in MLBase) | MLBase | protected |
| validationSetSize (defined in MLBase) | MLBase | protected |
| warningLog (defined in GRTBase) | GRTBase | protected |
| windowSizeMap | FFT | protected |
| ~FeatureExtraction() | FeatureExtraction | virtual |
| ~FFT(void) | FFT | virtual |
| ~GRTBase(void) | GRTBase | virtual |
| ~MLBase(void) | MLBase | virtual |
| ~Observer() (defined in Observer< TrainingResult >) | Observer< TrainingResult > | inlinevirtual |
| ~Observer() (defined in Observer< TestInstanceResult >) | Observer< TestInstanceResult > | inlinevirtual |
1.8.11 
