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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Files | |
file | ClassificationData.cpp [code] |
file | ClassificationData.h [code] |
The ClassificationData is the main data structure for recording, labeling, managing, saving, and loading training data for supervised learning problems. | |
file | ClassificationDataStream.cpp [code] |
file | ClassificationDataStream.h [code] |
The ClassificationDataStream is the main data structure for recording, labeling, managing, saving, and loading datasets that can be used to test the continuous classification abilities of the GRT supervised learning algorithms. | |
file | ClassificationSample.cpp [code] |
file | ClassificationSample.h [code] |
This class stores the class label and raw data for a single labelled classification sample. | |
file | Matrix.h [code] |
The Matrix class is a basic class for storing any type of data. This class is a template and can therefore be used with any generic data type. | |
file | MatrixFloat.cpp [code] |
file | MatrixFloat.h [code] |
file | RegressionData.cpp [code] |
file | RegressionData.h [code] |
The RegressionData is the main data structure for recording, labeling, managing, saving, and loading datasets that can be used to train and test the GRT supervised regression algorithms. | |
file | RegressionSample.cpp [code] |
file | RegressionSample.h [code] |
This class stores the input vector and target vector for a single labelled regression instance. | |
file | TimeSeriesClassificationData.cpp [code] |
file | TimeSeriesClassificationData.h [code] |
The TimeSeriesClassificationData is the main data structure for recording, labeling, managing, saving, and loading training data for supervised temporal learning problems. Unlike the ClassificationData, in which each sample consists of 1 N dimensional datum, a TimeSeriesClassificationData sample will consist of an N dimensional time series of length M. The length of each time series sample (i.e. M) can be different for each datum in the dataset. | |
file | TimeSeriesClassificationSample.cpp [code] |
file | TimeSeriesClassificationSample.h [code] |
This class stores the timeseries data for a single labelled timeseries classification sample. | |
file | TimeSeriesPositionTracker.h [code] |
This class can be used to track the class label, start and end indexs for labelled data. | |
file | UnlabelledData.cpp [code] |
file | UnlabelledData.h [code] |
The UnlabelledData class is the main data container for supporting unsupervised learning. | |
file | Vector.h [code] |
The Vector class is a basic class for storing any type of data. The default Vector is an interface for std::vector, but the idea is this can easily be changed when needed (e.g., when running the GRT on an embedded device with limited STL support). This class is a template and can therefore be used with any generic data type. | |
file | VectorFloat.cpp [code] |
file | VectorFloat.h [code] |