NNStreamer Doxygen book

NNStreamer Doxygen book provides documents generated by doxygen comments of nnstreamer's source code. If you are investigating the internals of nnstreamer, this document might be helpful.

Tizen Machine-Learning Native API reference

NNStreamer is acting as the library to execute inferences in Tizen; in other words, NNStreamer is the implementation of the Tizen's MachineLearning.Inference APIs. This link provides native APIs (C-APIs) for Tizen Machine Learning. In this document, the "inference.single" and "inference.pipeline" are implemented by NNStreamer. MachineLearning.Inference.Single allows using subplugins of tensor_filter to run the given neural network model, invoking the model directly from the application with a single-shot input data. MachineLearning.Inference.Pipeline allows describing and executing GStreamer pipelines including NNStreamer elements. Note that MachineLearning.Training and MachineLearning.Service are implemented by other packages in this organization.

This API's main target is Tizen, but it supports other OS as well.

If you are writing Tizen applications in C/C++ along with neural network inferences, you are supposed to use Tizen Machine-Learning.Inference Native APIs.

Tizen Machine-Learning .NET API reference

If you are writing Tizen applications in .NET along with neural network inferences, you are supposed to use Tizen Machine-Learning.Inference.Singleshot/Pipeline .NET APIs. The subdomains have the same roles as in Native APIs.

This API's main target is Tizen, but it supports other OS as well.

Tizen Machine-Learning Web API reference

If you are writing Tizen web applications along with neural network inferences, you are supposed to use Tizen Machine-Learning.Inference.Single/Pipeline Web APIs. The subdomains have the same roles as in Native APIs.

  • Web API (HTML5) (stable, since Tizen 6.5 M2)

Android Java API reference

We provide Java APIs for Android applications. Note that this supports SingleShot/Pipeline subdomains and do not include training or ML-service capabilities.

Python API is planned

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