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Deepstream Python API

Build Deepstream apps easily!
Explore the docs »

Samples · Report Bug · Request Feature

Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgements

About The Project

App Home

This repository contains Python bindings and sample applications for the DeepStream SDK.

DeepStream pipelines can be constructed using Gst Python, the GStreamer framework's Python bindings. For accessing DeepStream MetaData, Python bindings are provided in the form of a compiled module which is included in the DeepStream SDK.

These bindings support a Python interface to the MetaData structures and functions. Usage of this interface is documented in the HOW-TO Guide and demonstrated in the sample applications. This release adds bindings for decoded image buffers (NvBufSurface) as well as inference output tensors (NvDsInferTensorMeta).

Getting Started

Sample applications provided here demonstrate how to work with DeepStream pipelines using Python. The sample applications require MetaData Bindings to work.

To run the sample applications or write your own, please consult the HOW-TO Guide

Prerequisites

Installation

  1. Clone the repo

    git clone https://github.com/imneonizer/pydstream.git
cd pydstream

  2. Build the container

    sudo chmod +x container.sh
sudo ./container.sh --build

  3. Run the container

    sudo ./container.sh --run

Usage

Go to the samples directory and run test apps, for example:

cd samples/deepstream-test1
python ./deepstream_test_1.py

You can explore the sample apps to understand how pipeline construction works.

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

DeepStream Python Apps use third-party packages that may be distributed under different licensing terms from DeepStream licenses. See LICENSE for more information.

Contact

Nitin Rai - @imneonizer - [email protected]

Project Link: https://github.com/imneonizer/pydstream

Acknowledgements