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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).
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
- Ubuntu 18.04
- DeepStream SDK 5.1 or later
- Python 3.6
- Gst Python v1.14.5
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Clone the repo
git clone https://github.com/imneonizer/pydstream.git cd pydstream -
Build the container
sudo chmod +x container.sh sudo ./container.sh --build
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Run the container
sudo ./container.sh --run
Go to the samples directory and run test apps, for example:
cd samples/deepstream-test1
python ./deepstream_test_1.pyYou can explore the sample apps to understand how pipeline construction works.
See the open issues for a list of proposed features (and known issues).
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.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
DeepStream Python Apps use third-party packages that may be distributed under different licensing terms from DeepStream licenses. See LICENSE for more information.
Nitin Rai - @imneonizer - mneonizer@gmail.com
Project Link: https://github.com/imneonizer/pydstream