DeepStream Python Apps

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

SDK version supported: 6.1.1

The bindings sources along with build instructions are now available under bindings!

This release comes with Operating System upgrades (from Ubuntu 18.04 to Ubuntu 20.04) for DeepStreamSDK 6.1.1 support. This translates to upgrade in Python version to 3.8 and gst-python version has also been upgraded to 1.16.2 !

Download the latest release package complete with bindings and sample applications from the release section.

Please report any issues or bugs on the DeepStream SDK Forums. This enables the DeepStream community to find help at a central location.

• DeepStream Python Apps
  • Python Bindings
  • Sample Applications

Python Bindings

DeepStream pipelines can be constructed using Gst Python, the GStreamer framework's Python bindings. For accessing DeepStream MetaData, Python bindings are provided as part of this repository. This module is generated using Pybind11.

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.

Sample Applications

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

We currently provide the following sample applications:

• deepstream-test1 -- 4-class object detection pipeline
• deepstream-test2 -- 4-class object detection, tracking and attribute classification pipeline
• deepstream-test3 -- multi-stream pipeline performing 4-class object detection - now also supports triton inference server, no-display mode, file-loop and silent mode
• deepstream-test4 -- msgbroker for sending analytics results to the cloud
• deepstream-imagedata-multistream -- multi-stream pipeline with access to image buffers
• deepstream-ssd-parser -- SSD model inference via Triton server with output parsing in Python
• deepstream-test1-usbcam -- deepstream-test1 pipelien with USB camera input
• deepstream-test1-rtsp-out -- deepstream-test1 pipeline with RTSP output
• deepstream-opticalflow -- optical flow and visualization pipeline with flow vectors returned in NumPy array
• deepstream-segmentation -- segmentation and visualization pipeline with segmentation mask returned in NumPy array
• deepstream-nvdsanalytics -- multistream pipeline with analytics plugin
• runtime_source_add_delete -- add/delete source streams at runtime
• deepstream-imagedata-multistream-redaction -- multi-stream pipeline with face detection and redaction
• deepstream-rtsp-in-rtsp-out -- multi-stream pipeline with RTSP input/output
• deepstream-preprocess-test -- multi-stream pipeline using nvdspreprocess plugin with custom ROIs
• NEW deepstream-demux-multi-in-multi-out -- multi-stream pipeline using nvstreamdemux plugin to generated separate buffer outputs

Detailed application information is provided in each application's subdirectory under apps.