This repository has been archived by the owner on Jul 10, 2023. It is now read-only.
v0.4.1-beta
Pre-release
Pre-release
Video Analytics Serving (VA Serving) is a python package and microservice for deploying hardware optimized media analytics pipelines. It supports pipelines defined in GStreamer* or FFmpeg* media frameworks and provides APIs to discover, start, stop, customize and monitor pipeline execution. Video Analytics Serving is based on Intel® Distribution of OpenVINO™ Toolkit - DL Streamer and FFmpeg Video Analytics.
New and Changed in Release v0.4.1-beta
| Title | Description |
|---|---|
| Hardware accelerator support | Updated VA Serving REST microservice and the Edge AI Extension sample to support Intel® Neural Compute Stick 2 and HDDL-R cards as inference devices. |
| Edge AI Extension Module | Updated to the latest version of gRPC AI Extension for Live Video Analytics on IoT Edge which includes a new tracking id metadata for object tracking. |
| Model Download Tool (MDT) | Added a shell script to provide a consistent environment and improved developer experience for downloading the models from Open Model Zoo. |
| Model-proc auto-selection | VA Serving can auto-select model-proc based on the model name. If a model-proc is not configured for an inference element in a pipeline, VA Serving will search the model-procs downloaded by MDT and select the appropriate one. |
Known Issues
Known issues can be found as GitHub issues. If you encounter defects in functionality, please submit an issue.
| Description | Issue |
|---|---|
| Docker build fails if directory name contains spaces | #38 |
Tested Base Images
Supported base images are listed in the Building Video Analytics Serving document.
* Other names and brands may be claimed as the property of others.