2019 R1.2
Pre-release
Pre-release
This release contains GStreamer* Video Analytics plugins that bring Deep Learning Inference capabilities to open-source framework GStreamer* and helps developers to build highly efficient and scalable video analytics applications. The solution:
- Extracts insights from video stream(s) using object detection, classification and recognition CNN models and sends video metadata to application or cloud service for further processing
- Leverages hardware acceleration for media and inference operations and heterogeneous execution across Intel CPU and GPU
- Provides flexible mechanism to quickly construct video analytics pipeline from highly optimized building blocks
- Deployable on both edge devices and cloud infrastructure, including deployment in Docker containers
Can be used for various applications such as video surveillance and security, smart city, retail analytics, ad insertion and others
New features in this release:
- Support of OpenVINO R1.1
- New element for configurable metadata publishing to Kafka and MQTT
- Improved stability of multichannel pipelines execution on Intel® Xeon™ CPU
- Improved/simplified Getting Started guide
Release details including known issues and system requirements are in available in the attached release notes.
Getting started is available on the Wiki