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- Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
- Curated collections of sample applications designed to help you develop optimized AI solutions. Tailored to specific use cases, covering retail, manufacturing, metro, and media & entertainment.
- A comprehensive solution designed to streamline and enhance the deployment and management of infrastructure and applications at the edge
- An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
- Utilities of Edge Manageability Framework Orchestrator
scenescape
PublicMultimodal object tracking and scene analytics for highly actionable, real-world contextualized data- Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.
- SRE Exporter service enables exporting Edge Orchestrator's Service Level Indicators (SLIs) and its key runtime metrics to external systems.
- This repository provides key Observability Helm Charts and its helper applications deployable on the Edge Orchestrator.
- The Edge Microvisor Toolkit is a streamlined container host that showcases Intel® silicon optimizations. Built on the Azure Linux distribution, it features a Linux kernel maintained by Intel, incorporating all the latest kernel and user patches.
- Deep Learning Streamer (DL Streamer) Pipeline Framework is an open-source streaming media analytics framework, based on GStreamer* multimedia framework, for creating complex media analytics pipelines for the Cloud or at the Edge.
app-orch-catalog
Public- Build computer vision models in a fraction of the time and with less data.
- This framework provides a general-purpose toolchain for composing OS images from pre-built artifacts of any Linux distribution that supports Debian or RPM packages. With OS Image Composer, you can generate edge-optimized OS images using Intel's pre-curated YAML templates or your own customization.