Object detection on Edge devices with Live Video Analytics using YOLO model
Intermediate
AI Edge Engineer
Azure IoT Hub
Review how a historical Live Video Analytics on IoT Edge solution used Azure resources, IoT Edge modules, a YOLO model, and a web app to process camera video and validate object detection at the edge.
Learning objectives
In this module, you will:
- Review how a historical Live Video Analytics on IoT Edge solution was structured
- Identify Azure resources and IoT Edge modules used by the archived Vision on Edge sample
- Examine how the installer and virtual device supported rapid inference at the edge
- Review how a YOLO-based AI model was incorporated into the video analytics workflow
- Examine how the historical solution was validated from a web application
"Produced in partnership with the University of Oxford – Ajit Jaokar, Artificial Intelligence: Cloud and Edge Implementations course."
Prerequisites
- An Azure subscription
- Ability to use Azure Cloud Shell
- Basic knowledge of Azure IoT Edge 1.5 LTS
- Basic knowledge of containers
- Ability to use Docker in a local environment or build host that has a Docker daemon
- Awareness that Custom Vision is a legacy dependency with a planned retirement, and Live Video Analytics and Azure Media Services are no longer supported for this scenario