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Void detection on Edge devices with Live Video Analytics using own images and video

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Module

11 Units

Use a Live Video Analytics module on IoT Edge and deploy a Custom Vision machine learning solution to an IoT Edge device. The solution will identify void spaces in shelves. Check that the solution is successfully deployed and test your solution from a web application.

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Use Live Video Analytics to build video analytics solution with Custom Vision, Deploy a set of modules to an IoT Edge virtual machine using the installer, Set up an application that uses the virtual device for rapid inference at the edge, Deploy a solution that will enable you to watch images with defects through a web application
Prerequisites
An Azure subscription
Ability to use Azure Cloud Shell
Basic knowledge of Azure IoT Edge
Basic knowledge of Custom Vision
Basic knowledge of Live Video Analytics

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Void detection on Edge devices with Live Video Analytics using own images and video
Void detection on Edge devices with Live Video Analytics using own images and video
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