Inference Engine & integration with Deep Learning applications

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Lab - Retail use-case: Store Aisle Monitor

In this lab exercise on Intel® DevCloud for the Edge, you will learn to Run inference on a pre-trained people detection model from the Intel Distribution of OpenVINO™ toolkit to detect people in a retail setting. This sample application demonstrates how a smart video IoT solution may be created using Intel® hardware and software tools to perform store aisle monitoring. This solution detects any number of people within a video frame and:

  • Draws a box around each detected person
  • Periodically (every 5 seconds) Saves a snapshot image of the frame with inference time and count (filename includes timestamp)
  • Optionally uploads the snapshot image to the Azure cloud

To get started, follow the below steps:

  • Go to Intel® DevCloud for the Edge and login using your Intel account.
  • Navigate to Home page --> Learn -->Get Started --> Sample Applications --> Store Aisle Monitor
  • Follow the steps mentioned in the Jupyter* Notebook to understand the concepts and complete this lab. enter image description here

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