Quickly test AI model deployment and inference on your edge device
An edge application that runs on Raspberry Pi and utilizes the IMX500-based AI Camera to identify and track high visibility vests in real-time.
View the code on GitHub ❯
An edge application to track cars and analyze if they are parked in a marked parking space, to ensure efficient and organized parking solutions.
An edge application utilizing object classification for real-time analysis of production line performance with high accuracy.
An edge application to track people in queues to help optimize queue management to reduce waiting times and enhance efficiency.
An edge application that tracks multiple people in real time using keypoints and boxes to analyze the number of reps they do in an exercise group.
This sample application detects objects within configurable zones, combining a Backend for Console interaction and a UI to display images with detected objects and zone overlaps.
This sample application implements object detection and classification, featuring a Backend for Console interaction and a UI that displays images alongside detected objects.
This sample application implements human detection features like people counting and heatmaps. It includes a Backend for Console interaction and a UI that displays images with detected objects using metadata from the Console.
