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The smart city reference pipeline shows how to integrate various media building blocks, with analytics powered by the OpenVINO™ Toolkit, for traffic or stadium sensing, analytics and management tasks.
This repository presents a method for people counting using a CNN trained with IR-UWB radar samples, in the COVID-19 and GDPR context. The purpose is the monitoring of the number of people inside a room, sending e-mail notifications every 10 minutes with the status of the room.
Multi-sensor RealSense + YOLO Top-View People Counting System, developed within the MEI (Museo Egizio Immersive) project. The solution enables real-time detection and counting of people in defined spatial areas, driving immersive scene logic, lighting systems, and audience analytics for interactive museum installations in Unreal Engine 5.
The OpenCV project is dedicated to tracking and counting people present in both images and videos. With two distinct folders, this project performs people tracking and counting and also includes the ability to predict the distance from the camera and determine their direction.
This repository contains a crowd counting model using the CSRNet architecture to estimate the number of people in crowded scenes. The model is trained on the Shanghaitech dataset and aims to provide accurate crowd density maps and count predictions. Data augmentation techniques are employed to enhance the model's performance.
Real-time people counting and crowd monitoring using YOLO11 | AI-powered bidirectional tracking | Perfect for schools, retail, exhibitions | Raspberry Pi ready