This project implements an AI-based video surveillance system on a Raspberry Pi. Utilizing advanced object detection and counting algorithms, the system is capable of real-time monitoring and analysis. The core functionality leverages machine learning models to detect and count objects within the video feed, making it suitable for various security and monitoring applications.
The Project is about object detection, tracking and counting with tensorflow lite for a raspberry pi, and the data of detection, tracking and counting is shown on a webpage using the Flask library.
To run the program just run the python script "object_detection_counting_web.py". But don't forget to install the necessary packages from PIP or install them from the source if they are not available for your architecture!