This project implements a prototype AI-based self-checkout system that uses computer vision to automatically recognize products placed in front of a camera and calculate their total price. The system is designed to simulate a simplified self-service retail experience, where users manually control the scanning process using physical buttons.
When a product is placed in view of the camera, an object detection model identifies supported items such as fruits, vegetables, and packaged food. By pressing an “Add” button, all valid items currently detected in the camera frame are added to a virtual inventory. This process can be repeated multiple times, allowing users to scan products in batches. Once all items are added, a “Checkout” button displays the final purchase summary and total price. A “Reset” button clears the inventory, preparing the system for the next customer. This project demonstrates how AI-powered vision, hardware controls, and user interfaces can be combined to create intelligent retail automation systems.