This project simulates a monitoring system for kitchens, using YOLO for object detection and tracking. The detection model is trained to track two types of items (dish, tray), and each item type has a classification model to further categorize them into three sub-classes, depending on the content of the dish or tray.
The system includes a module to perform inference, and a module for users to re-annotate the object detection themselves.
- Models: YOLO (for detection, tracking, and classification)
- Tools: FastAPI, Gradio, Docker