Mohamed Ashraf Zaki Omar Ashraf

Food Classifier App

Developed an end-to-end Computer Vision web application utilizing YOLO (You Only Look Once) to achieve real-time, high-accuracy food item detection and classification. Built a robust Full-Stack architecture integrating a React frontend for an intuitive user dashboard with a Django backend to orchestrate API requests and model inference tasks. Designed a non-relational database schema using MongoDB to efficiently store, index, and manage user detection history, food metadata, and classification logs. Optimized the end-to-end pipeline to ensure low-latency communication between the Deep Learning model and the backend server, maintaining seamless performance during concurrent image uploads.

React · Django · MongoDB · YOLO · Python