---
title: SmartPlate
emoji: 🍽️
colorFrom: green
colorTo: red
sdk: gradio
sdk_version: 4.32.0
python_version: '3.10'
app_file: app.py
pinned: false
license: mit
---

# SmartPlate – AI Nutrition Assistant

Photograph your meal and get instant nutritional analysis with evidence-based health advice from WHO, DGE, and Harvard guidelines.

## How it works

1. 📷 **Computer Vision** — A Vision Transformer (ViT) fine-tuned on Food-101 classifies the dish (20 classes, 96.46% accuracy)
2. 🔢 **ML Numeric** — Logistic Regression classifies the dish as healthy/medium/unhealthy based on nutritional values (100% test accuracy)
3. 💬 **NLP RAG** — OpenAI gpt-4o-mini generates evidence-based advice from a vector store (ChromaDB) of WHO/DGE/Harvard nutrition guidelines

## Supported food classes

Healthy: caesar_salad, greek_salad, edamame, miso_soup, grilled_salmon
Medium: sushi, sashimi, spaghetti_bolognese, pad_thai, chicken_curry, omelette, pancakes, ramen
Unhealthy: pizza, hamburger, french_fries, donuts, cheesecake, ice_cream, chocolate_cake

## Project Repository

GitHub: https://github.com/Gianone-byte/smartplate

Built as a semester project for the ZHAW "KI-Anwendungen" Module (FS 2026).