Snap What You Have, Cook What You Can.

SnapNcook is an AI-powered web application that helps you cook smarter and reduce food waste. Just snap a photo of your fridge or kitchen items and our custom-trained YOLOv11 model detects ingredients, and we suggest recipes based on what’s available. Optionally, Gemini API integration helps enhance recipe suggestions.

• Ingredient detection using YOLOv11
• FastAPI-powered backend
• Recipe suggestion system (Gemini-enhanced)
• Static frontend with HTML/CSS/JS
• Gemini API integration via .env
• Future-ready for voice, grocery suggestions, and more!

snapncook/
│
├── app/
│   ├── main.py                # FastAPI backend entry point
│   ├── model_loader.py        # Loads YOLOv8 model
│   ├── image_processor.py     # Image handling logic
│   ├── best.pt                # Trained YOLOv8 model
│   └── .env                   # Environment variables (ignored in Git)
│
├── static/
│   └── css/style.css          # UI styles
│   └── script.js              # Frontend JS logic
│
├── templates/
│   └── index.html             # Main HTML page
│
├── model results/             # Output images from detection
├── requirements.txt           # Python dependencies
└── README.md                  # Project documentation

1. Clone the Repository

git clone https://github.com/yourusername/snapncook.git
cd snapncook/app

2. Install Python Dependencies

pip install -r ../requirements.txt

3. Add .env File

GEMINI_API_KEY=your-gemini-api-key-here

4. Run the FastAPI Server

uvicorn main:app --reload

This project uses the latest YOLOv8 via the Ultralytics package, sometimes referred to as YOLOv11 due to its community-enhanced capabilities.

• Voice-based ingredient input
• Grocery list generator
• Save and share favorite recipes
• Nutrition breakdowns
• More advanced recipe AI using Gemini Pro Vision

PRs and feedback are always welcome! Fork the repo, create a feature branch, and submit a pull request.