README.md

metadata

title: Food Recognition API
emoji: 🍕
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: false
license: mit
short_description: FastAPI food recognition service

🍕 Food Recognition API

A FastAPI web service that uses a Vision Transformer model to recognize 10 different types of food from images.

🎯 Features

• FastAPI Backend - RESTful API with comprehensive endpoints
• Gradio Interface - User-friendly web interface
• Vision Transformer - State-of-the-art image classification
• Real-time Predictions - Instant food recognition
• Multiple Input Methods - File upload and base64 support

🍽️ Supported Food Types

1. Apple Pie
2. Caesar Salad
3. Chocolate Cake
4. Cup Cakes
5. Donuts
6. Hamburger
7. Ice Cream
8. Pancakes
9. Pizza
10. Waffles

📡 API Endpoints

• / - Gradio web interface
• /health - Health check and model status
• /classes - Get supported food classes
• /model-info - Detailed model information
• /docs - Interactive API documentation

🚀 Usage

Web Interface

Simply upload an image using the Gradio interface above!

API Usage

import requests

# Upload image file
with open('food_image.jpg', 'rb') as f:
    files = {'file': f}
    response = requests.post('https://your-space-url.hf.space/predict', files=files)
    result = response.json()
    print(result)

Health Check

curl https://your-space-url.hf.space/health

📊 Model Performance

• Accuracy: 68%
• F1 Score: 66.5%
• Architecture: Vision Transformer (ViT-Base)
• Training Data: Custom food dataset
• Classes: 10 food categories

🔧 Technical Details

• Framework: FastAPI + Gradio
• Model: Hugging Face Transformers
• Backend: PyTorch
• Deployment: Hugging Face Spaces

📝 Model Information

• Model ID: BinhQuocNguyen/food-recognition-vit
• Model URL: https://huggingface.co/BinhQuocNguyen/food-recognition-vit
• Training Time: ~84 minutes
• Image Size: 224x224 pixels

🛠️ Local Development

# Clone the repository
git clone https://github.com/your-username/food-recognition-api

# Install dependencies
pip install -r requirements_spaces.txt

# Run locally
python app.py

📄 License

MIT License - Feel free to use and modify for your projects.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📞 Support

If you encounter any issues or have questions, please open an issue on the repository.