IndiScan / README.md
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---
title: IndiScan
emoji: πŸ”
colorFrom: green
colorTo: blue
sdk: streamlit
sdk_version: "1.31.0"
app_file: app.py
pinned: false
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
# IndiScan: Indian Product Health Analyzer πŸ”
IndiScan is a comprehensive health analysis tool that helps users make informed decisions about food and cosmetic products by analyzing ingredients, providing health scores, and comparing prices across Indian e-commerce platforms.
## Features 🌟
- **Smart Product Analysis**
- Barcode scanning
- Image-based ingredient extraction
- Manual ingredient entry
- Health score calculation (0-1000)
- Ingredient risk assessment
- Nutrition information analysis
- **Price Comparison**
- Real-time price tracking across:
- Amazon India
- Blinkit
- Zepto
- Swiggy Instamart
- **Admin Controls**
- Product database management
- CSV import/export
- 60-day auto-refresh system
## Setup πŸ› οΈ
1. Install dependencies:
```bash
pip install -r requirements.txt
```
2. Run the application:
```bash
python app.py
```
The application will start both the backend API (port 8000) and the Streamlit frontend.
## Usage πŸ“±
1. **Scan Products**
- Enter a barcode number
- Upload a product image
- Manually enter ingredients
2. **View Analysis**
- Health score and explanation
- Ingredient breakdown
- Risk categories
- Nutrition information
- Price comparison
3. **Admin Features**
- Login with admin credentials
- Add/update product information
- Export/import database
- Monitor data freshness
## Technology Stack πŸ’»
- **Backend**: FastAPI
- **Frontend**: Streamlit
- **Database**: SQLite
- **Image Processing**: EasyOCR
- **Data Analysis**: Pandas, Plotly
- **Web Scraping**: aiohttp, BeautifulSoup4
## Contributing 🀝
Feel free to contribute to this project by:
1. Forking the repository
2. Creating a feature branch
3. Committing your changes
4. Opening a pull request
## License πŸ“„
This project is licensed under the MIT License - see the LICENSE file for details.
## Acknowledgments πŸ™
- Inspired by the Yuka app
- Uses OpenFoodFacts data
- Built with ❀️ for Indian consumers