README.md

metadata

title: IndiScan
emoji: 🔍
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 🔍

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 🛠️

1. Install dependencies:

pip install -r requirements.txt

2. Run the application:

python app.py

The application will start both the backend API (port 8000) and the Streamlit frontend.

Usage 📱

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 💻

• 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 📄

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments 🙏

• Inspired by the Yuka app
• Uses OpenFoodFacts data
• Built with ❤️ for Indian consumers