♻️ ReStyleAI – AI-Powered Circular Fashion Platform

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ReStyleAI is an AI-powered platform that promotes circular fashion by helping users match their existing clothes with sustainable alternatives — reducing textile waste, supporting ethical production, and raising environmental awareness.

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🌍 Problem Statement

"Every second, one garbage truck full of clothes is burned or buried."

The fashion industry is one of the largest contributors to global pollution. ReStyleAI empowers users to make sustainable choices by intelligently recommending matching items based on uploaded clothing, material type, and weight — using AI/ML-powered matching and impact calculations.

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🖼️ Demo

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🚀 Features

Feature	Description
📸 Upload Clothing	Drag & drop interface for garment images (JPG, PNG, JPEG up to 200MB)
🧵 Material & Weight	Select fabric type and weight for accurate impact analysis
♻️ AI Matching Engine	Top sustainable alternatives via image similarity + eco-impact scoring
🌱 Impact Calculator	CO₂ saved, water saved, and carbon footprint breakdown
💡 Circularity Score	Evaluates how eco-friendly your clothing choices are
📊 Impact Equivalents	Real-world analogies to make sustainability tangible

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🧠 How It Works

User uploads image + selects material & weight
        │
        ▼
  Image Processing (PIL + Base64)
        │
        ▼
  AI Matching Engine queries fashion database
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        ▼
  Returns: sustainable matches + CO₂ saved + water saved + circularity score

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🛠️ Tech Stack

Layer	Technology
Frontend	Streamlit + Custom CSS
Image Processing	PIL, Base64 Encoding
Backend	Python (FastAPI / Flask)
Matching Engine	Image URL + Material + Weight matching
Impact Engine	Custom logic based on material database
Containerization	Docker + Docker Compose
Cloud Deployment	GCP (deploy script included)

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📁 Project Structure

ReStyleAI/
├── backend/
│   ├── __init__.py
│   ├── main.py              # API entry point
│   ├── ai_engine.py         # Core AI matching logic
│   └── firebase_service.py  # Database integration
├── frontend/
│   ├── __init__.py
│   ├── app.py               # Streamlit UI
│   └── utils.py             # Utility functions
├── scripts/
│   ├── __init__.py
│   └── deploy_gcp.sh        # GCP deployment script
├── .env                     # Environment variables (not committed)
├── docker-compose.yml
├── Dockerfile
├── requirements.txt
└── README.md

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⚙️ Getting Started

Prerequisites

• Python 3.10+
• Docker (optional)
• Git

Local Setup

# 1. Clone the repository
git clone https://github.com/JoinDeeHub/ReStyleAI.git
cd ReStyleAI

# 2. Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Set up environment variables
cp .env.example .env
# Edit .env with your API keys

# 5. Run the app
streamlit run frontend/app.py

Docker Setup

docker-compose up --build

App will be available at http://localhost:8501

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🤝 Contributing

Contributions are welcome! Here's how:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature-name
3. Commit changes: git commit -m 'feat: add your feature'
4. Push to branch: git push origin feature/your-feature-name
5. Open a Pull Request

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📄 License

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

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🏆 Acknowledgements

• Hope AI – AI Hackathon 2025 organizers
• Unsplash – Sample fashion item images
• Streamlit – Rapid prototyping framework

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📬 Contact

Deepika Narendran | Lead AI/DevOps Engineer

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Made with 💚 for a sustainable future | © 2025 Deepika Narendran