💍 Virtual Try-On for Jewellery

🚀 Transforming Online Jewellery Shopping with AI & Augmented Reality ✨

Virtual Try-On for Jewellery 💎 is an AI-powered project that enables users to virtually try on earrings, necklaces, rings, and other jewellery pieces. This innovative solution enhances the online jewellery shopping experience, allowing customers to see how pieces look before purchasing. 🛍️

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📌 Table of Contents

• ✨ Overview
• 🎯 Features
• 🎮 Demo
• 🛠️ Technologies Used
• ⚙️ Installation & Setup
• 🚀 Usage
• 📚 YOLO Training Notebook
• 📊 Presentation
• 🔮 Future Enhancements
• 🤝 Contributing
• 🐟 License
• 📩 Contact

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✨ Overview

In the digital era, shopping for jewellery online can be challenging without seeing how it looks when worn. Virtual Try-On for Jewellery solves this problem by leveraging computer vision and deep learning. The project demonstrates:

• 🎯 Real-Time Jewellery Detection: Using a custom-trained YOLO model to detect jewellery pieces.
• 💻 Interactive Web Application: Allows users to upload their photos or use a webcam for a virtual try-on.
• 🔗 End-to-End AI Pipeline: Includes model training and an interactive web-based demonstration.

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🎯 Features

• ✅ Accurate Jewellery Detection: Uses YOLO for precise object detection.
• 🔧 User-Friendly Interface: Easy-to-use web app built with Python.
• ⚡ Real-Time Virtual Try-On: Overlay earrings, necklaces, rings, and more in real time.
• 🛠️ Modular Codebase: Clean and well-structured for future improvements.
• 🎮 Demonstrative Assets: GIFs and a presentation (Ppt.pdf) included.

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🎮 Demo

Check out a preview of how the Virtual Try-On works:

🎮 An animated demo showcasing the jewellery try-on feature.

Alternatively, check out this additional demonstration:

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🛠️ Technologies Used

• 🐍 Python: The core programming language.
• 🧫 YOLO: Detects and segments jewellery items.
• 📚 Jupyter Notebook: For training and fine-tuning the YOLO model (YOLO_TRAINING.ipynb).
• 🌐 Flask (or similar frameworks): Runs the web application (app.py).
• 📷 OpenCV: Image processing and real-time computer vision.

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⚙️ Installation & Setup

Follow these steps to get started:

1. 🔽 Clone the Repository:

   git clone https://github.com/pranjaykumar926/VIRTUAL-TRY-ON.git
   cd VIRTUAL-TRY-ON

2. 🔧 Create a Virtual Environment (Optional but Recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. 📦 Install Dependencies:

   pip install -r requirements.txt

4. 📝 Download Pre-trained Weights (if applicable):

   Follow the steps in YOLO_TRAINING.ipynb to obtain the model weights.

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🚀 Usage

To launch the web application demo:

1. ▶️ Run the Application:

   python app.py

2. 🌐 Open Your Browser:

   Navigate to http://localhost:5000 to try on jewellery virtually.

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📚 YOLO Training Notebook

The YOLO_TRAINING.ipynb notebook includes:

• 🛠️ Data preprocessing and augmentation
• 🎯 YOLO model training configuration
• 📊 Model evaluation steps

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📊 Presentation

For an in-depth project explanation, check out Ppt.pdf. 📂

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🔮 Future Enhancements

• 🎯 Improved Jewellery Detection: Train on more diverse jewellery datasets.
• 💆️ Augmented Reality (AR): Enhance the try-on experience with live tracking.
• 📱 Mobile Compatibility: Optimize for smartphones and tablets.
• 👕 Personalized Recommendations: AI-based jewellery recommendations.

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🤝 Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a new branch (feature/your-feature).
3. Commit your changes.
4. Open a pull request. ✅

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🐟 License

This project is currently not licensed. Contact the repository owner for permissions.

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📩 Contact

For inquiries or collaborations, reach out:

• GitHub: pranjaykumar926 🏰️
• 💌 Email: pranjaykumar926@gmail.com 📩

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✨ Revolutionizing jewellery shopping with AI-powered Virtual Try-On! 💍🚀