README.md

metadata

title: Dermatology AI Assistant
emoji: 🩺
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
license: apache-2.0
short_description: AI-powered dermatology analysis using Qwen2.5-VL-3B

🩺 Dermatology AI Assistant

An AI-powered dermatology analysis tool built with Qwen2.5-VL-3B, fine-tuned specifically for skin condition analysis and medical image understanding.

🚀 Features

• Advanced Vision-Language Model: Powered by Qwen2.5-VL-3B fine-tuned for dermatology
• Interactive Analysis: Upload skin images and get detailed AI analysis
• Customizable Questions: Ask specific questions about skin conditions
• Medical-Grade Interface: Clean, professional interface designed for healthcare use
• ZeroGPU Support: Optimized for Hugging Face Spaces ZeroGPU

🏥 Medical Disclaimer

⚠️ IMPORTANT: This AI assistant is for educational and research purposes only. It should not be used as a substitute for professional medical advice, diagnosis, or treatment. Always consult with a qualified healthcare provider for medical concerns.

🛠️ Technical Details

Model Information

• Base Model: Qwen2.5-VL-3B-Instruct
• Fine-tuning Method: LoRA (Low-Rank Adaptation)
• Training Data: 1,000 dermatology images with conversations
• Validation Data: 200 dermatology images
• Domain: Dermatology and skin condition analysis

Training Configuration

• LoRA Rank: 64
• LoRA Alpha: 64
• LoRA Dropout: 0.05
• Learning Rate: 1e-4
• Batch Size: 16
• Epochs: 1
• Gradient Accumulation: 8
• GPU: A100 80GB

📖 Usage

1. Upload Image: Click on the image upload area and select a skin condition image
2. Ask Questions: Use the default question or customize your own
3. Get Analysis: Click "Analyze Skin Condition" to get AI-powered insights
4. Review Results: Read the detailed analysis in the output area

Example Questions

• "What type of skin condition is this?"
• "Describe the characteristics of this lesion."
• "What are the potential causes of this skin issue?"
• "What should I know about this skin condition?"

🔧 Local Development

Prerequisites

• Python 3.8+
• CUDA-compatible GPU (recommended)
• 8GB+ VRAM

Installation

# Clone the repository
git clone https://huggingface.co/spaces/ColdSlim/Dermatology-AI-Assistant
cd Dermatology-AI-Assistant

# Install dependencies
pip install -r requirements.txt

# Run the application
python app.py

📊 Model Performance

• Training Time: ~10-15 minutes on A100 80GB
• Inference Speed: ~2-5 seconds per image
• Memory Usage: ~20-30GB VRAM
• Model Size: ~3B parameters

🤝 Contributing

Contributions are welcome! Please feel free to submit issues, feature requests, or pull requests.

📄 License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.

🙏 Acknowledgments

• Qwen Team for the base model
• Hugging Face for the platform and infrastructure
• Medical professionals who provided domain expertise

📞 Contact

For questions or support, please open an issue in this repository.

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Remember: This tool is for educational purposes only. Always consult healthcare professionals for medical advice.