🌟 Mozhi - Intelligent Calligraphy Education Evaluation System 🖋️🎨

Welcome to Mozhi, the future of calligraphy education! 🎉 This project revolutionizes traditional Chinese calligraphy teaching with cutting-edge AI and a sleek, user-friendly interface. If you think mastering calligraphy takes years, think again—Mozhi brings that learning curve way down! 🚀

🚀 About the Project

Calligraphy, a treasured gem in Chinese culture, faces a modern challenge—lack of resources, objective scoring, and personalized feedback. But we’ve got this covered. 💡 With Mozhi, learners get instant feedback on their strokes, structures, and even aesthetics!

What Makes Mozhi Special?

• 🖥️ Frontend (Vue): A smooth and dynamic user experience, bringing calligraphy practice to your screen with real-time feedback.
• ⚙️ Backend (FastAPI): The backbone of Mozhi, handling user data, evaluations, and recommendations at lightning speed.
• 🧠 Algorithms (Torch, GNN, RL): We've incorporated deep learning with a Siamese Regression Network (SRN) for structure scoring, and Stroke-Seg for detailed stroke analysis. Plus, there's personalized learning routes powered by DQN and knowledge graph-enhanced ChatGPT guidance!

Core Features 🔑

1. Charm Framework: A robust scoring system that evaluates the overall shape and individual stroke details of calligraphy.
   • Vision Module: Handles large-scale aesthetic features like balance and symmetry.
   • Rule Module: Provides detailed stroke analysis with the help of a cutting-edge Unet-Transformer hybrid model.
2. Knowledge Graph & ChatGPT: Fine-tuned AI to give learners helpful feedback and direction, ensuring continual improvement.
3. Reinforcement Learning: Adaptive learning paths based on individual progress, giving each user a unique experience tailored to their skills.

Mozhi has been rigorously tested with 99.6% stroke segmentation accuracy and delivers superior performance over previous methods in aesthetic evaluations. It’s fast, reliable, and, most importantly, easy to use! 🚀

🎨 How to Get Started

1. Clone the repo:

   git clone https://github.com/CSU-YKF/mozhi.git

2. Install dependencies:

   cd mozhi
   pip install -r requirements.txt

3. Run the backend:

   uvicorn main:app --reload

4. Run the frontend:

   cd web
   npm install
   npm run serve

5. Start practicing your calligraphy skills and receive instant AI feedback! 🖌️

🏆 Achievements

Mozhi proudly secured First Place 🥇 in the National Finals of the "Chinese Robotics and Artificial Intelligence Competition - AI Innovation Track"! 💻✨

Our system was praised for:

• Precision in stroke segmentation
• Aesthetic scoring accuracy
• Personalized learning paths
• Seamless integration of AI into traditional art 🎉

🙌 Acknowledgements

This project wouldn’t have been possible without the dedication of our amazing team:

• @Rvosuke (白泽阳) - Project Lead & AI Specialist 💻
• @LambertRao (饶逸石) - Backend Engineer 🔧
• @August-snoopy (丁御峰) - Frontend Developer 🎨
• @kyliancc (朱若朴) - Optimization and Future Enhancements 🌱
• @wosida (李东阳) - Algorithm Contributor 🧠

A huge thanks to everyone for their hard work and support! 🚀

📅 Future Plans

The journey doesn’t stop here! Next steps for Mozhi include:

• Further optimization of the personalized recommendation engine.
• Expanding the knowledge graph for more detailed feedback.
• Enhancing the user interface for a more engaging learning experience.

Stay tuned for updates and new features! 👀