README.md

---
title: UniCalli
emoji: 🖌️
colorFrom: purple
colorTo: red
sdk: gradio
sdk_version: 5.44.0
app_file: app.py
pinned: false
license: cc-by-nc-nd-4.0
short_description: Chinese Calligraphy Generator
---

# 🖌️ UniCalli-Dev - Chinese Calligraphy Generator

**A Unified Diffusion Framework for Column-Level Generation and Recognition of Chinese Calligraphy**

## Links

- 🌐 **Project Page**: [https://envision-research.github.io/UniCalli/](https://envision-research.github.io/UniCalli/)
- 📄 **Paper**: [arXiv:2510.13745](https://arxiv.org/abs/2510.13745)
- 💻 **Code**: [GitHub](https://github.com/Envision-Research/UniCalli)
- 🎨 **Demo**: [https://huggingface.co/spaces/TSXu/UniCalli_Dev](https://huggingface.co/spaces/TSXu/UniCalli_Dev)
- 🤗 **Model**: [TSXu/Unicalli_Pro](https://huggingface.co/TSXu/Unicalli_Pro)

## Features

- **1-7 Chinese Characters**: Supports generating 1 to 7 Chinese characters in a column
- **Historical Masters**: 90+ calligraphers including 王羲之, 颜真卿, 赵佶/宋徽宗, etc.
- **Multiple Font Styles**: 楷 (Regular), 行 (Running), 草 (Cursive)
- **Interactive Session**: Generate multiple images in one GPU session
- **4-bit Quantization**: Runtime quantization for efficient inference on limited GPU memory

## Usage

1. Enter 1-7 Chinese characters
2. Select a calligrapher (or use synthetic style)
3. Choose a font style
4. Click "Start Generation"

## Citation

If you find UniCalli useful in your research, please cite our paper:

```bibtex
@article{xu2025unicalli,
  title={UniCalli: A Unified Diffusion Framework for Column-Level
         Generation and Recognition of Chinese Calligraphy},
  author={Xu, Tianshuo and Wang, Kai and Chen, Zhifei and Wu, Leyi
          and Wen, Tianshui and Chao, Fei and Chen, Ying-Cong},
  journal={arXiv preprint arXiv:2510.13745},
  year={2025}
}
```