We introduce MarkDiffusion, an open-source Python toolkit for generative watermarking of latent diffusion models. It comprises three key components: a unified implementation framework for streamlined watermarking algorithm integrations and user-friendly interfaces; a mechanism visualization suite that intuitively showcases added and extracted watermark patterns to aid public understanding; and a comprehensive evaluation module offering standard implementations of 24 tools across three essential aspects - detectability, robustness, and output quality - plus 8 automated evaluation pipelines. Through MarkDiffusion, we seek to assist researchers, enhance public awareness and engagement in generative watermarking, and promote consensus while advancing research and applications.
@article{arxiv.2509.10569,
title = {MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models},
author = {Leyi Pan and Sheng Guan and Zheyu Fu and Luyang Si and Huan Wang and Zian Wang and Hanqian Li and Xuming Hu and Irwin King and Philip S. Yu and Aiwei Liu and Lijie Wen},
journal= {arXiv preprint arXiv:2509.10569},
year = {2025}
}