MarkDiffusion Documentation

Welcome to MarkDiffusion

MarkDiffusion is an open-source Python toolkit for generative watermarking of latent diffusion models. As the use of diffusion-based generative models expands, ensuring the authenticity and origin of generated media becomes critical. MarkDiffusion simplifies the access, understanding, and assessment of watermarking technologies, making it accessible to both researchers and the broader community.

Key Features

🚀 Unified Implementation Framework

MarkDiffusion provides a modular architecture supporting eleven state-of-the-art generative image/video watermarking algorithms of LDMs.

📦 Comprehensive Algorithm Support

Currently implements 11 watermarking algorithms from two major categories:

• Pattern-based methods: Tree-Ring, Ring-ID, ROBIN, WIND, SFW

• Key-based methods: Gaussian-Shading, GaussMarker, PRC, SEAL, VideoShield, VideoMark

🔍 Visualization Solutions

The toolkit includes custom visualization tools that enable clear and insightful views into how different watermarking algorithms operate under various scenarios.

📊 Comprehensive Evaluation Module

With 31 evaluation tools covering detectability, robustness, and impact on output quality, MarkDiffusion provides comprehensive assessment capabilities with 6 automated evaluation pipelines.

A Quick Example of Generating and Detecting Watermarked Image via MarkDiffusion Toolkit

Documentation Contents