In this paper, we introduce PhotoHolmes, an open-source Python library designed to easily run and benchmark forgery detection methods on digital images. The library includes implementations of popular and state-of-the-art methods, dataset integration tools, and evaluation metrics. Utilizing the Benchmark tool in PhotoHolmes, users can effortlessly compare various methods. This facilitates an accurate and reproducible comparison between their own methods and those in the existing literature. Furthermore, PhotoHolmes includes a command-line interface (CLI) to easily run the methods implemented in the library on any suspicious image. As such, image forgery methods become more accessible to the community. The library has been built with extensibility and modularity in mind, which makes adding new methods, datasets and metrics to the library a straightforward process. The source code is available at https://github.com/photoholmes/photoholmes.

翻译：本文介绍PhotoHolmes，一个旨在便捷运行和基准测试数字图像伪造检测方法的开源Python库。该库包含流行及前沿方法的实现、数据集集成工具以及评估指标。通过使用PhotoHolmes中的基准测试工具，用户可以轻松比较不同方法，从而在自有方法与现有文献方法之间实现精确且可复现的对比。此外，PhotoHolmes提供命令行界面（CLI），便于在任何可疑图像上直接运行库中已实现的方法。这使得图像伪造检测技术更易于被社区广泛使用。该库在设计上注重可扩展性与模块化，因此添加新方法、数据集和指标至库中的过程十分简便。源代码发布于https://github.com/photoholmes/photoholmes。