PhotoHolmes让图像伪造检测更简单，支持一键对比和测试新方法。
PhotoHolmes: a Python library for forgery detection in digital images
- 提供多种主流伪造检测方法的代码实现
- 支持快速比较不同方法在真实数据上的表现
- 开源可扩展，适合研究人员和安全从业者使用
本文介绍 PhotoHolmes，一个开源的 Python 库，旨在简化数字图像伪造检测方法的运行与基准测试。该库集成了多种流行及前沿的检测方法、数据集接入工具和评估指标。通过内置的 Benchmark 工具，用户可轻松对比不同方法的表现，实现与其自身方法或已有文献结果的准确、可复现比较。此外，PhotoHolmes 提供命令行接口（CLI），可对任意可疑图像快速运行库中实现的方法。整个库设计注重可扩展性与模块化，新增方法、数据集和评估指标的操作简便。源代码已公开于 https://github.com/photoholmes/photoholmes。
原文摘要 · Abstract (English)
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.
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