FrOoDo is an easy-to-use and flexible framework for Out-of-Distribution detection tasks in digital pathology. It can be used with PyTorch classification and segmentation models, and its modular design allows for easy extension. The goal is to automate the task of OoD Evaluation such that research can focus on the main goal of either designing new models, new methods or evaluating a new dataset. The code can be found at https://github.com/MECLabTUDA/FrOoDo.

翻译：FRODo是数字病理学中传播外检测任务的一个容易使用的灵活框架,可用于PyTorch分类和分解模型,模块设计便于扩展,目的是将OOOD评价的任务自动化,使研究能够侧重于设计新模型、新方法或评价新数据集的主要目标。该代码可在https://github.com/MECLABTUDA/FrOoDo查阅。