开源PyTorch库torchmil统一了深度多重实例学习的开发与评估流程。
torchmil: A PyTorch-based library for deep Multiple Instance Learning
- 基于PyTorch构建模块化框架，支持快速搭建MIL模型
- 提供标准数据格式与10+基准数据集，提升可复现性
- 适合初学者和研究者快速上手弱监督学习
多重实例学习（MIL）是一种强大的弱监督学习框架，特别适用于缺乏细粒度标注的场景。尽管深度MIL方法日益受到关注，但该领域缺乏标准化的工具用于模型开发、评估与对比，阻碍了可复现性和可及性。为此，我们提出了torchmil，一个基于PyTorch的开源Python库。torchmil提供统一、模块化且可扩展的框架，包含MIL模型的基础构建模块、标准化数据格式，以及经过整理的基准数据集与模型集合。库中还配备完整文档与教程，支持实践者与研究人员。torchmil旨在加速MIL领域的进展，并降低新用户的入门门槛。项目地址：https://torchmil.readthedocs.io。
原文摘要 · Abstract (English)
Multiple Instance Learning (MIL) is a powerful framework for weakly supervised learning, particularly useful when fine-grained annotations are unavailable. Despite growing interest in deep MIL methods, the field lacks standardized tools for model development, evaluation, and comparison, which hinders reproducibility and accessibility. To address this, we present torchmil, an open-source Python library built on PyTorch. torchmil offers a unified, modular, and extensible framework, featuring basic building blocks for MIL models, a standardized data format, and a curated collection of benchmark datasets and models. The library includes comprehensive documentation and tutorials to support both practitioners and researchers. torchmil aims to accelerate progress in MIL and lower the entry barrier for new users. Available at https://torchmil.readthedocs.io.
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