We introduce PyTorchVideo, an open-source deep-learning library that provides a rich set of modular, efficient, and reproducible components for a variety of video understanding tasks, including classification, detection, self-supervised learning, and low-level processing. The library covers a full stack of video understanding tools including multimodal data loading, transformations, and models that reproduce state-of-the-art performance. PyTorchVideo further supports hardware acceleration that enables real-time inference on mobile devices. The library is based on PyTorch and can be used by any training framework; for example, PyTorchLightning, PySlowFast, or Classy Vision. PyTorchVideo is available at https://pytorchvideo.org/

翻译：我们引入了PyTorrchVideo(一个开放源码深层学习图书馆),它为各种视频理解任务,包括分类、检测、自我监督学习和低层次处理,提供了一套丰富的模块、高效和可复制的组件,包括分类、检测、自我监督学习和低层次处理。该图书馆涵盖全套视频理解工具,包括多式数据负荷、转换和复制最新性能的模型。PyTorrchVideo还支持硬件加速,使移动设备能够实时推断。该图书馆以PyTorch为基础,可以被任何培训框架使用;例如,PyTorchLightning、PySlowFast或Lassiary Vision。PyTorrchVideo可在https://pytorgvict.org/上查阅。