This paper introduces an open source platform to support the rapid development of computer vision applications at scale. The platform puts the efficient data development at the center of the machine learning development process, integrates active learning methods, data and model version control, and uses concepts such as projects to enable fast iterations of multiple task specific datasets in parallel. This platform abstracts the development process into core states and operations, and integrates third party tools via open APIs as implementations of the operations. This open design reduces the development cost and adoption cost for ML teams with existing tools. At the same time, the platform supports recording project development histories, through which successful projects can be shared to further boost model production efficiency on similar tasks. The platform is open source and is already used internally to meet the increasing demand for different real world computer vision applications.
翻译:本文介绍一个开放源码平台,以支持大规模计算机愿景应用的快速开发。该平台将高效数据开发置于机器学习开发过程的中心,整合积极的学习方法、数据和模式版本控制,并使用项目等概念,使多重任务特定数据集能够同步快速迭代。该平台将开发进程摘要纳入核心国家和业务,并通过开放式API将第三方工具整合为操作的实施。这一开放设计降低了现有工具对ML团队的开发成本和采用成本。同时,该平台支持记录项目开发历史,通过这些成功项目共享成功项目,进一步提高类似任务的模式生产效率。该平台是开放源,内部已经用于满足对不同真实世界计算机愿景应用程序日益增长的需求。