This paper introduces an open source platform for rapid development of computer vision applications. 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 iteration of multiple task specific datasets in parallel. We make it an open platform by abstracting the development process into core states and operations, and design open APIs to integrate third party tools 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 history, 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 from custom real world computer vision applications.
翻译:本文介绍了一个用于快速开发计算机愿景应用程序的开放源码平台。 该平台将高效数据开发置于机器学习开发过程的中心,整合了积极的学习方法、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复制。 我们通过将开发进程纳入核心状态和操作,将该平台建成一个开放平台,并设计开放的API,将第三方工具整合为操作的实施工具。这一开放设计降低了ML团队使用现有工具的开发成本和采用成本。 与此同时,该平台支持记录项目开发历史,通过共享成功项目,进一步提高类似任务的模型生产效率。 该平台是开放源,内部已经用于满足定制真实世界计算机愿景应用程序不断增长的需求。