We introduce the Unity Perception package which aims to simplify and accelerate the process of generating synthetic datasets for computer vision tasks by offering an easy-to-use and highly customizable toolset. This open-source package extends the Unity Editor and engine components to generate perfectly annotated examples for several common computer vision tasks. Additionally, it offers an extensible Randomization framework that lets the user quickly construct and configure randomized simulation parameters in order to introduce variation into the generated datasets. We provide an overview of the provided tools and how they work, and demonstrate the value of the generated synthetic datasets by training a 2D object detection model. The model trained with mostly synthetic data outperforms the model trained using only real data.

翻译：我们引入“团结感知”软件包,目的是通过提供易于使用和高度定制的工具,简化和加快为计算机视觉任务生成合成数据集的进程。这个开放源码软件包扩展了“团结编辑”和引擎组件,为若干共同的计算机视觉任务生成了完全附加说明的实例。此外,它提供了一个可扩展的随机化框架,使用户能够快速构建和配置随机模拟参数,以对生成的数据集进行变异。我们提供了所提供的工具及其工作方式的概览,并通过培训2D对象探测模型展示了生成的合成数据集的价值。经过培训的模型大多是合成数据,比仅使用真实数据所培训的模式要强。