Computer vision (CV), a non-intrusive and cost-effective technology, has furthered the development of precision livestock farming by enabling optimized decision-making through timely and individualized animal care. The availability of affordable two- and three-dimensional camera sensors, combined with various machine learning and deep learning algorithms, has provided a valuable opportunity to improve livestock production systems. However, despite the availability of various CV tools in the public domain, applying these tools to animal data can be challenging, often requiring users to have programming and data analysis skills, as well as access to computing resources. Moreover, the rapid expansion of precision livestock farming is creating a growing need to educate and train animal science students in CV. This presents educators with the challenge of efficiently demonstrating the complex algorithms involved in CV. Thus, the objective of this study was to develop ShinyAnimalCV, an open-source cloud-based web application. This application provides a user-friendly interface for performing CV tasks, including object segmentation, detection, three-dimensional surface visualization, and extraction of two- and three-dimensional morphological features. Nine pre-trained CV models using top-view animal data are included in the application. ShinyAnimalCV has been deployed online using cloud computing platforms. The source code of ShinyAnimalCV is available on GitHub, along with detailed documentation on training CV models using custom data and deploying ShinyAnimalCV locally to allow users to fully leverage the capabilities of the application. ShinyAnimalCV can contribute to CV research and teaching in the animal science community.

翻译：计算机视觉（CV）作为一种非侵入性且经济高效的技术，通过实现及时、个性化的动物护理以优化决策，推动了精准畜牧业的发展。低成本二维与三维摄像头传感器，结合各类机器学习与深度学习算法，为改善畜牧生产系统提供了宝贵机遇。然而，尽管公共领域已有多种CV工具可用，但将这些工具应用于动物数据仍具有挑战性，通常要求用户具备编程与数据分析技能，并拥有计算资源访问权限。此外，精准畜牧业的快速扩展导致对动物科学专业学生进行CV教育与培训的需求日益增长，这对教育工作者高效演示CV中涉及的复杂算法提出了挑战。因此，本研究旨在开发ShinyAnimalCV——一款开源云平台网络应用程序。该应用程序提供用户友好界面，可执行目标分割、检测、三维表面可视化及二维与三维形态特征提取等CV任务。其内置九个基于俯视动物数据的预训练CV模型。ShinyAnimalCV已通过云计算平台完成在线部署，其源代码发布于GitHub平台，并附带使用自定义数据训练CV模型及本地部署ShinyAnimalCV的详细文档，以便用户充分利用该应用程序功能。ShinyAnimalCV可助力动物科学领域的CV研究与教学。