基于无人机直播联动的养殖动物视觉识别系统
Visual Recognition System for Farmed Animals Based on UAV Live Broadcast Linkage
叶扬 1徐精文 1徐鹏飞1
作者信息
- 1. 四川农业大学资源学院,成都 611134
- 折叠
摘要
对养殖动物的高效识别是畜牧养殖场开展各类精准养殖的基础,需要建设相应识别系统做支撑.本文所设计系统采用无人机直播联动方式进行样本采集和巡检识别,既能将视频实时上传到数据中心,又比无人机普通拍摄具有更少的小目标和遮挡问题发生,在此基础上,系统选用YOLOv7 算法模型进行动物行为和数量的识别,并对YOLOv7 算法模型优化和轻量化,以提升识别精度和降低系统负载,最后将识别数据输出到标准接口供各类精准养殖程序便捷调用.系统既适应养殖场的场景需求又兼顾系统的高效运行,能为养殖场实施各类精准养殖提供统一数据支持,降低重复设计成本和分散管理成本.
Abstract
The efficient recognition of farmed animals is the basis for animal husbandry farms to conduct all kinds of precision breeding.Therefore,it is essential to build a corresponding recognition system to support it.The system designed in this study uses the UAV live broadcast linkage method for sample collection and cruise recognition.This method allows real-time video uploading to the data center and addresses issues such as fewer small targets and occlusion problems compared to ordinary UAV shooting.On this basis,the study selects the YOLOv7 algorithm model to recognize animal behavior and quantity.Furthermore,it optimizes and lightweights the YOLOv7 algorithm model to enhance the recognition accuracy and reduce the system load.Finally,the recognition data is output to the standard interface for convenient calls by various precision breeding programs.The system not only adapts to the scene needs of the farm but also takes into account the efficient operation of the system.It can provide unified data support for implementing diverse precision breeding in the farm and reduce the cost of repeated design and decentralized management.
关键词
无人机直播/养殖动物/视觉识别/YOLOv7/轻量化Key words
UAV live broadcast/farmed animal/visual recognition/YOLOv7/lightweight引用本文复制引用
基金项目
国家重点研发计划(2021YFE0102000)
中国电信-四川农业大学智慧农业创新实验室揭榜挂帅项目()
国家级大学生创新训练项目(202310626023)
出版年
2024
NETL
NSTL
万方数据