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基于改进YOLO v5-pose的群养生猪体尺自动测量方法

刘刚 曾雪婷 刘晓文 李涛 丁向东 米阳

农业机械学报2025,Vol.56Issue(5):455-465,11.
农业机械学报2025,Vol.56Issue(5):455-465,11.DOI:10.6041/j.issn.1000-1298.2025.05.043

基于改进YOLO v5-pose的群养生猪体尺自动测量方法

Automatic Measurement Method of Body Size of Group-raised Pigs Based on Improved YOLO v5-pose

刘刚 1曾雪婷 1刘晓文 1李涛 2丁向东 3米阳1

作者信息

  • 1. 中国农业大学智慧农业系统集成研究教育部重点实验室,北京 100083||中国农业大学农业农村部农业信息获取技术重点实验室,北京 100083
  • 2. 河南丰源和普农牧股份有限公司,信阳 464000
  • 3. 中国农业大学动物科学技术学院,北京 100193||中国农业大学农业农村部动物遗传育种与繁殖重点实验室,北京 100193
  • 折叠

摘要

Abstract

Aiming at the problem that it is difficult to extract body measurement points efficiently and accurately in the automatic measurement of body size of group-raised pigs,an automatic measurement method of body size of group-raised pigs based on improved YOLO v5-pose was proposed.Firstly,the convolutional block attention module(CBAM)was integrated into the YOLO v5-pose backbone network to better capture the relevant features of the measurement points.Then the C3 traditional module of the Neck layer was replaced with the C3 Ghost lightweight module to reduce the number of model parameters and memory usage.Finally,the dynamic head(DyHead)target detection head was introduced in the Head layer to enhance the model's ability to represent the position of the measurement points.The results showed that the average accuracy of the improved model was 92.6%,the number of parameters was 6.890 × 106,and the memory usage was 14.1 MB.Compared with the original YOLO v5-pose model,the average accuracy was increased by 2.1 percentage points,and the number of parameters and memory usage were decreased by 2.380 × 105 and 0.4 MB,respectively.Compared with the current classic models YOLO v7-pose,YOLO v8-pose,real-time multi-person pose estimation based on mmpose(RTMPose)and CenterNet,this model had better recall rate and average precision and was more lightweight.Experiments were conducted on a dataset of 2 400 group-raised pigs images.The results showed that the average absolute errors of the body length,body width,hip width,body height and hip height measured by this method were 4.61 cm,5.87 cm,6.03 cm,0.49 cm and 0.46 cm,respectively,and the average relative errors were 2.69%,11.53%,12.29%,0.90%and 0.76%,respectively.In summary,the method improved the detection accuracy of body size measurement points,reduced the complexity of the model,and achieved more accurate body size measurement results,providing an effective technical means for the automatic measurement of body size of pigs in group-raising environments.

关键词

群养生猪/体尺测量/改进YOLO v5-pose/关键点检测/坐标变换

Key words

group-raised pig/body size measurement/improved YOLO v5-pose/key point detection/coordinate transformation

分类

信息技术与安全科学

引用本文复制引用

刘刚,曾雪婷,刘晓文,李涛,丁向东,米阳..基于改进YOLO v5-pose的群养生猪体尺自动测量方法[J].农业机械学报,2025,56(5):455-465,11.

基金项目

财政部和农业农村部:国家现代农业产业技术体系项目(CARS-35) (CARS-35)

农业机械学报

OA北大核心

1000-1298

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