Lin Du, Manyu Wang, Zongkai Yang, Ke Zhang, Yanhan Li, Zhihua Chen
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引用次数: 0
摘要
2019年爆发了COVID-19(2019冠状病毒病)，为了阻止疫情的蔓延，戴口罩是非常关键的一环。利用深度学习技术进行口罩佩戴检测，可以提高检测精度，减少人力物力。本文使用YOLOv5(You Only Look Once version 5)模型进行口罩佩戴检测。在实验验证阶段，分别采用不同的方法对YOLOv5的性能进行了测试。最后，发现使用标签平滑训练方法的检测性能最优，Mean Average Precision (mAP)可以达到0.9252。
A method of mask wearing state detection based on YOLOv5
The COVID-19 (Corona Virus Disease 2019) outbroke in 2019, and in order to stop the epidemic, wearing masks is a very critical part. The use of deep learning technology for mask wearing detection can improve the detection accuracy and reduce human and material resources. In this paper, the YOLOv5(You Only Look Once version 5) model is used for mask wearing detection. In the experimental validation phase, the performance of YOLOv5 is tested by using different methods, respectively. Finally, it is found that the detection performance is optimal with the training method of labelsmoothing, and the Mean Average Precision (mAP) can reach 0.9252.
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