Design of Mask Compliance Recognition and Reminder System Based on YOLOv8
This paper investigates mask-wearing detection,designs and realizes a mask compliance recognition and reminder system based on YOLOv8.The study reports the current status and challenges of mask-wearing,and conducts training and integration work of the object detection model.Initially,it collects and annotates image datasets depicting different mask-wearing statuses,and uses YOLOv8 model to train for object detection,so as to recognize masks and their wearing states accurately.The system achieves real-time mask compliance recognition on video streams,which issues voice reminders upon detecting improper or absent mask-wearing to prompt individuals to adjust.Experimental results demonstrate the system has outstanding accuracy and real-time performance,and has potential for practical application in public spaces,which could enhance epidemic prevention effectiveness and mitigate transmission risks.
国家科技期刊平台
NSTL
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