Development of Hospital Mask Wearing Detection System Based on Deep Learning
According to the characteristics of large flow of people,short detection time and many interfering factors,the design of hospital mask wearing detection system is studied.The detection data set of hospital mask wearing is made,and the position and category of mask wearing are marked by using the LabelImg tool.In order to reduce the influence of illumination on the detection performance,the image is whitened.The YOLOv5 model is selected for detection,the number of iterations is set to different values,and the model is trained and the evaluation index values are compared to find the appropriate number of iterations.The display page based on Flask and ECharts is constructed to realize real-time detection of hospital video surveillance pictures.It reduces false detection and missed detection,and saves manpower and material resources.
Deep Learningmask wearingtarget detectionFlask frame
国家科技期刊平台
NSTL
万方数据
