Yawning is a key factor in determining the state of driver fatigue,and considering that driving fatigue detection is susceptible to interference from the car driver's own conditions and external environment and poor real-time performance,this paper studies the driver's yawning and proposes a method for fatigue detection using the YOLOv5 network model.The processed YawDD open source dataset is firstly labeled by LabelImg,and then the samples are trained by deep learning model for several iterations to obtain the opti-mal weight data,and finally they are used on the test set for testing.The testing results show that the average recognition accuracy of the samples can reach more than 98%,so the used model has the ability to detect yawning behavior with high accuracy.
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