Deployment Yolov8 Model for Face Mask Detection Based on Amazon Web Service

Since the current pandemic of covid 9, there have been many concerns expressed regarding public health and safety, which has led to the widespread adoption of protective measures such wearing face masks. To ensure adherence to safety regulations, the development of reliable and effective solutions for automatic mask detection is of the utmost importance. In this paper, we use Amazon SageMaker to build and train the yolov8 model, testing and validation were performed on the MJFR dataset which is collected by us. The evaluation of the model’s performance is carried out by employing the following metrics: precision (P), recall (R), mean average precision (mAP@.5), and (mAP@.5:.95). The deployment of face mask identification system using the YOLOv8 object detection algorithm and integration into a Flask web application running on an Amazon EC2 instance is thoroughly studied in this work.