Abstract:
Global pandemic COVID-19 circumstances emerged in an epidemic of dangerous disease in all
over the world. Masks play a crucial role in protecting the health of individuals against respiratory
diseases, as is one of the few precautions available for COVID-19 in the absence of immunization.
Wearing a face mask will also help prevent the spread of infection . But most of the people are not
wearing face masks in public places which increases the spread of viruses. Therefore, automated
and efficient face detection methods are essential for such enforcement. In this paper, a face mask
detection model has been presented which classifies the images as “with mask", “without mask”
and ”incorrect mask”. The model is trained and evaluated using the Kaggle dataset. The object
detection algorithm YOLOV5 based on deep learning is used for detecting mask. The experimental
results show that the algorithm proposed in this paper can effectively recognize face masks and
realize the effective monitoring of personnel .The experimentation mAP of YOLOV5 exhibited average of 85.7% which proves the effectiveness of face mask detection.
