Face Mask Detector with Deep Learning and MobileNetV2
Keywords:
OpenCV, Tenser Flow, Keras, Computer VisionAbstract
The corona virus COVID-19 pandemic is causing a global health crisis so the effective protection method is wearing a face mask in public areas according to the World Health Organization (WHO). The COVID-19 pandemic forced governments across the world to impose lockdowns to prevent virus transmissions. Reports indicate that wearing facemasks while at work clearly reduces the risk of transmission. An efficient and economic approach of using AI to create a safe environment in a manufacturing setup. A hybrid model using deep and classical machine learning for face mask detection will be presented. A face mask detection dataset consists of with mask and without mask images, we are going to use OpenCV to do real-time face detection from a live stream via our webcam. We will use the dataset to build a COVID-19 face mask detector with computer vision using Python, OpenCV, and Tensor Flow and Keras. Our goal is to identify whether the person on image/video stream is wearing a face mask or not with the help of computer vision and deep learning.
References
- P. A. Rota, M. S. Oberste, S. S. Monroe, W. A. Nix, R. Campagnoli, J. P. Icenogle, S. Penaranda, B. Bankamp,K. Maher, M.-h. Chenet al., “Characterization of a novel coronavirus associated with severe acute respiratorysyndrome,”science, vol. 300, no. 5624, pp. 1394–1399, 2003.
- Z. A. Memish, A. I. Zumla, R. F. Al-Hakeem, A. A. AlRabeeah, and G. M. Stephens, “Family cluster of middleeast respiratory syndrome coronavirus infections,”New England Journal of Medicine, vol. 368, no. 26, pp.2487–2494, 2013.
- Y. Liu, A. A. Gayle, A. Wilder-Smith, and J. Rocklöv, “The reproductive number of covid-19 is higher comparedto sars coronavirus,”Journal of travel medicine, 2020.
- Y. Fang, Y. Nie, and M. Penny, “Transmission dynamics of the covid-19 outbreak and effectiveness of governmentinterventions: A datadriven analysis,”Journal of medical virology, vol. 92, no. 6, pp. 645–659, 2020.
- N. H. Leung, D. K. Chu, E. Y. Shiu, K.-H. Chan, J. J. McDevitt, B. J. Hau, H.-L. Yen, Y. Li, D. KM, J. Ipet al.,“Respiratory virus shedding in exhaled breath and efficacy of face masks.”
- S. Feng, C. Shen, N. Xia, W. Song, M. Fan, and B. J. Cowling, “Rational use of face masks in the covid19pandemic,”The Lancet Respiratory Medicine, 2020.
- Z. Wang, G. Wang, B. Huang, Z. Xiong, Q. Hong, H. Wu, P. Yi, K. Jiang, N. Wang, Y. Peiet al., “Masked facerecognition dataset and application,”arXiv preprint arXiv:2003.09093, 2020.[10]Z.-Q. Zhao, P. Zheng, S.-t. Xu, and X. Wu, “Object detection with deep learning: A review,”IEEE transactions on neural networks and learning systems, vol. 30, no. 11, pp. 3212–3232, 2019.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRSET
This work is licensed under a Creative Commons Attribution 4.0 International License.