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Mask detection algorithm based on pyramid box

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DOI: 10.23977/jipta.2020.31002 | Downloads: 33 | Views: 2368


Yueyuan Liu 1, Jun Liu 1, Kai Chen 1


1 College of information science and technology, Chengdu University of Technology (College of network security, Oxford Brooks College), Chengdu, 610059

Corresponding Author

Yueyuan Liu


The novel coronavirus outbreak there was no parallel in history. In early 2020, the outbreak of an unprecedented coronavirus outbreak could effectively block the spread of the epidemic in the crowd in the public areas of the society if it could use artificial intelligence technology to detect people without masks in the crowded area. This paper introduces the face mask image detection algorithm, mainly based on the face recognition algorithm pyramid box to complete, describes how to use Baidu's paddlehub mask detection project, through the use of Python language to complete the mask detection of multiple images and get accurate detection data. The accuracy rate of face detection based on the pyramid box mask detection model is not satisfactory. It can also be deployed to the server or even the mobile terminal to achieve rapid real-time detection. With the resumption of work of enterprises, I believe that the face mask detection scheme can solve many pain points that need to be solved for many enterprises, communities and manufacturers.


PyramidBox algorithm, Deep learning, Convolutional neural network, Face mask image detection


Yueyuan Liu, Jun Liu and Kai Chen, Mask detection algorithm based on pyramid box. Journal of Image Processing Theory and Applications (2020) Vol. 3: 11-19. DOI:


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