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MiniProject_SemIV

Mask Detection System

Members:

  1. Umaima Yasir
  2. Ishika De
  3. Tanvi Deshpande

Domain:

UI/UX and Image Processing

Abstract:

After the new Coronavirus disease (COVID-19) case spread rapidly in Wuhan-China in December 2019, World Health Organization (WHO) confirmed that this is a dangerous virus that can be spread from humans to humans through droplets and airborne. As for prevention, wearing a face mask is essential while going outside or meeting with others. Moreover, developing the face mask detector is very crucial in this case.

Scope:

The idea is to create a mask detection system that can be employed at different organizations and can fit into door opening systems to check whether employees/clients/customers are wearing masks to prevent deadly viruses.

Aim:

To create a website that will check if the person is wearing a mask or not.

Target Audience:

This web application is aimed at helping organizations take precautions against covid 19 by tracking whether employees are wearing masks.

Tech Stack:

FrontEnd: Figma, HTML, CSS, Bootstrap BackEnd: Flask Libraries: OpenCV, Keras, tensorflow

References:

  1. Rapid Object Detection using a Boosted Cascade of Simple Features - Viola and Jones
  2. https://docs.opencv.org/3.4/db/d28/tutorial_cascade_classifier.html

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  • Jupyter Notebook 83.1%
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  • Other 1.4%