Hawkeye Vision Model: AI-enabled Mask Wearing Detection

Project Introduction

In today’s world, one of the common issues that people are facing is to remain safe while being in crowded places. This problem was exacerbated when COVID-19 struck major cities in the world, forcing city dwellers to adapt to the new norm, such as wearing masks and frequently washing hands with soap.

Target Problems

In certain regions, mask wearing may be compulsory for crowded places such as workspaces or in public transits. Our project aims to help teams better enforce this requirement by identifying those who do not abide to the rules, and alert teams.


We are planning to implement the above concept by splitting it into 3 modules. The first module is to detect if a person/employee is wearing a mask or not from a webcam/video. The second module is to identify the person from the image and store the employee information such as employee id, name into a database or any file. Here we don’t have any employee records so we will use the image of celebrities found online, and map it with their name and store it in a database or file (.csv or .txt file).

Flow Diagram of Face Mask Detection
Architecture of Face Mask Detection
Nomask Detect (Image Source: Wikipedia)
The person has a mask (Image Source: Pinkvilla)
An email with attachment from Python

Alibaba Cloud Products Used

Technology highlights

We used Alibaba AI API and Alibaba ECS to build the Machine Learning models using python language to detect the face and face mask in an image and detect the name of the person using it.

Future Enhancement

We are planning to implement the above concept with different/multiple kind of datasets and models. We are also planning to add another module to determine the social distancing.

About the Team

Vivekanandhan M.Alibaba Cloud MVP — Artificial Intelligence

Original Source:

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