Real-Time Face Mask Detection OpenCV Python

Real-Time Face Mask Detection OpenCV Python – During the COVID-19 pandemic, WHO mandated the use of masks to guard against the deadly virus. With regards to the mandate, we came up with a machine learning project called Real-time Face Mask Detector with Python in this tutorial.

Base on this, we will create a real-time system that can tell whether or not the person on the webcam is wearing a mask. We will use Keras and OpenCV to train the face mask detector model.

Importance of Real-Time Face Mask Detection Python

When talking, breathing, or coughing, face coverings reduce the volume and travel distance of exhaled droplets. A face mask with no vents or holes will filter out virus-carrying particles from inhaled and exhaled air, lowering the risk of infection.

Real-Time Face Mask Detection Python Beneficiaries

  • Schools
  • Malls
  • Restaurant
  • Stores
  • Public Places
  • Hospitals and ETC.

Real-Time Face Mask Detection OpenCV Python: Project Details and Technology

Project Name:Real-Time Face Mask Detection OpenCV Python With Source Code
AbstractReal-Time Face Mask Detection OpenCV Python – Face Mask Detection Platform uses Artificial Network to recognize is a user is not wearing a mask.
Language/s Used:Python Deep Learning
Python version (Recommended):3.8/3.9
Database:None
Type:Desktop Application
Developer:Source Code Hero
Updates:0
Real-Time Face Mask Detector With Python, OpenCV, Keras– Project Information

Real-Time Face Mask Detection OpenCV Python

This 2022 Real-Time Face Mask Detection OpenCV Python was developed using Python OpenCV and Keras and This both a Deep Learning Machine Project.

We used Python, Keras, and OpenCV to create a deep learning model for face mask identification in this project. The face mask detector model was created to determine whether or not a person is wearing a mask. We used Keras with network architecture to train the model.

Real-Time Face Mask Detection Python: Major Functionalities

  • Display Real-Time Camera – For this functionality the system will display a real-time camera.
  • Detecting Faces – For this functionality the real-time camera detect faces.
  • Detecting Wearing Mask or Not – For this functionality the system detects if the person wearing face mask or not.

This OpenCV Project In Python also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.

By the way, if you are new to python programming and you don’t have any idea what Python IDE to use, I have here a list of Best Python IDE for Windows, Linux, Mac OS for you. Additionally, I also have here How to Download and Install Latest Version of Python on Windows.

To start executing a Real-Time Face Mask Detection Python With Source Code, make sure that you have installed Python in your computer.

Real-Time Face Mask Detection OpenCV Python : Steps on how to run the project

Time needed: 5 minutes.

These are the steps on how to run Real-Time Face Mask Detection OpenCV Python

  1. Download Source Code

    First, download the provided source code below.
    face mask detetor download source code

  2. Extract File

    Next, after the download finished extract the zip file.
    facemask detector extract file

  3. Open CMD

    Next, open the folder and type CMD to the file directory.
    face mask detector open cmd

  4. Run Project

    last, run project by typing py main.py
    face mask detector run project

Download Source Code below

Summary

In this project, we have developed a deep learning model for face mask detection using Python, Keras, and OpenCV. We developed the face mask detector model for detecting whether person is wearing a mask or not. We have trained the model using Keras with network architecture. Training the model is the first part of this project and testing using webcam using OpenCV is the second part.

Inquiries

If you have any questions or suggestions about Real-Time Face Mask Detector With Python, OpenCV, Keras With Source Code, please feel free to leave a comment below.

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