The Real-Time Face Mask Detection System with OpenCV and Python was developed using Python and OpenCV during the COVID-19 pandemic, when the World Health Organization (WHO) emphasized the importance of wearing masks to protect against the virus.
In this tutorial, we will build a machine learning project — a real-time face mask detector using Python. The system will be able to detect, through a webcam, whether a person is wearing a mask or not.
To achieve this, we will train a face mask detection model with OpenCV and integrate it into a real-time application.
This project is an excellent starting point for beginners who want to apply their knowledge of Python, machine learning, and computer vision.
It provides hands-on experience and helps learners gain confidence and expertise in building practical AI applications.
By the way, if you are new to Python programming and are unsure which Python IDE to use, I have prepared a list of the best Python IDEs for Windows, Linux, and macOS to help you choose the one that suits your needs.
I also created a guide on how to download and install the latest version of Python on Windows.
Before you start working on the Real-Time Face Mask Detection Project with OpenCV and Python (including source code), make sure that Python is properly installed on your computer.
These are the steps on how to run Real-Time Face Mask Detection OpenCV Python With Source Code.
- Download the given source code.
First, download the given source code and unzip the source code.
- Import the project to your PyCharm IDE.
Next, import the source code you’ve downloaded to your PyCharm IDE.
- Run the project.
Lastly, run the project with the command "py main.py"
from tensorflow.keras.applications.mobilenet_v2 import preprocess_input
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.models import load_model
from imutils.video import VideoStream
import numpy as np
import imutils
import time
import cv2
import os