RealTime Ai Face Mask Detection Using Python & Opencv

Real-Time Ai Face Mask Detection Using Python & Opencv
Published 5/2025
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz

Real-Time Mask Detection: How AI Helps Enforce Safety Measures with Python & Computer Vision.

What you’ll learn

Understand the fundamentals of face mask detection using deep learning models and its role in ensuring public health safety through automated monitoring.

Set up a Python development environment with essential libraries, including OpenCV for image processing and Tkinter for real-time video streaming on the web.

Explore the YOLOv11 model, optimized for accurate and efficient face mask detection in real-time video streams.

Utilize a Roboflow dataset to train and evaluate the model, ensuring diverse and high-quality image data for improved detection accuracy.

Learn preprocessing techniques, such as image normalization, resizing, and augmentation, to enhance model performance and ensure compatibility with YOLOv11.

Implement real-time visualization by annotating video frames with bounding boxes, class labels, and confidence scores for face mask detection.

Develop a user-friendly application using Tkinter to display live video feeds with real-time mask detection capabilities.

Optimize model deployment for real-time use, ensuring low latency in video processing and accurate detection of masked and unmasked individuals.

Apply the developed system in real-world scenarios such as public spaces, hospitals, airports, and workplaces to enhance safety and compliance monitoring.

Requirements

Basic understanding of Python programming (helpful but not mandatory).

A laptop or desktop computer with internet access [Windows OS with Minimum 4GB of RAM).
No prior knowledge of AI or Machine Learning is required-this course is beginner-friendly.

Enthusiasm to learn and build practical projects using AI and IoT tools.

Description

Overview

Section 1: Introduction to Face Mask Detection and Recognition

Lecture 1 Course Introduction and Features

Section 2: Environment Setup for Python Development

Lecture 2 Installing Python

Lecture 3 VS Code Setup for Python Development

Section 3: Face Mask Detection System Project Overview

Lecture 4 Face Mask Detection

Section 4: Google Drive Mount

Lecture 5 Google Drive Mount

Section 5: Face Mask Detection Dataset Download

Lecture 6 Face Mask Detection Dataset Download

Section 6: Dataset Visualization

Lecture 7 Dataset Visualization

Section 7: Ultralytics Installation & Setting Up YOLOv11 for Mask Detection

Lecture 8 Ultralytics Installation & Setting Up YOLOv11 for Mask Detection

Section 8: YOLOv11 Model Training for Mask Detection

Lecture 9 YOLOv11 Model Training for Mask Detection

Section 9: Packages Explanation

Lecture 10 Packages Explanation

Section 10: Model Inference Code Explanation

Lecture 11 Model Inference Code Explanation

Section 11: Tkinter Implementation

Lecture 12 Tkinter Implementation

Section 12: Code Execution

Lecture 13 Code Execution

Section 13: Wrapping Up

Lecture 14 Course Wrap-Up