Mask Detection Using YOLOv8

This project implements a real-time mask detection system that identifies individuals wearing or not wearing masks. If a person without a mask is detected, their picture is captured and saved in a designated folder. This solution is ideal for use in environments like hospitals, pharmacies, or public spaces to ensure compliance with mask-wearing policies.

Project Overview

• Model: YOLOv8
• Task: Detect mask-wearing individuals, save images of those without masks.
• Application: Useful for monitoring mask-wearing in public places.

Results and Evaluation

Several metrics were used to evaluate the model’s performance:

• F1 Score Curve:
• Precision-Recall Curve:
• Confusion Matrix:

These metrics demonstrate the model's ability to balance precision and recall when identifying individuals with and without masks.

Example of saved images:

Sample Output

Sample output from the model detecting individuals in a video stream is shown below:Output Video