AI Mask Detection System

In this video, I demonstrate a high-performance AI Face Mask Tracker built using the latest YOLOv11 architecture. Unlike standard detection systems that "flicker" or lose track of people when they move, this project uses Advanced Object Tracking to remember each individual. Once the AI identifies a mask on a person, it locks their status as "Safe" for the entire video—even if they turn their head or walk behind others. Key Features: Persistent Tracking: Every person is assigned a unique ID to maintain a consistent safety status. Buffer Zone Technology: We use an expanded detection area to ensure accuracy during fast movement. Real-World Ready: Designed for high-traffic areas like hospitals, airports, and factories. High Accuracy: Powered by a custom-trained YOLOv11x model for the best possible results. This automation makes safety monitoring more reliable and reduces the need for constant manual supervision. Github: https://github.com/Labellerr CookBook: https://github.com/Labellerr/Hands-On-Learning-in-Computer-Vision/blob/main/fine-tune%20YOLO%20for%20various%20use%20cases/People_Mask.ipynb #FaceMaskDetection #YOLOv11 #ArtificialIntelligence #ComputerVision #ObjectTracking #MachineLearning #SmartSafety #AIProject #DeepLearning #PythonProgramming #PublicSafety #TechInnovation #RealTimeDetection #Automation #DataScience #AIVideoAnalysis #SafetyTech #ImageProcessing #YOLOv11x #CustomAI