Count People in Zone - Using YOLOv5, YOLOv8, and Detectron2 - Computer Vision

Learn to detect and count objects within polygon zones using YOLOv5, YOLOv8, and Detectron2 in this comprehensive 21-minute tutorial. Explore three real-world examples: detecting customers in a shopping mall, people at a subway station edge, and counting individuals in a market square. Master object detection techniques using the Supervision library to build advanced analytics. Follow along with the provided Jupyter Notebook as the tutorial guides you step-by-step through setting up the Python environment, implementing YOLOv8 and Detectron2 examples, and creating an advanced YOLOv5 solution. Enhance your computer vision skills and unlock powerful object detection capabilities for various applications.

Introduction
Setting up the Python environment
Simple YOLOv8 Shopping Mall Example
Simple Detectron2 Subway Example
Advanced YOLOv5 Market Square Example
Conclusion