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Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking

In this video, we explore real-time traffic analysis using YOLOv8 and ByteTrack to detect and track vehicles on aerial images. Harnessing the power of Python and Supervision, we delve deep into assigning cars to specific entry zones and understanding their direction of movement. By visualizing their paths, we gain insights into traffic flow across bustling roundabouts. All resources, including our open-source project, are accessible via Roboflow's GitHub. Chapters: - 00:00 Introduction - 01:16 Vehicle detection on aerial images using YOLOv8 - 05:03 Tracking objects using ByteTrack and Supervision - 06:46 Defining entry and exit zones - 10:28 Assigning vehicles to specific entry zones - 16:22 Drawing the path of moving objects - 17:18 Analysing traffic flow - 22:23 Conclusions Resources: - 🌏 Roboflow: https://roboflow.com - 📚 Roboflow Notebooks Repository: https://github.com/roboflow/notebooks - 🌌 Roboflow Universe: https://universe.roboflow.com - 💻 Supervision GitHub repository: https://github.com/roboflow/supervision - 🖼️ Detecting Vehicles on Aerial Images dataset: https://universe.roboflow.com/roboflo... - 🎬 YOLOv8: How to Train for Object Detection on a Custom Dataset YouTube video:    • YOLOv8: How to Train for Object Detec...   - 🎬 Track & Count Objects using YOLOv8 ByteTrack & Supervision YouTube video:    • Track & Count Objects using YOLOv8 By...   🎬 Count People in Zone | Using YOLOv5, YOLOv8, and Detectron2 | Computer Vision YouTube video:    • Count People in Zone | Using YOLOv5, ...   Remember to like, comment, and subscribe for more content on AI, computer vision, and the latest technological breakthroughs! 🚀 Stay updated with the projects I'm working on at https://github.com/roboflow and https://github.com/SkalskiP! ⭐