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, ...
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