Learn how to track and estimate the speed of vehicles using YOLO, ByteTrack, and Roboflow Inference. This comprehensive tutorial covers object detection, multi-object tracking, filtering detections, perspective transformation, speed estimation, visualization improvements, and more.
Use this knowledge to enhance traffic control systems, monitor road conditions, and gain valuable insights into vehicle behavior.
Chapters:
- 00:00 Intro
- 00:36 Object Detection
- 03:43 Multi-Object Tracking
- 05:11 Filtering Detections with Polygon Zone
- 06:39 Math Behind Perspective Transformation
- 14:35 Perspective Transformation in Code
- 16:46 Math Behind Speed Estimation
- 18:42 Speed Estimation in Code
- 21:29 Visualization Improvements
- 22:45 Final Results
Resources:
- Roboflow: roboflow.com
- 💻 Speed Estimation Open-Source Code: github.com/roboflow/supervisi...
- 📚 "How to Estimate Speed with Computer Vision" blog.roboflow.com/estimate-sp...
- 📓Colab Notebook: colab.research.google.com/git...
- ⭐ Supervision GitHub: github.com/roboflow/supervision
- ⭐ Inference GitHub: github.com/roboflow/inference
- 📚 “How to Track Objects” Supervision Docs: supervision.roboflow.com/how_...
- 📚 “Annotators” Supervision Docs: supervision.roboflow.com/anno...
- 🎬 “Track & Count Objects using YOLOv8 ByteTrack & Supervision” KZitem video: • Track & Count Objects ...
- 🎬 “Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking” KZitem video: • Traffic Analysis with ...
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Stay updated with the projects I'm working on at github.com/roboflow and github.com/SkalskiP! ⭐
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