Let's build together an application to track and count objects using Computer Vision. We used YOLOv8 for detection, ByteTrack for tracking, and the latest python library from Roboflow - Supervision for object counting.

Chapters:

0:00 Introduction
1:28 Setting up the Python environment for vehicle tracking
5:28 Using YOLOv8 for vehicle detection
6:27 Building custom inference pipeline with Supervision for a single image
12:37 Building custom inference pipeline with Supervision for a whole video
15:46 Tracking detections with ByteTrack
17:40 Counting objects crossing the line with Supervision
19:29 Training YOLOv8 Object Detection model on custom dataset
22:50 Detect, track, and count candies on the conveyor
25:50 Conclusion

Resources:

🌏 Roboflow: [ Ссылка ]

🌌 Roboflow Universe: [ Ссылка ]

⭐ Supervision repository: [ Ссылка ]

📝 Track and Count with YOLOv8 Blogpost: [ Ссылка ]

📓 Track and Count Vehicles with YOLOv8 + ByteTRACK + Supervision Notebook: [ Ссылка ]
📓How to Train YOLOv8 Object Detection on a Custom Dataset Notebook: [ Ссылка ]

🎬 Count People in Zone | 3 Models: YOLOv5, YOLOv8 and Detectron2: [ Ссылка ]
🎬 YOLOv8 Object Counting in Real-time with Webcam, OpenCV and Supervision: [ Ссылка ]
🎬 YOLOv8: How to Train for Object Detection on a Custom Dataset: [ Ссылка ]
🎬 Instance Segmentation in 12 minutes with YOLOv8 and Python: [ Ссылка ]

📓 Learn more about YOLOv8 and other Computer Vision models with Roboflow Notebooks: [ Ссылка ]

Stay updated with the projects I'm working on at [ Ссылка ] and [ Ссылка ]! ⭐

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