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Overview
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This course demonstrates how to build a computer vision system that detects, tracks, and counts objects in video. It uses YOLOv8, ByteTrack, and Supervision for vehicle and conveyor-candy examples, including a custom detection model.
Syllabus
Introduction
Setting up the Python environment for vehicle tracking
Using YOLOv8 for vehicle detection
Building custom inference pipeline with Supervision for a single image
Building custom inference pipeline with Supervision for a whole video
Tracking detections with ByteTrack
Counting objects crossing the line with Supervision
Training YOLOv8 Object Detection model on custom dataset
Detect, track, and count candies on the conveyor
Conclusion
Taught by
Roboflow