Track and Count Objects Using YOLOv8
Blog post from Roboflow
The article by Piotr Skalski provides a comprehensive guide on using computer vision tools such as YOLOv8, ByteTrack, and Supervision to detect, track, and count moving objects, a common task in areas like traffic analysis and manufacturing automation. It offers a step-by-step approach to building a reusable script for these tasks, starting with object detection using YOLOv8, which supports easy installation and use through its SDK. For tracking, ByteTrack is recommended, with an unofficial package simplifying the installation process. The article emphasizes the integration of detection and tracking processes and introduces the Supervision library to streamline object counting and solve common problems encountered in computer vision projects. As a practical demonstration, the tutorial includes an example of counting candies on a conveyor belt, highlighting the adaptability of the approach with minimal code adjustments. The tutorial encourages users to deploy their models using the open-source Roboflow Inference Server while staying updated with Roboflow's ongoing projects.