How to Count Objects in a Zone

Counting objects within a specified zone plays a significant role in computer vision, with applications ranging from monitoring supermarket congestion to assessing components in manufacturing. The process involves using the open-source Supervision library along with YOLOv8 for object detection. Initially, the Supervision package and the ultralytics package containing YOLOv8 are installed. The approach begins by using the PolygonZone tool to calculate the coordinates for desired zones within a video frame. These coordinates are essential for identifying whether objects are inside or outside the specified zone. Once the zone is defined, a pre-trained YOLOv8 model detects objects, particularly people in this instance, by filtering detections to focus on the "person" class from the COCO dataset. The detected objects are processed and annotated using Supervision, resulting in a fully annotated video that visualizes the object count within the zone. This methodology not only counts objects but can also trigger actions based on the count, such as logging when a zone is busy, thereby providing a comprehensive toolkit for various computer vision applications.