Object Detection

The YOLO family of models (i.e. YOLOv7, YOLOv7) are commonly used in object detection use cases. YOLO has been developed and refined over a years-long period and is still in active development. The latest model, YOLOv7, achieves state-of-the-art performance on object detection in the MS COCO dataset. Other models like Detectron2 and EfficientDet are also used in object detection.

Object detection has many use cases, including:

• Identifying whether someone is wearing the requisite safety equipment in a controlled environment (i.e. a construction site or a medical area).
• Finding objects on a road to help guide an autonomous car.
• Identifying animals in a wildlife reserve.
• Counting pills to be dispensed into bottles for pharmacies.

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Object detection is a computer vision solution that focuses on identifying the location of objects in an image or video. Each identified object is assigned a label that represents its contents. Using object detection, you can also count the number of times different objects appear in an image.