How to Annotate Images for Object Detection
High quality training data is the foundation of every successful object detection model. Understanding how to annotate images for object detection is essential for teams working with medical imaging, industrial inspection, robotics, geospatial systems, and complex computer vision pipelines. Meticulous annotation defines how an AI system interprets objects, boundaries, and spatial relationships across thousands or millions of images. This article provides a comprehensive explanation of the annotation workflow, focusing on accuracy, consistency, quality control, and domain-specific considerations. Readers will learn best practices grounded in technical, clinical, and research-backed principles used by leading universities and AI labs.
