LLM Evaluations
Computer Vision Data Labeling: Bounding Boxes, Segmentation, and Choosing the Right Annotation Type
Published on May 1, 2026 · 6 min read
Frequently Asked Questions
What annotation format should I use for object detection?
Bounding boxes are the standard for object detection tasks and are supported by all major frameworks (YOLO, Faster R-CNN, SSD). Use polygons if your objects are highly non-rectangular and background context would confuse the model.
Is semantic segmentation worth the extra annotation cost?
For applications requiring pixel-level understanding, autonomous vehicles, medical imaging, satellite analysis, yes. For most detection tasks, bounding boxes deliver comparable model performance at a fraction of the annotation cost.
About the Author
Trainset AI is led by Timothy Yang, a founder with a proven track record in online business and digital marketplaces. Timothy previously exited Landvalue.au and owns two freelance marketplaces with over 160,000 members combined. With experience scaling communities and building platforms, he's now making enterprise-quality AI data labeling accessible to startups and mid-market companies.