Boxes, masks, keypoints and polygons at any scale.
Overview
What is image annotation?
Image annotation labels images with bounding boxes, polygons, masks and keypoints, so vision models can detect, classify and localize objects with pixel-level precision.
Model accuracy is bounded by annotation precision. Boundary consistency and a disciplined class taxonomy decide detection and segmentation performance.
Object detection annotation across single and multi-class datasets.
Semantic and instance masks with sub-pixel precision.
Pose estimation and landmark annotation for structured objects.
Full dataset coverage guarantee with automated gap detection.
Workflow
How we do it
- 01Image analysis
We analyze your dataset to define annotation types, class taxonomy and edge-case guidelines.
- 02Pilot batch
100 to 500 images annotated as a calibration pilot, reviewed with you before production.
- 03Production annotation
Annotators label images with boxes, polygons, masks or keypoints per your schema.
- 04Consistency check
Automated geometric validation catches boundary precision and overlap errors.
- 05Export & delivery
Exported in COCO, Pascal VOC, YOLO or custom JSON with a QA certificate.
Case study
Annotate 500K shelf images for planogram compliance
Custom bounding-box pipeline with SKU-level class taxonomy and automated QA.
Ready to get startedwith image annotation?
Tell us about your project and we will scope a pilot within 48 hours.