Precision labeling for visual AI
Image Annotation
Bounding boxes, segmentation masks, keypoints, and polygon annotation for computer vision models at any scale.
Overview
What is Image Annotation?
Image annotation labels images with bounding boxes, polygons, segmentation masks, and keypoints so computer vision models can detect, classify, and localize objects with pixel-level precision.
Why it matters: Vision model accuracy is bounded by annotation precision. Sub-pixel boundary consistency and disciplined class taxonomy directly determine detection and segmentation performance in production.
Bounding Boxes
Object detection annotation across single and multi-class datasets
Segmentation
Semantic and instance segmentation masks with sub-pixel precision
Keypoints
Pose estimation and landmark annotation for structured objects
99%+ Coverage
Full dataset coverage guarantee with automated gap detection
Workflow
How We Do It
01
Image Analysis
We analyze your dataset to define annotation types, class taxonomy, and edge-case guidelines.
02
Pilot Batch
100-500 images annotated as a calibration pilot, reviewed with you before production.
03
Production Annotation
Expert annotators label images with bounding boxes, polygons, masks, or keypoints per your schema.
04
Consistency Check
Automated geometric validation catches boundary precision and overlap errors.
05
Export & Delivery
Dataset exported in COCO, Pascal VOC, YOLO, or custom JSON with a QA certificate.
Case Study
Retail AI Platform
Retail AI Platform
Annotate 500K shelf images for planogram compliance
Solution
Custom bounding-box pipeline with SKU-level class taxonomy and automated QA
Results
500K
Images annotated
98%
Detection accuracy
5 wks
Delivery
Ready to Get Started with Image Annotation?
Tell us about your project and we'll scope a pilot within 48 hours.