Bounding Box Annotation
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Image Annotation Services for Computer Vision and Visual AI
Pixel-accurate annotation for object detection, segmentation, pose estimation and classification with documented edge-case rules and multi-tier quality review.
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What Is Image Annotation?
Image annotation adds machine-readable labels to still images. Boxes teach approximate location, masks teach exact shape, keypoints teach structure and image labels teach scene-level categories.
Image Annotation vs. Image Labeling
Labeling commonly means a whole-image class; annotation includes spatial boxes, polygons, masks and keypoints.
Image Annotation vs. Image Data Collection
Collection captures new images. Annotation structures images you already have. Explore Image Data Collection.
Image Annotation Types We Deliver
Rotated and Oriented Boxes
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Polygon and Polyline Annotation
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Semantic Segmentation
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Instance Segmentation
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Panoptic Segmentation
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Keypoint and Landmark Annotation
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Image Classification and Multi-label Tagging
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Attribute and Metadata Tagging
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Text Region Labeling in Images
Guideline-led visual labels delivered to the geometry, class and attribute rules agreed in the pilot.
Which Image Annotation Type Do You Need?
Choose classification for image-level categories, boxes for detection, polygons for tight outlines, semantic masks for class areas, instance masks for separate objects, panoptic masks for complete scenes, and keypoints for pose or structure.
Bounding Box or Polygon?
Use boxes when location is enough and polygons when shape matters.
Semantic or Instance Segmentation?
Semantic masks map area by class; instance masks preserve separate objects.
Our Image Annotation Process
- Sample review
- Guideline authoring
- Annotator calibration
- Pilot batch
- Production
- Multi-tier QA
- Delivery and iteration
How We Keep Image Annotation Accurate
IoU monitoring, gold sets, inter-annotator agreement, consensus, adjudication, second-pass review, automated geometry validation, class-balance reporting and pilot-defined acceptance criteria.
Occlusion, Truncation and the Cases That Break Datasets
Written rules cover occlusion, truncation, crowds, small objects, ambiguous classes, reflections, poor exposure and overlapping instances.
Tools, Platforms and Output Formats
COCO JSON, YOLO, Pascal VOC, CVAT XML, PNG and RLE masks, JSON, CSV, TFRecord, Parquet and custom schemas, with a manifest, QA report and versioned guideline.
Image Annotation Across Industries
Automotive, retail, manufacturing, agriculture, healthcare, construction, security and robotics.
Model-Assisted Pre-Labeling
Human reviewers can correct model suggestions while quality is measured against the same expert ground truth as manual work.
Data Security and Compliance
ISO-certified processes, NDAs, role-based access, audit trails, secure environments, PII redaction and contract-defined retention.
What Determines Image Annotation Cost?
Annotation type, object count, taxonomy complexity, precision target, scene density, QA tier, volume, expertise, turnaround and security.
Related AI Data Services
Image Data Collection Data Cleaning and Validation AI Model Testing All Annotation Services
Why Choose eQOURSE for Image Annotation?
Guideline-first delivery, measured quality, full-pipeline support, 500+ specialists, ISO-certified processes and a free pilot.
Frequently Asked Questions About Image Annotation
What is image annotation?
Image annotation adds machine-readable boxes, outlines, masks, keypoints or class tags to still images so computer vision models can learn to recognise objects, shapes and scenes.
What is the difference between bounding box and polygon annotation?
Bounding boxes mark approximate object location quickly. Polygons trace the actual outline and are used when shape matters.
What is the difference between semantic and instance segmentation?
Semantic segmentation assigns pixels by class. Instance segmentation gives every object its own mask.
How do you measure image annotation quality?
eQOURSE uses IoU scoring, gold sets, inter-annotator agreement, consensus, second-pass review and automated validation.
What output formats do you deliver?
COCO JSON, YOLO, Pascal VOC, CVAT XML, PNG masks, RLE masks, JSON, CSV, TFRecord, Parquet and custom schemas.
How do we start?
Share representative images, your label schema and accuracy target for a free pilot with a QA report.