Image
Annotation Tool
Label faster with a quality-first annotation platform
Ango Hub is a production ready image labeling platform with built in workflows, quality checks, and automation assist. iMerit delivers your annotation program inside the tool so you can scale output, reduce rework, and keep quality consistent from pilot to production.
WHAT ANGO HUB OFFERS
Everything you need to run image labeling at production scale, with control over quality, throughput, and performance.
WORKFLOW MANAGEMENT
Configure projects end to end with a customizable workflow editor that supports roles, stages, routing, and handoffs. Keep project instructions centralized so every contributor follows the same standard.
BUILT-IN QUALITY CHECKS
Quality is enforced inside the workflow with reviewer validation and correction steps, multi labeler consensus for difficult tasks, benchmark questions to measure performance, and custom label validation to catch errors early.
AUTOMATION ASSIST
Auto detect and Copilot speed up labeling with auto labeling, YOLOv11 bounding boxes for 80 plus object types, image summaries, and schema aware classification support.
INTEGRATIONS
Connect Ango Hub to your pipelines using SDK and API support, and automate downstream handoffs through webhooks for instant data egress.
ANALYTICS
Monitor progress with detailed project analytics including throughput, cycle time, and quality trends, so you can identify bottlenecks, manage capacity, and improve consistency over time.
SECURITY AND GOVERNANCE
Control access and accountability across teams with role based permissions and governed workflows. Keep quality decisions traceable with in workflow issue resolution and structured review paths.
USE CASES
Across autonomy, geospatial, retail, robotics, and inspection, iMerit helps teams turn your image data into high-quality ground truth for training and benchmarking image models.
AUTONOMOUS VEHICLES
Image annotation for lanes, vehicles, pedestrians, signs, and drivable areas for ADAS and autonomy
MEDICAL IMAGING
Segmentation and classification to support imaging AI training and validation.
GEO SPATIAL AND MAPPING
Label features in satellite and aerial imagery for mapping, planning, and monitoring.
FACIAL RECOGNITION
Keypoint and face attribute labeling to train and evaluate recognition and verification models.
ROBOTICS
Image annotation for robots to understand objects, depth, and spatial relationships
AGRICULTURE
Label crops, weeds, canopy, and field features to power yield and health insights.
INDUSTRIAL INSPECTION
Defect detection and classification for manufacturing quality and asset maintenance.
DOCUMENT AND id VISION
Annotate document regions, fields, and text areas to improve OCR and document AI.
RETAIL AND E-COMMERCE
Product detection, shelf intelligence, and catalog labeling to improve search and conversion.
Energy and utilities
Detect corrosion, leaks, cracks, and anomalies across pipelines, power lines, and water networks using image labeling for inspection models.
TYPES OF ANNOTATION
Bounding Boxes
It is the most commonly used type of image annotation in computer vision. iMerit computer vision experts use rectangular box annotation to illustrate objects and train data, enabling algorithms with annotated images to identify and localize objects during the machine learning process. The simplicity of bounding boxes is exactly their strength, making this method of image annotation applicable for a wide range of uses.
Polygon Annotation
Expert annotators plot points on each vertex of the target object. Polygon annotation allows all of the object’s exact edges to be annotated, regardless of shape. This allows computer vision and other artificial intelligence models to recognize and respond to objects. This technique is especially useful in computer vision as annotators can use it to identify irregular shapes, allowing computers to identify and respond to them.
Semantic Segmentation
Images are segmented into component parts, by the iMerit team, and then annotated. iMerit computer vision experts detect desired objects within images at the pixel level. With expert semantic segmentation, data can be organized in multiple formats for AI models across a variety of use cases.
LiDAR Annotation
iMerit teams label images and videos in 360-degree visibility, captured by multi-sensor cameras, in order to build accurate, high-quality, ground truth datasets for use in computer vision models such as autonomous vehicles.
Image Classification
iMerit annotators classify images or objects within images based on custom multi-level taxonomies, including land use, crops, residential property features, among others. Expert image classification turns image data into image insights for AI and ML models.
3d cuboid annotation
Through the use of cuboids, iMerit annotators can generate training datasets to teach machine learning models to recognize the depth of objects. Expert data labeling creates best-in-class training datasets for computer vision models to detect object and obstacle dimensions. Through the use of anchor points typically placed at the edges of an item, these dots are then connected with a line that results in a 3D representation of the object.
Keypoint annotation
iMerit teams outline objects and shape variations by connecting individual points across objects. This annotation type detects body features and could include facial expressions and emotions. Popular use cases for keypoint annotation involve facial recognition.
Polyline annotation
iMerit experts create training datasets using polyline annotation that teach a machine learning model to identify physical boundaries to operate within. Popular use cases include autonomous vehicles and teaching them road boundaries.
Rapid annotation
iMerit’s image annotation platform utilizes image interpolation to rapidly annotate suitable files including JPG, PNG, and even CSV. iMerit annotation experts create best-in-class video training datasets in rapid time for any AI or ML project. Give your data science team the expert service they need to take their project from idea to production.
SCALING
HUMAN IN THE LOOP
AI-Assisted features of iMerits’ Ango Hub will automate your AI data workflows to improve efficiency and model RLHF, allowing domain experts to focus on applying their knowledge to create high-quality data.
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Get production-ready labels for computer vision. Ango Hub pairs workflow control and automation assist with iMerit delivery so you can scale image annotation with consistent quality.
