The Fastest Data Labeling For High-Quality Computer Vision At Scale
Accelerate the development of your AI solutions with our complete labeling toolset built for speed and ease for dataset creation. Available with Sense for integrated model training or as a standalone application, HyperLabel helps machine learning teams iterate quickly and easily.
Experience HyperLabel For High-Performance Computer Vision Data Annotation
HyperLabel makes labeling video and images for your computer vision projects fast and easy with a robust set of features and simple step-by-step interface. Download today and start labeling in minutes.
A full set of features to equip all your computer vision labeling projects, HyperLabel is designed to maximize productivity and scale.
Custom Label Schemas
Create label schema types for object detection, image segmentation, pose estimation, facial key points, captioning, classification & more
AI Assisted Labeling
Save time and resources by using the built in smart labeling features such as Auto-Labeling, Smart Polygon Selection & Label QA
Sync data across teams, manage roles, provide instructions, add comments & review labeling progress
Data Export Formats
All major computer vision label formats are available for export: COCO, YOLO, Pascal VOC & CreateML
Easy-To-Define Custom Schemas
HyperLabel supports all major definitions used in computer vision labeling. Choose from Rectangles, Polygons, Point, Feature Points, Text, Class, or Multi-Class.
Rectangle, Polygon, and Point labels also support sub-labeling options.
Draw boxes to detect specific objects within images.
Segment objects for detection within image frames.
Label anatomical or structural points of interest within images.
Use for highly detailed detection such as emotion & body pose.
Leverage for free text production for image captions ideal for accessibility.
Designed for specific filters & image search.
Apply for multi label image classification & attribute identification.
Add sub-labels into the label definitions for rectangles, polygons, and point labels.
Supported Label Export Formats
HyperLabel supports the most common label formats for computer vision. Choose to export as COCO, Pascal VOC, YOLO, Create ML or HyperLabels own JSON format.
Connect Data Sources
Connect both local storage and remote data sources to projects.
Data sources can contain images and video files. Video files will automatically convert to frames for easy labeling.
Supported image formats: JPG, PNG, GIF, BMP
Supported video formats: MPG, MP4, WMV
Connect an Amazon S3 bucket
Google Cloud Storage
Connect a GCP bucket
Label files stored locally
Use a local CSV file
AI Assisted Labeling (Coming Soon)
Label smarter with HyperLabel’s AI assisted labeling features.
Automatically label common objects such as cars and people, and automatic polygon selection saves massive amount of labeling time for image segmentation.
Check label quality and receive suggestions using SmartQA.
Select objects to recognize, and HyperLabel will use its SmartLabel feature to automatically apply labels
Auto Polygon Selection
Save time labeling instance segmentation by drawing a simple rectangle that resolves to an auto-polygon selection
Check the project quality by using HyperLabel’s SmartQA feature to audit and correct labels
HyperLabel makes working as a team easy.
Sync data sources across teams, manage roles, provide labeling instructions, add comments, review labeling progress and time spent per label.
Sync data sources across teams
Add labeling and project details
Add comments to applied labels
Track production time and progress
HyperLabel is fully integrated with the Sixgill Sense platform to streamline and accelerate the data annotation and model training stages in the ML lifecycle.
Connect and manage sensor streams & edge computing devices
Create training datasets with version control directly from sensors
Integrate with HyperLabel to sync datasets for easy image labeling
Select existing models or bring you own & train from a labeled dataset
Manage edge and cloud model deployments from a single interface
Built By Machine Learning Engineers For Everyone
We’re not just a dev team behind an application, we’re users too. We know first-hand the pain points of each step in the machine learning life cycle, so we built Sense and HyperLabel from the ground up to eliminate bottlenecks and allow anyone to build machine learning models and benefit from the value of AI.
Connect with our engineers and community to learn how Sense can work for you.
AI for ALL
All AI/ML teams within organizations across all industries can benefit from computer vision AI-powered solutions.
Fever & PPE Detection
Occupancy & Distancing Monitoring
Cleaning & Disinfecting Compliance
Drug R&D Acceleration
Clinical Trial Optimization
Product/Goods Count & Tracking
Shipment On-Off Loading Monitoring
Product Compromise Detection
Oil & Gas
VOC Gas Leak Detection
Site Security Intelligence
APPLIED MACHINE LEARNING FOR FEVER DETECTION & PPE ENFORCEMENT
Across all industries, there’s an urgent need to accurately screen all people coming into a facility, or area, and automate the detection of fever and assure compliance with PPE policies.
Sense enables organizations to use the power of video to cameras help identify threats in real time. Sixgill-built models allow for non-contact preventative monitoring and screening and real-time alerting and data logging of events. Models include thermographic fever scanning, mask (and other PPE) compliance detection.