CVAT
Open-source data annotation platform for images, videos, and 3D
About CVAT
CVAT (Computer Vision Annotation Tool) is an industry-leading open-source annotation platform originally developed by Intel for labeling images, videos, and 3D point clouds. Trusted by over 200,000 developers, it offers a comprehensive toolset including bounding boxes, polygons, skeletons, and cuboids with AI-assisted auto-annotation that speeds up labeling by up to 10x. Available as a self-hosted open-source edition, a managed cloud platform, or an enterprise on-premises deployment.
Pros & Cons
Pros
- Fully open source (MIT license) with no vendor lock-in — self-host for free with unlimited usage
- Industry-leading annotation toolset covering images, video, 3D point clouds, and LIDAR data
- AI-assisted auto-annotation with SAM, YOLO, and custom model support dramatically speeds up labeling
- Supports 20+ export formats (COCO, YOLO, VOC, KITTI, etc.) for seamless ML pipeline integration
- Scales from individual researchers to enterprise teams with 300+ annotators
- Active open-source community with 15.5k GitHub stars and regular updates
Cons
- Self-hosted setup requires Docker and server administration knowledge
- Free cloud tier is very limited (1 project, 3 tasks, 1 GB storage)
- Learning curve for advanced features like 3D annotation and custom model integration
- No native text or audio annotation — focused exclusively on computer vision tasks
- Enterprise pricing starts at \u002412,000/year which may be steep for small teams
Key Features
AI-Powered Auto Annotation
Annotate data up to 10x faster using built-in AI models like Segment Anything (SAM 2/3), YOLO, and Faster RCNN, or connect your own custom models
Comprehensive Annotation Toolset
Full suite of annotation primitives including bounding boxes, polygons, polylines, points, skeletons, cuboids, and trajectories for any computer vision task
Video & 3D Point Cloud Support
Annotate video sequences with object tracking and interpolation, plus full 3D point cloud and LIDAR annotation capabilities
20+ Export Formats
Export annotations in PASCAL VOC, COCO, YOLO, KITTI, TensorFlow Detection API, CamVid, Cityscapes, LabelMe, MOT, and many more formats
Cloud Storage Integration
Connect directly to AWS S3, Google Cloud Storage, and Azure Blob Storage for seamless data management at scale
Quality Assurance & Analytics
Built-in review workflows, ground truth jobs, honey pot validation, and performance analytics tracking annotator hours and objects per hour
Python SDK, CLI & REST API
Programmatic access via a full REST API, Python SDK, and command-line interface for integration into ML pipelines and automation workflows
Team Collaboration
Role-based access control, SSO support, audit logs, and multi-user project management for annotation teams of any size
Pricing
- MIT licensed open source
- All core annotation tools
- Unlimited projects and tasks
- Docker deployment
- REST API & Python SDK
- Community support via GitHub & Discord
- 1 project, 3 tasks
- 1 GB internal storage
- Images, video & 3D data support
- Manual review & QA tools
- API access
- 100 AI agent calls per month
- 10 projects, 250 tasks
- 25 GB internal storage
- 3 cloud storage connections
- Automatic batch annotation
- 10,000 AI calls per month
- Reports & analytics
- Annotation + image export
- 30-100 projects (scales with plan)
- 75-250 GB storage
- Up to 30 cloud storage connections
- 30,000-100,000 AI calls per month
- SSO & role-based access control
- Ground truth & honey pot validation
- SAM 2/3 & Hugging Face integrations
- Audit logs & dedicated support
- On-premises or private cloud deployment
- Unlimited projects and storage
- Custom AI model integration
- GDPR, CCPA & EU AI Act compliance
- Dedicated support & SLA
- Professional annotation services available
Best For
Autonomous Vehicle Development
Annotate driving footage and LIDAR point clouds with bounding boxes, polygons, and 3D cuboids for training self-driving perception models
Medical Image Analysis
Label medical imaging data (X-rays, CT scans, pathology slides) with precise segmentation masks for diagnostic AI model training
Retail & Manufacturing Quality Control
Annotate product images and video feeds to train defect detection and inventory management computer vision systems
Research & Academic Projects
Free self-hosted deployment for university labs and research teams building custom computer vision datasets with full format flexibility
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