CVAT

Computer Vision Annotation Tool.

Visit Website →

Overview

CVAT (Computer Vision Annotation Tool) is a popular open-source tool for labeling images and videos for computer vision tasks. It supports a wide range of annotation formats and is highly customizable. CVAT can be self-hosted or used through the cloud-based service, CVAT.ai, which offers additional features and support.

✨ Key Features

  • Open-source and free to use (self-hosted)
  • Support for object detection, segmentation, and classification
  • Video annotation with interpolation
  • Collaborative annotation features
  • Extensible and customizable
  • Cloud-based and enterprise versions available

🎯 Key Differentiators

  • Rich feature set for an open-source tool
  • Strong community support
  • Scalability from individual use to enterprise deployment

Unique Value: Provides a powerful, flexible, and free open-source solution for computer vision data annotation.

🎯 Use Cases (4)

Academic research in computer vision Prototyping and building proof-of-concept models Data annotation for startups and small teams Custom in-house data labeling pipelines

✅ Best For

  • Creating datasets for object detection models
  • Semantic segmentation of street scenes

💡 Check With Vendor

Verify these considerations match your specific requirements:

  • Large-scale enterprise projects requiring extensive support and managed services without opting for the enterprise version.

🏆 Alternatives

Label Studio VGG Image Annotator (VIA) LabelImg

Offers a more comprehensive and user-friendly web-based interface compared to other open-source annotation tools.

💻 Platforms

Web Self-hosted API

✅ Offline Mode Available

🔌 Integrations

Python SDK REST API Integrations with various ML frameworks

🛟 Support Options

  • ✓ Email Support
  • ✓ Dedicated Support (Enterprise tier)

🔒 Compliance & Security

✓ GDPR ✓ SSO ✓ GDPR (for cvat.ai service)

💰 Pricing

$25.00/mo
Free Tier Available

✓ 14-day free trial

Free tier: The open-source version is completely free.

Visit CVAT Website →