CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our team to annotate million of objects with different properties. Many UI and UX decisions are based on feedbacks from professional data annotation team.

• Installation guide
• User's guide
• Django REST API documentation
• XML annotation format
• AWS Deployment Guide
• Questions

• Introduction
• Annotation mode
• Interpolation mode
• Attribute mode
• Segmentation mode
• Tutorial for polygons
• Semi-automatic segmentation

Format selection is possible after clicking on the Upload annotation / Dump annotation button.

• Intel AI blog: New Computer Vision Tool Accelerates Annotation of Digital Images and Video
• Intel Software: Computer Vision Annotation Tool: A Universal Approach to Data Annotation
• VentureBeat: Intel open-sources CVAT, a toolkit for data labeling

Onepanel has added CVAT as an environment into their platform and a running demo of CVAT can be accessed at CVAT Public Demo.

After you click the link above:

• Click on "GO TO WORKSPACE" and the CVAT environment will load up
• The environment is backed by a K80 GPU

If you have any questions, please contact Onepanel directly at [email protected]. If you are in the Onepanel application, you can also use the chat icon in the bottom right corner.

Automatically generated Swagger documentation for Django REST API is available on <cvat_origin>/api/swagger (default: localhost:8080/api/swagger).

Code released under the MIT License.

CVAT usage related questions or unclear concepts can be posted in our Gitter chat for quick replies from contributors and other users.

However, if you have a feature request or a bug report that can reproduced, feel free to open an issue (with steps to reproduce the bug if it's a bug report).

If you are not sure or just want to browse other users common questions, Gitter chat is the way to go.