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Computer Vision Annotation Tool (CVAT)

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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. Try it online cvat.org.

CVAT screenshot

Documentation

Screencasts

Supported annotation formats

Format selection is possible after clicking on the Upload annotation and Dump annotation buttons. Datumaro dataset framework allows additional dataset transformations via its command line tool and Python library.

Annotation format Import Export
CVAT for images X X
CVAT for a video X X
Datumaro X
PASCAL VOC X X
Segmentation masks from PASCAL VOC X X
YOLO X X
MS COCO Object Detection X X
TFrecord X X
MOT X X
LabelMe 3.0 X X

Links

Online demo: cvat.org

This is an online demo with the latest version of the annotation tool. Try it online without local installation. Only own or assigned tasks are visible to users.

Disabled features:

Limitations:

  • No more than 10 tasks per user
  • Uploaded data is limited to 500Mb

REST API

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

Swagger documentation is visiable on allowed hostes, Update environement variable in docker-compose.yml file with cvat hosted machine IP or domain name. Example - ALLOWED_HOSTS: 'localhost, 127.0.0.1')

LICENSE

Code released under the MIT License.

Questions

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) on GitHub* issues.

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

Other ways to ask questions and get our support: