CVAT

强大而高效的计算机视觉标注工具(CVAT)。「Powerful and efficient Computer Vision Annotion Tool (CVAT)」

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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.

For more information about supported formats look at the
documentation.

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
ImageNet X X
CamVid X X
WIDER Face X X
VGGFace2 X X
Market-1501 X X
ICDAR13/15 X X

Deep learning serverless functions for automatic labeling

Name Type Framework CPU GPU
Deep Extreme Cut interactor OpenVINO X
Faster RCNN detector OpenVINO X
Mask RCNN detector OpenVINO X
YOLO v3 detector OpenVINO X
Object reidentification reid OpenVINO X
Semantic segmentation for ADAS detector OpenVINO X
Text detection v4 detector OpenVINO X
SiamMask tracker PyTorch X
f-BRS interactor PyTorch X
Inside-Outside Guidance interactor PyTorch X
Faster RCNN detector TensorFlow X X
Mask RCNN detector TensorFlow X X
RetinaNet detector PyTorch X X

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

Prebuilt Docker images

Prebuilt docker images for CVAT releases are available on Docker Hub:

LICENSE

Code released under the MIT License.

This software uses LGPL licensed libraries from the FFmpeg project.
The exact steps on how FFmpeg was configured and compiled can be found in the Dockerfile.

FFmpeg is an open source framework licensed under LGPL and GPL.
See https://www.ffmpeg.org/legal.html. You are solely responsible
for determining if your use of FFmpeg requires any
additional licenses. Intel is not responsible for obtaining any
such licenses, nor liable for any licensing fees due in
connection with your use of FFmpeg.

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:

Projects using CVAT

  • Onepanel is an open source
    vision AI platform that fully integrates CVAT with scalable data processing
    and parallelized training pipelines.
  • DataIsKey uses CVAT as their prime data labeling tool
    to offer annotation services for projects of any size.
  • Human Protocol uses CVAT as a way of adding annotation service to the human protocol.

概覽

名稱與所有者cvat-ai/cvat
主編程語言TypeScript
編程語言Python (語言數: 11)
平台Docker, Linux, Mac, Web browsers
許可證MIT License
發布數71
最新版本名稱v2.12.1 (發布於 )
第一版名稱0.1.0 (發布於 2018-06-29 23:28:29)
創建於2018-06-29 14:02:45
推送於2024-04-30 15:00:26
最后一次提交2024-04-29 09:06:56
星數11.4k
關注者數185
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提交數4.3k
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