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[Documentation] links on readme.md page fixed (#5406)

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![CVAT logo](site/content/en/images/cvat_poster_with_name.png) ![CVAT logo](site/content/en/images/cvat_poster_with_name.png)
# Computer Vision Annotation Tool (CVAT) # Computer Vision Annotation Tool (CVAT)
<a href="https://www.producthunt.com/posts/cvat-computer-vision-annotation-tool?utm_source=badge-featured&utm_medium=badge&utm_souce=badge-cvat&#0045;computer&#0045;vision&#0045;annotation&#0045;tool" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=353415&theme=light" alt="CVAT&#0032;–&#0032;Computer&#0032;Vision&#0032;Annotation&#0032;Tool - The&#0032;open&#0032;data&#0032;annotation&#0032;platform&#0032;for&#0032;AI | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a> <a href="https://www.producthunt.com/posts/cvat-computer-vision-annotation-tool?utm_source=badge-featured&utm_medium=badge&utm_souce=badge-cvat&#0045;computer&#0045;vision&#0045;annotation&#0045;tool" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=353415&theme=light" alt="CVAT&#0032;–&#0032;Computer&#0032;Vision&#0032;Annotation&#0032;Tool - The&#0032;open&#0032;data&#0032;annotation&#0032;platform&#0032;for&#0032;AI | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
@ -50,9 +51,9 @@ please drop us a line at [contact@cvat.ai](mailto:contact+github@cvat.ai).
- [Human Protocol](https://hmt.ai) uses CVAT as a way of adding annotation service to the Human Protocol. - [Human Protocol](https://hmt.ai) uses CVAT as a way of adding annotation service to the Human Protocol.
- [FiftyOne](https://fiftyone.ai) is an open-source dataset curation and model analysis - [FiftyOne](https://fiftyone.ai) is an open-source dataset curation and model analysis
tool for visualizing, exploring, and improving computer vision datasets and models that are tool for visualizing, exploring, and improving computer vision datasets and models that are
[tightly integrated](https://voxel51.com/docs/fiftyone/integrations/cvat.html) with CVAT [tightly integrated](https://voxel51.com/docs/fiftyone/integrations/cvat.html) with CVAT
for annotation and label refinement. for annotation and label refinement.
## Public datasets ## Public datasets
@ -99,12 +100,12 @@ Here are some screencasts showing how to use CVAT.
- **Speeding up your data annotation process: introduction to CVAT and Datumaro**. What problems do CVAT and Datumaro solve, and how they can speed up your model training process. Some resources you can use to learn more about how to use them. - **Speeding up your data annotation process: introduction to CVAT and Datumaro**. What problems do CVAT and Datumaro solve, and how they can speed up your model training process. Some resources you can use to learn more about how to use them.
- **Deployment and use CVAT**. Use the app online at [app.cvat.ai](app.cvat.ai). A local deployment. A containerized local deployment with docker-compose (for regular use), and a local cluster deployment with Kubernetes (for enterprise users). A 2-minute tour of the interface, a breakdown of CVAT’s internals, and a demonstration of how to deploy CVAT using docker-compose. - **Deployment and use CVAT**. Use the app online at [app.cvat.ai](app.cvat.ai). A local deployment. A containerized local deployment with docker-compose (for regular use), and a local cluster deployment with Kubernetes (for enterprise users). A 2-minute tour of the interface, a breakdown of CVAT’s internals, and a demonstration of how to deploy CVAT using docker-compose.
[Product tour](https://www.youtube.com/playlist?list=PL0to7Ng4Puua37NJVMIShl_pzqJTigFzg): in this course, we show how to use CVAT, and help to get familiar with CVAT functionality and interfaces. This course does not cover integrations and is dedicated solely to CVAT. It covers the following topics: [Product tour](https://www.youtube.com/playlist?list=PL0to7Ng4Puua37NJVMIShl_pzqJTigFzg): in this course, we show how to use CVAT, and help to get familiar with CVAT functionality and interfaces. This course does not cover integrations and is dedicated solely to CVAT. It covers the following topics:
- **Pipeline**. In this video, we show how to use [app.cvat.ai](app.cvat.ai): how to sign up, upload your data, annotate it, and download it. - **Pipeline**. In this video, we show how to use [app.cvat.ai](app.cvat.ai): how to sign up, upload your data, annotate it, and download it.
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For feedback, please see [Contact us](#contact-us) For feedback, please see [Contact us](#contact-us)
## API ## API
@ -135,32 +136,32 @@ For more information about the supported formats, see:
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| Annotation format | Import | Export | | Annotation format | Import | Export |
| --------------------------------------------------------------------------------------------------------- | ------ | ------ | | ------------------------------------------------------------------------------------------------ | ------ | ------ |
| [CVAT for images](https://opencv.github.io/cvat/docs/manual/advanced/xml_format/#annotation) | ✔️ | ✔️ | | [CVAT for images](https://opencv.github.io/cvat/docs/manual/advanced/xml_format/#annotation) | ✔️ | ✔️ |
| [CVAT for a video](https://opencv.github.io/cvat/docs/manual/advanced/xml_format/#interpolation) | ✔️ | ✔️ | | [CVAT for a video](https://opencv.github.io/cvat/docs/manual/advanced/xml_format/#interpolation) | ✔️ | ✔️ |
| [Datumaro](https://github.com/cvat-ai/datumaro) | ✔️ | ✔️ | | [Datumaro](https://github.com/cvat-ai/datumaro) | ✔️ | ✔️ |
| [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | ✔️ | ✔️ | | [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | ✔️ | ✔️ |
| Segmentation masks from [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | ✔️ | ✔️ | | Segmentation masks from [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | ✔️ | ✔️ |
| [YOLO](https://pjreddie.com/darknet/yolo/) | ✔️ | ✔️ | | [YOLO](https://pjreddie.com/darknet/yolo/) | ✔️ | ✔️ |
| [MS COCO Object Detection](http://cocodataset.org/#format-data) | ✔️ | ✔️ | | [MS COCO Object Detection](http://cocodataset.org/#format-data) | ✔️ | ✔️ |
| [MS COCO Keypoints Detection](http://cocodataset.org/#format-data) | ✔️ | ✔️ | | [MS COCO Keypoints Detection](http://cocodataset.org/#format-data) | ✔️ | ✔️ |
| [TFrecord](https://www.tensorflow.org/tutorials/load_data/tfrecord) | ✔️ | ✔️ | | [TFrecord](https://www.tensorflow.org/tutorials/load_data/tfrecord) | ✔️ | ✔️ |
| [MOT](https://motchallenge.net/) | ✔️ | ✔️ | | [MOT](https://motchallenge.net/) | ✔️ | ✔️ |
| [MOTS PNG](https://www.vision.rwth-aachen.de/page/mots) | ✔️ | ✔️ | | [MOTS PNG](https://www.vision.rwth-aachen.de/page/mots) | ✔️ | ✔️ |
| [LabelMe 3.0](http://labelme.csail.mit.edu/Release3.0) | ✔️ | ✔️ | | [LabelMe 3.0](http://labelme.csail.mit.edu/Release3.0) | ✔️ | ✔️ |
| [ImageNet](http://www.image-net.org) | ✔️ | ✔️ | | [ImageNet](http://www.image-net.org) | ✔️ | ✔️ |
| [CamVid](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/) | ✔️ | ✔️ | | [CamVid](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/) | ✔️ | ✔️ |
| [WIDER Face](http://shuoyang1213.me/WIDERFACE/) | ✔️ | ✔️ | | [WIDER Face](http://shuoyang1213.me/WIDERFACE/) | ✔️ | ✔️ |
| [VGGFace2](https://github.com/ox-vgg/vgg_face2) | ✔️ | ✔️ | | [VGGFace2](https://github.com/ox-vgg/vgg_face2) | ✔️ | ✔️ |
| [Market-1501](https://www.aitribune.com/dataset/2018051063) | ✔️ | ✔️ | | [Market-1501](https://www.aitribune.com/dataset/2018051063) | ✔️ | ✔️ |
| [ICDAR13/15](https://rrc.cvc.uab.es/?ch=2) | ✔️ | ✔️ | | [ICDAR13/15](https://rrc.cvc.uab.es/?ch=2) | ✔️ | ✔️ |
| [Open Images V6](https://storage.googleapis.com/openimages/web/index.html) | ✔️ | ✔️ | | [Open Images V6](https://storage.googleapis.com/openimages/web/index.html) | ✔️ | ✔️ |
| [Cityscapes](https://www.cityscapes-dataset.com/login/) | ✔️ | ✔️ | | [Cityscapes](https://www.cityscapes-dataset.com/login/) | ✔️ | ✔️ |
| [KITTI](http://www.cvlibs.net/datasets/kitti/) | ✔️ | ✔️ | | [KITTI](http://www.cvlibs.net/datasets/kitti/) | ✔️ | ✔️ |
| [Kitti Raw Format](https://www.cvlibs.net/datasets/kitti/raw_data.php) | ✔️ | ✔️ | | [Kitti Raw Format](https://www.cvlibs.net/datasets/kitti/raw_data.php) | ✔️ | ✔️ |
| [LFW](http://vis-www.cs.umass.edu/lfw/) | ✔️ | ✔️ | | [LFW](http://vis-www.cs.umass.edu/lfw/) | ✔️ | ✔️ |
| [Supervisely Point Cloud Format](https://docs.supervise.ly/data-organization/00_ann_format_navi) | ✔️ | ✔️ | | [Supervisely Point Cloud Format](https://docs.supervise.ly/data-organization/00_ann_format_navi) | ✔️ | ✔️ |
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@ -173,23 +174,23 @@ up to 10x. Here is a list of the algorithms we support, and the platforms they c
| Name | Type | Framework | CPU | GPU | | Name | Type | Framework | CPU | GPU |
| ------------------------------------------------------------------------------------------------------- | ---------- | ---------- | --- | --- | | ------------------------------------------------------------------------------------------------------- | ---------- | ---------- | --- | --- |
| [Deep Extreme Cut](/serverless/openvino/dextr/nuclio) | interactor | OpenVINO | ✔️ | | | [Deep Extreme Cut](/serverless/openvino/dextr/nuclio) | interactor | OpenVINO | ✔️ | |
| [Faster RCNN](/serverless/openvino/omz/public/faster_rcnn_inception_v2_coco/nuclio) | detector | OpenVINO | ✔️ | | | [Faster RCNN](/serverless/openvino/omz/public/faster_rcnn_inception_v2_coco/nuclio) | detector | OpenVINO | ✔️ | |
| [Mask RCNN](/serverless/openvino/omz/public/mask_rcnn_inception_resnet_v2_atrous_coco/nuclio) | detector | OpenVINO | ✔️ | | | [Mask RCNN](/serverless/openvino/omz/public/mask_rcnn_inception_resnet_v2_atrous_coco/nuclio) | detector | OpenVINO | ✔️ | |
| [YOLO v3](/serverless/openvino/omz/public/yolo-v3-tf/nuclio) | detector | OpenVINO | ✔️ | | | [YOLO v3](/serverless/openvino/omz/public/yolo-v3-tf/nuclio) | detector | OpenVINO | ✔️ | |
| [Object reidentification](/serverless/openvino/omz/intel/person-reidentification-retail-300/nuclio) | reid | OpenVINO | ✔️ | | | [Object reidentification](/serverless/openvino/omz/intel/person-reidentification-retail-300/nuclio) | reid | OpenVINO | ✔️ | |
| [Semantic segmentation for ADAS](/serverless/openvino/omz/intel/semantic-segmentation-adas-0001/nuclio) | detector | OpenVINO | ✔️ | | | [Semantic segmentation for ADAS](/serverless/openvino/omz/intel/semantic-segmentation-adas-0001/nuclio) | detector | OpenVINO | ✔️ | |
| [Text detection v4](/serverless/openvino/omz/intel/text-detection-0004/nuclio) | detector | OpenVINO | ✔️ | | | [Text detection v4](/serverless/openvino/omz/intel/text-detection-0004/nuclio) | detector | OpenVINO | ✔️ | |
| [YOLO v5](/serverless/pytorch/ultralytics/yolov5/nuclio) | detector | PyTorch | ✔️ | | | [YOLO v5](/serverless/pytorch/ultralytics/yolov5/nuclio) | detector | PyTorch | ✔️ | |
| [SiamMask](/serverless/pytorch/foolwood/siammask/nuclio) | tracker | PyTorch | ✔️ | ✔️ | | [SiamMask](/serverless/pytorch/foolwood/siammask/nuclio) | tracker | PyTorch | ✔️ | ✔️ |
| [TransT](/serverless/pytorch/dschoerk/transt/nuclio) | tracker | PyTorch | ✔️ | ✔️ | | [TransT](/serverless/pytorch/dschoerk/transt/nuclio) | tracker | PyTorch | ✔️ | ✔️ |
| [f-BRS](/serverless/pytorch/saic-vul/fbrs/nuclio) | interactor | PyTorch | ✔️ | | | [f-BRS](/serverless/pytorch/saic-vul/fbrs/nuclio) | interactor | PyTorch | ✔️ | |
| [HRNet](/serverless/pytorch/saic-vul/hrnet/nuclio) | interactor | PyTorch | | ✔️ | | [HRNet](/serverless/pytorch/saic-vul/hrnet/nuclio) | interactor | PyTorch | | ✔️ |
| [Inside-Outside Guidance](/serverless/pytorch/shiyinzhang/iog/nuclio) | interactor | PyTorch | ✔️ | | | [Inside-Outside Guidance](/serverless/pytorch/shiyinzhang/iog/nuclio) | interactor | PyTorch | ✔️ | |
| [Faster RCNN](/serverless/tensorflow/faster_rcnn_inception_v2_coco/nuclio) | detector | TensorFlow | ✔️ | ✔️ | | [Faster RCNN](/serverless/tensorflow/faster_rcnn_inception_v2_coco/nuclio) | detector | TensorFlow | ✔️ | ✔️ |
| [Mask RCNN](/serverless/tensorflow/matterport/mask_rcnn/nuclio) | detector | TensorFlow | ✔️ | ✔️ | | [Mask RCNN](/serverless/tensorflow/matterport/mask_rcnn/nuclio) | detector | TensorFlow | ✔️ | ✔️ |
| [RetinaNet](serverless/pytorch/facebookresearch/detectron2/retinanet/nuclio) | detector | PyTorch | ✔️ | ✔️ | | [RetinaNet](serverless/pytorch/facebookresearch/detectron2/retinanet/nuclio) | detector | PyTorch | ✔️ | ✔️ |
| [Face Detection](/serverless/openvino/omz/intel/face-detection-0205/nuclio) | detector | OpenVINO | ✔️ | | | [Face Detection](/serverless/openvino/omz/intel/face-detection-0205/nuclio) | detector | OpenVINO | ✔️ | |
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@ -237,21 +238,15 @@ questions and get our support.
[docker-server-pulls-img]: https://img.shields.io/docker/pulls/cvat/server.svg?style=flat-square&label=server%20pulls [docker-server-pulls-img]: https://img.shields.io/docker/pulls/cvat/server.svg?style=flat-square&label=server%20pulls
[docker-server-image-url]: https://hub.docker.com/r/cvat/server [docker-server-image-url]: https://hub.docker.com/r/cvat/server
[docker-ui-pulls-img]: https://img.shields.io/docker/pulls/cvat/ui.svg?style=flat-square&label=UI%20pulls [docker-ui-pulls-img]: https://img.shields.io/docker/pulls/cvat/ui.svg?style=flat-square&label=UI%20pulls
[docker-ui-image-url]: https://hub.docker.com/r/cvat/ui [docker-ui-image-url]: https://hub.docker.com/r/cvat/ui
[ci-img]: https://github.com/opencv/cvat/workflows/CI/badge.svg?branch=develop
[ci-img]: https://github.com/cvat-ai/cvat/workflows/CI/badge.svg?branch=develop [ci-url]: https://github.com/opencv/cvat/actions
[ci-url]: https://github.com/cvat-ai/cvat/actions
[gitter-img]: https://img.shields.io/gitter/room/opencv-cvat/public?style=flat [gitter-img]: https://img.shields.io/gitter/room/opencv-cvat/public?style=flat
[gitter-url]: https://gitter.im/opencv-cvat [gitter-url]: https://gitter.im/opencv-cvat
[coverage-img]: https://coveralls.io/repos/github/cvat-ai/cvat/badge.svg?branch=develop [coverage-img]: https://coveralls.io/repos/github/cvat-ai/cvat/badge.svg?branch=develop
[coverage-url]: https://coveralls.io/github/cvat-ai/cvat?branch=develop [coverage-url]: https://coveralls.io/github/cvat-ai/cvat?branch=develop
[doi-img]: https://zenodo.org/badge/139156354.svg [doi-img]: https://zenodo.org/badge/139156354.svg
[doi-url]: https://zenodo.org/badge/latestdoi/139156354 [doi-url]: https://zenodo.org/badge/latestdoi/139156354
[discord-img]: https://img.shields.io/discord/1000789942802337834?label=discord [discord-img]: https://img.shields.io/discord/1000789942802337834?label=discord
[discord-url]: https://discord.gg/fNR3eXfk6C [discord-url]: https://discord.gg/fNR3eXfk6C

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