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Add dataset examples and update some links in docs (#6259)
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### Motivation and context
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- Added dataset example links
- Fixed COCO links to Datumaro docs

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- [ ] I submit my changes into the `develop` branch
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2 changes: 2 additions & 0 deletions site/content/en/docs/manual/advanced/formats/format-camvid.md
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# [CamVid](http://mi.eng.cam.ac.uk/research/projects/VideoRec/CamVid/)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/camvid_dataset)

## CamVid export

Downloaded file: a zip archive of the following structure:
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# [Cityscapes](https://www.cityscapes-dataset.com/login/)

- [Format specification](https://github.com/mcordts/cityscapesScripts#the-cityscapes-dataset)
- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/cityscapes_dataset)

- Supported annotations

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# [MS COCO Object Detection](http://cocodataset.org/#format-data)

- [Format specification](https://openvinotoolkit.github.io/datumaro/docs/formats/coco/)
- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/coco_dataset)

## COCO export

Downloaded file: a zip archive with the structure described [here](https://openvinotoolkit.github.io/datumaro/docs/formats/coco/#import-coco-dataset)
Downloaded file: a zip archive with the structure described [here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset)

```
archive.zip/
├── images/
│ ├── train/
│ │ ├── <image_name1.ext>
│ │ ├── <image_name2.ext>
│ │ └── ...
│ └── val/
│ ├── <image_name1.ext>
│ ├── <image_name2.ext>
│ └── ...
└── annotations/
├── <task>_<subset_name>.json
└── ...
```

If the dataset is exported from a Project, the subsets are named the same way as they are named
in the project. In other cases there will be a single `default` subset, containing all the data.
The `<task>` part corresponds to one of the COCO tasks: `instances`, `person_keypoints`,
`panoptic`, `image_info`, `labels`, `captions`, `stuff`. There can be several annotation
files in the archive.

- supported annotations: Polygons, Rectangles
- supported attributes:
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- `score` (number) - the annotation `score` field
- arbitrary attributes - will be stored in the `attributes` annotation section

Support for COCO tasks via Datumaro is described [here](https://openvinotoolkit.github.io/datumaro/docs/formats/coco/#export-to-other-formats)
Support for COCO tasks via Datumaro is described [here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#export-to-other-formats)
For example, [support for COCO keypoints over Datumaro](https://github.com/openvinotoolkit/cvat/issues/2910#issuecomment-726077582):

1. Install [Datumaro](https://github.com/openvinotoolkit/datumaro)
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## COCO import

Uploaded file: a single unpacked `*.json` or a zip archive with the structure described
[here](https://openvinotoolkit.github.io/datumaro/docs/formats/coco/#import-coco-dataset)
Uploaded file: a single unpacked `*.json` or a zip archive with the structure described above or
[here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset)
(without images).

- supported annotations: Polygons, Rectangles (if the `segmentation` field is empty)
- supported tasks: `instances`, `person_keypoints` (only segmentations will be imported), `panoptic`

# [MS COCO Keypoint Detection](https://cocodataset.org/#keypoints-2020)

- [Format specification](https://openvinotoolkit.github.io/datumaro/docs/formats/coco/)
- [Format specification](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html)

## COCO export

Downloaded file: a zip archive with the structure described [here](https://openvinotoolkit.github.io/datumaro/docs/formats/coco/#import-coco-dataset)
Downloaded file: a zip archive with the structure described [here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset)

- supported annotations: Skeletons
- supported attributes:
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## COCO import

Uploaded file: a single unpacked `*.json` or a zip archive with the structure described
[here](https://openvinotoolkit.github.io/datumaro/docs/formats/coco/#import-coco-dataset)
[here](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset)
(without images).

- supported annotations: Skeletons

## How to create a task from MS COCO dataset

1. Download the [MS COCO dataset](https://openvinotoolkit.github.io/datumaro/docs/formats/coco/#import-coco-dataset).
1. Download the [MS COCO dataset](https://openvinotoolkit.github.io/datumaro/latest/docs/data-formats/formats/coco.html#import-coco-dataset).

For example `val images` and `instances` annotations

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# CVAT

- [Format specification](/docs/manual/advanced/xml_format/)
- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/cvat_dataset)

This is the native CVAT annotation format. It supports all CVAT annotations
features, so it can be used to make data backups.

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- attributes are supported

- [Format specification](/docs/manual/advanced/xml_format/)

## CVAT for images export

Downloaded file: a ZIP file of the following structure:
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# [ICDAR13/15](https://rrc.cvc.uab.es/?ch=2)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/icdar_dataset)

## ICDAR13/15 export

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# [ImageNet](http://www.image-net.org)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/imagenet_dataset)

## ImageNet export

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- [Format specification for KITTI detection](https://s3.eu-central-1.amazonaws.com/avg-kitti/devkit_object.zip)
- [Format specification for KITTI segmentation](https://s3.eu-central-1.amazonaws.com/avg-kitti/devkit_semantics.zip)
- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/kitti_dataset)

- supported annotations:

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# [LabelMe](http://labelme.csail.mit.edu/Release3.0)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/labelme_dataset)

## LabelMe export

Downloaded file: a zip archive of the following structure:
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# [LFW](http://vis-www.cs.umass.edu/lfw/)

- Format specification available [here](http://vis-www.cs.umass.edu/lfw/README.txt)
- [Format specification](http://vis-www.cs.umass.edu/lfw/README.txt)
- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/lfw_dataset)

- Supported annotations: tags, points.

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# [Market-1501](https://www.aitribune.com/dataset/2018051063)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/market1501_dataset)

## Market-1501 export

Downloaded file: a zip archive of the following structure:
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# [MOT sequence](https://arxiv.org/pdf/1906.04567.pdf)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/mot_dataset)

## MOT export

Downloaded file: a zip archive of the following structure:
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# [MOTS PNG](https://www.vision.rwth-aachen.de/page/mots)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/mots_dataset)

## MOTS PNG export

Downloaded file: a zip archive of the following structure:
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# [Open Images](https://storage.googleapis.com/openimages/web/index.html)

- [Format specification](https://storage.googleapis.com/openimages/web/download.html)
- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/open_images_dataset)

- Supported annotations:

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# [TFRecord](https://www.tensorflow.org/tutorials/load_data/tfrecord)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/tf_detection_api_dataset)

TFRecord is a very flexible format, but we try to correspond the
format that used in
[TF object detection](https://github.com/tensorflow/models/tree/master/research/object_detection)
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# [VGGFace2](https://github.com/ox-vgg/vgg_face2)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/vgg_face2_dataset)

## VGGFace2 export

Downloaded file: a zip archive of the following structure:
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# [Pascal VOC](http://host.robots.ox.ac.uk/pascal/VOC/)

- [Format specification](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/devkit_doc.pdf)
- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/voc_dataset)

- supported annotations:

- Rectangles (detection and layout tasks)
- Tags (action- and classification tasks)
- Polygons (segmentation task)
- Rectangles (`detection` and `layout` tasks)
- Tags (`action-` and `classification` tasks)
- Polygons (`segmentation` task)

- supported attributes:

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# [WIDER Face](http://shuoyang1213.me/WIDERFACE/)

- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/widerface_dataset)

## WIDER Face export

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# [YOLO](https://pjreddie.com/darknet/yolo/)

- [Format specification](https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects)
- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/yolo_dataset)
- supported annotations: Rectangles

## YOLO export
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