Add dataset examples and update some links in docs

site/content/en/docs/manual/advanced/formats/format-camvid.md

@@ -5,6 +5,8 @@ weight: 10
 
 # [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:

site/content/en/docs/manual/advanced/formats/format-cityscapes.md

@@ -6,6 +6,7 @@ weight: 16
 # [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
 

site/content/en/docs/manual/advanced/formats/format-coco.md

@@ -6,10 +6,33 @@ weight: 5
 # [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:
@@ -21,7 +44,7 @@ Downloaded file: a zip archive with the structure described [here](https://openv
   - `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)
@@ -35,19 +58,20 @@ keypoint lists (without the `visibility` COCO flag).
 
 ## 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:
@@ -62,14 +86,14 @@ Downloaded file: a zip archive with the structure described [here](https://openv
 ## 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
 

site/content/en/docs/manual/advanced/formats/format-cvat.md

@@ -5,6 +5,9 @@ weight: 1
 
 # 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.
 
@@ -16,8 +19,6 @@ features, so it can be used to make data backups.
 
 - attributes are supported
 
-- [Format specification](/docs/manual/advanced/xml_format/)
-
 ## CVAT for images export
 
 Downloaded file: a ZIP file of the following structure:

site/content/en/docs/manual/advanced/formats/format-icdar.md

@@ -5,6 +5,8 @@ weight: 14
 
 # [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
 
 Downloaded file: a zip archive of the following structure:

site/content/en/docs/manual/advanced/formats/format-imagenet.md

@@ -5,6 +5,8 @@ weight: 9
 
 # [ImageNet](http://www.image-net.org)
 
+- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/imagenet_dataset)
+
 ## ImageNet export
 
 Downloaded file: a zip archive of the following structure:

site/content/en/docs/manual/advanced/formats/format-kitti.md

@@ -7,6 +7,7 @@ weight: 17
 
 - [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:
 

site/content/en/docs/manual/advanced/formats/format-labelme.md

@@ -5,6 +5,8 @@ weight: 2
 
 # [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:

site/content/en/docs/manual/advanced/formats/format-lfw.md

@@ -5,7 +5,8 @@ weight: 17
 
 # [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.
 

site/content/en/docs/manual/advanced/formats/format-market1501.md

@@ -5,6 +5,8 @@ weight: 13
 
 # [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:

site/content/en/docs/manual/advanced/formats/format-mot.md

@@ -5,6 +5,8 @@ weight: 3
 
 # [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:

site/content/en/docs/manual/advanced/formats/format-mots.md

@@ -5,6 +5,8 @@ weight: 4
 
 # [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:

site/content/en/docs/manual/advanced/formats/format-openimages.md

@@ -6,6 +6,7 @@ weight: 15
 # [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:
 

site/content/en/docs/manual/advanced/formats/format-tfrecord.md

@@ -5,6 +5,8 @@ weight: 8
 
 # [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)

site/content/en/docs/manual/advanced/formats/format-vggface2.md

@@ -5,6 +5,8 @@ weight: 12
 
 # [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:

site/content/en/docs/manual/advanced/formats/format-voc.md

@@ -6,12 +6,13 @@ weight: 6
 # [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:
 

site/content/en/docs/manual/advanced/formats/format-widerface.md

@@ -5,6 +5,8 @@ weight: 9
 
 # [WIDER Face](http://shuoyang1213.me/WIDERFACE/)
 
+- [Dataset examples](https://github.com/cvat-ai/datumaro/tree/v0.3/tests/assets/widerface_dataset)
+
 ## WIDER Face export
 
 Downloaded file: a zip archive of the following structure:

site/content/en/docs/manual/advanced/formats/format-yolo.md

@@ -6,6 +6,7 @@ weight: 7
 # [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