未验证 提交 9fab8c5e 编写于 作者: M Maxim Zhiltsov 提交者: GitHub

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
- [ ] I have added a description of my changes into the
[CHANGELOG](https://github.com/opencv/cvat/blob/develop/CHANGELOG.md)
file
- [ ] I have updated the documentation accordingly
- [ ] I have added tests to cover my changes
- [ ] I have linked related issues (see [GitHub docs](

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- [ ] I have increased versions of npm packages if it is necessary

([cvat-canvas](https://github.com/opencv/cvat/tree/develop/cvat-canvas#versioning),

[cvat-core](https://github.com/opencv/cvat/tree/develop/cvat-core#versioning),

[cvat-data](https://github.com/opencv/cvat/tree/develop/cvat-data#versioning)
and

[cvat-ui](https://github.com/opencv/cvat/tree/develop/cvat-ui#versioning))

### License

- [ ] I submit _my code changes_ under the same [MIT License](
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project.
  Feel free to contact the maintainers if that's a concern.
上级 62334912
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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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......@@ -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
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......@@ -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
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......@@ -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:
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......@@ -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:
......
......@@ -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:
......
......@@ -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:
......
......@@ -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:
......
......@@ -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.
......
......@@ -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:
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......@@ -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:
......
......@@ -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:
......
......@@ -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:
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......@@ -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)
......
......@@ -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:
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......@@ -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:
......
......@@ -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:
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......@@ -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
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