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30
README.md
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@ -17,15 +17,15 @@ annotation team. Try it online [cvat.org](https://cvat.org).
## Documentation
- [Contributing](https://openvinotoolkit.github.io/cvat/docs/contributing/)
- [Installation guide](https://openvinotoolkit.github.io/cvat/docs/administration/basics/installation/)
- [Manual](https://openvinotoolkit.github.io/cvat/docs/manual/)
- [Django REST API documentation](https://openvinotoolkit.github.io/cvat/docs/administration/basics/rest_api_guide/)
- [Datumaro dataset framework](https://github.com/openvinotoolkit/datumaro/blob/develop/README.md)
- [Command line interface](https://openvinotoolkit.github.io/cvat/docs/manual/advanced/cli/)
- [XML annotation format](https://openvinotoolkit.github.io/cvat/docs/manual/advanced/xml_format/)
- [AWS Deployment Guide](https://openvinotoolkit.github.io/cvat/docs/administration/basics/aws-deployment-guide/)
- [Frequently asked questions](https://openvinotoolkit.github.io/cvat/docs/faq/)
- [Contributing](https://cvat-ai.github.io/cvat/docs/contributing/)
- [Installation guide](https://cvat-ai.github.io/cvat/docs/administration/basics/installation/)
- [Manual](https://cvat-ai.github.io/cvat/docs/manual/)
- [Django REST API documentation](https://cvat-ai.github.io/cvat/docs/administration/basics/rest_api_guide/)
- [Datumaro dataset framework](https://github.com/cvat-ai/datumaro/blob/develop/README.md)
- [Command line interface](https://cvat-ai.github.io/cvat/docs/manual/advanced/cli/)
- [XML annotation format](https://cvat-ai.github.io/cvat/docs/manual/advanced/xml_format/)
- [AWS Deployment Guide](https://cvat-ai.github.io/cvat/docs/administration/basics/aws-deployment-guide/)
- [Frequently asked questions](https://cvat-ai.github.io/cvat/docs/faq/)
- [Questions](#questions)
## Screencasts
@ -43,20 +43,20 @@ annotation team. Try it online [cvat.org](https://cvat.org).
## Supported annotation formats
Format selection is possible after clicking on the Upload annotation and Dump
annotation buttons. [Datumaro](https://github.com/openvinotoolkit/datumaro)
annotation buttons. [Datumaro](https://github.com/cvat-ai/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](https://openvinotoolkit.github.io/cvat/docs/manual/advanced/formats/).
[documentation](https://cvat-ai.github.io/cvat/docs/manual/advanced/formats/).
<!--lint disable maximum-line-length-->
| Annotation format | Import | Export |
| --------------------------------------------------------------------------------------------------------- | ------ | ------ |
| [CVAT for images](https://openvinotoolkit.github.io/cvat/docs/manual/advanced/xml_format/#annotation) | X | X |
| [CVAT for a video](https://openvinotoolkit.github.io/cvat/docs/manual/advanced/xml_format/#interpolation) | X | X |
| [Datumaro](https://github.com/openvinotoolkit/datumaro) | | X |
| [CVAT for images](https://cvat-ai.github.io/cvat/docs/manual/advanced/xml_format/#annotation) | X | X |
| [CVAT for a video](https://cvat-ai.github.io/cvat/docs/manual/advanced/xml_format/#interpolation) | X | X |
| [Datumaro](https://github.com/cvat-ai/datumaro) | | X |
| [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | X | X |
| Segmentation masks from [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/) | X | X |
| [YOLO](https://pjreddie.com/darknet/yolo/) | X | X |
@ -110,7 +110,7 @@ are visible to users.
Disabled features:
- [Analytics: management and monitoring of data annotation team](https://openvinotoolkit.github.io/cvat/docs/administration/advanced/analytics/)
- [Analytics: management and monitoring of data annotation team](https://cvat-ai.github.io/cvat/docs/administration/advanced/analytics/)
Limitations:

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cvat-cli/setup.py
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@ -48,7 +48,7 @@ setup(
description="Command-line client for CVAT",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/openvinotoolkit/cvat/",
url="https://github.com/cvat-ai/cvat/",
package_dir={"": "src"},
packages=find_packages(where="src"),
classifiers=[

2
cvat-ui/README.md
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@ -36,5 +36,5 @@ yarn run build
yarn run build --mode=development # without a minification
```
Important: You also have to run CVAT REST API server (please read `https://openvinotoolkit.github.io/cvat/docs/contributing/`)
Important: You also have to run CVAT REST API server (please read `https://cvat-ai.github.io/cvat/docs/contributing/`)
to correct working since UI gets all necessary data (tasks, users, annotations) from there

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cvat-ui/src/components/create-cloud-storage-page/manifests-manager.tsx
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@ -80,7 +80,7 @@ export default function ManifestsManager(props: Props): JSX.Element {
type='link'
target='_blank'
className='cvat-cloud-storage-help-button'
href='https://openvinotoolkit.github.io/cvat/docs/manual/advanced/dataset_manifest/'
href='https://cvat-ai.github.io/cvat/docs/manual/advanced/dataset_manifest/'
>
<QuestionCircleOutlined />
</Button>

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cvat-ui/src/consts.ts
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@ -4,18 +4,18 @@
const UNDEFINED_ATTRIBUTE_VALUE = '__undefined__';
const NO_BREAK_SPACE = '\u00a0';
const CHANGELOG_URL = 'https://github.com/openvinotoolkit/cvat/blob/develop/CHANGELOG.md';
const LICENSE_URL = 'https://github.com/openvinotoolkit/cvat/blob/develop/LICENSE';
const CHANGELOG_URL = 'https://github.com/cvat-ai/cvat/blob/develop/CHANGELOG.md';
const LICENSE_URL = 'https://github.com/cvat-ai/cvat/blob/develop/LICENSE';
const GITTER_URL = 'https://gitter.im/opencv-cvat';
const GITTER_PUBLIC_URL = 'https://gitter.im/opencv-cvat/public';
const FORUM_URL = 'https://software.intel.com/en-us/forums/intel-distribution-of-openvino-toolkit';
const GITHUB_URL = 'https://github.com/openvinotoolkit/cvat';
const GITHUB_IMAGE_URL = 'https://github.com/openvinotoolkit/cvat/raw/develop/site/content/en/images/cvat.jpg';
const GUIDE_URL = 'https://openvinotoolkit.github.io/cvat/docs';
const GITHUB_URL = 'https://github.com/cvat-ai/cvat';
const GITHUB_IMAGE_URL = 'https://github.com/cvat-ai/cvat/raw/develop/site/content/en/images/cvat.jpg';
const GUIDE_URL = 'https://cvat-ai.github.io/cvat/docs';
const SHARE_MOUNT_GUIDE_URL =
'https://openvinotoolkit.github.io/cvat/docs/administration/basics/installation/#share-path';
'https://cvat-ai.github.io/cvat/docs/administration/basics/installation/#share-path';
const NUCLIO_GUIDE =
'https://openvinotoolkit.github.io/cvat//docs/administration/advanced/installation_automatic_annotation/';
'https://cvat-ai.github.io/cvat//docs/administration/advanced/installation_automatic_annotation/';
const CANVAS_BACKGROUND_COLORS = ['#ffffff', '#f1f1f1', '#e5e5e5', '#d8d8d8', '#CCCCCC', '#B3B3B3', '#999999'];
const NEW_LABEL_COLOR = '#b3b3b3';
const LATEST_COMMENTS_SHOWN_QUICK_ISSUE = 3;

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cvat/settings/base.py
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@ -534,7 +534,7 @@ SPECTACULAR_SETTINGS = {
'TOS': 'https://www.google.com/policies/terms/',
'EXTERNAL_DOCS': {
'description': 'CVAT documentation',
'url': 'https://openvinotoolkit.github.io/cvat/docs/',
'url': 'https://cvat-ai.github.io/cvat/docs/',
},
# OTHER SETTINGS
# https://drf-spectacular.readthedocs.io/en/latest/settings.html

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package.json
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@ -113,14 +113,14 @@
},
"repository": {
"type": "git",
"url": "git+https://github.com/openvinotoolkit/cvat.git"
"url": "git+https://github.com/cvat-ai/cvat.git"
},
"author": "Intel",
"license": "MIT",
"bugs": {
"url": "https://github.com/openvinotoolkit/cvat/issues"
"url": "https://github.com/cvat-ai/cvat/issues"
},
"homepage": "https://github.com/openvinotoolkit/cvat#readme",
"homepage": "https://github.com/cvat-ai/cvat#readme",
"resolutions": {
"@types/react": "^17.0.30",
"@types/react-dom": "^18.0.5",

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serverless/openvino/dextr/nuclio/function.yaml
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@ -7,7 +7,7 @@ metadata:
spec:
framework: openvino
min_pos_points: 4
animated_gif: https://raw.githubusercontent.com/openvinotoolkit/cvat/0fbb19ae3846a017853d52e187f0ce149adced7d/site/content/en/images/dextr_example.gif
animated_gif: https://raw.githubusercontent.com/cvat-ai/cvat/0fbb19ae3846a017853d52e187f0ce149adced7d/site/content/en/images/dextr_example.gif
help_message: The interactor allows to get a mask of an object using its extreme points (more or equal than 4). You can add a point left-clicking the image
spec:

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serverless/pytorch/saic-vul/fbrs/nuclio/function.yaml
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@ -8,7 +8,7 @@ metadata:
framework: pytorch
min_pos_points: 1
min_neg_points: 0
animated_gif: https://raw.githubusercontent.com/openvinotoolkit/cvat/0fbb19ae3846a017853d52e187f0ce149adced7d/site/content/en/images/fbrs_example.gif
animated_gif: https://raw.githubusercontent.com/cvat-ai/cvat/0fbb19ae3846a017853d52e187f0ce149adced7d/site/content/en/images/fbrs_example.gif
help_message: The interactor allows to get a mask for an object using positive points, and negative points
spec:

2
serverless/pytorch/saic-vul/hrnet/nuclio/function-gpu.yaml
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@ -8,7 +8,7 @@ metadata:
framework: pytorch
min_pos_points: 1
min_neg_points: 0
animated_gif: https://raw.githubusercontent.com/openvinotoolkit/cvat/develop/site/content/en/images/hrnet_example.gif
animated_gif: https://raw.githubusercontent.com/cvat-ai/cvat/develop/site/content/en/images/hrnet_example.gif
help_message: The interactor allows to get a mask for an object using positive points, and negative points
spec:

2
serverless/pytorch/shiyinzhang/iog/nuclio/function.yaml
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@ -9,7 +9,7 @@ metadata:
min_pos_points: 1
min_neg_points: 0
startswith_box: true
animated_gif: https://raw.githubusercontent.com/openvinotoolkit/cvat/0fbb19ae3846a017853d52e187f0ce149adced7d/site/content/en/images/iog_example.gif
animated_gif: https://raw.githubusercontent.com/cvat-ai/cvat/0fbb19ae3846a017853d52e187f0ce149adced7d/site/content/en/images/iog_example.gif
help_message: The interactor allows to get a mask of an object using its wrapping boundig box, positive, and negative points inside it
spec:

8
site/config.toml
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@ -52,7 +52,7 @@ anchor = "smart"
[[menu.main]]
name = "GitHub"
weight = 60
url = "https://github.com/openvinotoolkit/cvat"
url = "https://github.com/cvat-ai/cvat"
pre = "<i class='fab fa-github'></i>"
[services]
@ -113,9 +113,9 @@ version = "0.0"
url_latest_version = "https://example.com"
# Repository configuration (URLs for in-page links to opening issues and suggesting changes)
github_repo = "https://github.com/openvinotoolkit/cvat"
github_repo = "https://github.com/cvat-ai/cvat"
# An optional link to a related project repo. For example, the sibling repository where your product code lives.
github_project_repo = "https://github.com/openvinotoolkit/cvat"
github_project_repo = "https://github.com/cvat-ai/cvat"
# Specify a value here if your content directory is not in your repo's root directory
github_subdir = "site"
@ -186,7 +186,7 @@ enable = false
# Developer relevant links. These will show up on right side of footer and in the community page if you have one.
[[params.links.developer]]
name = "GitHub"
url = "https://github.com/openvinotoolkit/cvat"
url = "https://github.com/cvat-ai/cvat"
icon = "fab fa-github"
desc = "Development takes place here!"
[[params.links.developer]]

2
site/content/en/about/_index.html
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@ -144,7 +144,7 @@ menu:
We have is a separate <a href="https://gitter.im/opencv-cvat/dev">Gitter chat for developers</a> to discuss the development of CVAT.
</li>
<li>
Visit our <a href="https://github.com/openvinotoolkit/cvat">GitHub</a> repository.
Visit our <a href="https://github.com/cvat-ai/cvat">GitHub</a> repository.
</li>
</ul>
</div>

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site/content/en/docs/_index.md
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@ -32,7 +32,7 @@ Answers to frequently asked questions.
{{% /blocks/feature %}}
{{% blocks/feature icon="fab fa-github" title="[GitHub Repository](https://github.com/openvinotoolkit/cvat)" %}}
{{% blocks/feature icon="fab fa-github" title="[GitHub Repository](https://github.com/cvat-ai/cvat)" %}}
Computer Vision Annotation Tool GitHub repository.

2
site/content/en/docs/administration/advanced/analytics.md
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@ -5,7 +5,7 @@
title: 'Installation Analytics'
linkTitle: 'Installation Analytics'
weight: 2
description: 'Instructions for deployment and customization of Analytics. This section on [GitHub](https://github.com/openvinotoolkit/cvat/tree/develop/components/analytics).'
description: 'Instructions for deployment and customization of Analytics. This section on [GitHub](https://github.com/cvat-ai/cvat/tree/develop/components/analytics).'
---

6
site/content/en/docs/administration/advanced/installation_automatic_annotation.md
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@ -31,7 +31,7 @@ description: 'Information about the installation of components needed for semi-a
- You have to install `nuctl` command line tool to build and deploy serverless
functions. Download [version 1.8.14](https://github.com/nuclio/nuclio/releases/tag/1.8.14).
It is important that the version you download matches the version in
[docker-compose.serverless.yml](https://github.com/openvinotoolkit/cvat/blob/develop/components/serverless/docker-compose.serverless.yml).
[docker-compose.serverless.yml](https://github.com/cvat-ai/cvat/blob/develop/components/serverless/docker-compose.serverless.yml).
For example, using wget.
```bash
@ -69,7 +69,7 @@ description: 'Information about the installation of components needed for semi-a
**Note:**
- See [deploy_cpu.sh](https://github.com/openvinotoolkit/cvat/blob/develop/serverless/deploy_cpu.sh)
- See [deploy_cpu.sh](https://github.com/cvat-ai/cvat/blob/develop/serverless/deploy_cpu.sh)
for more examples.
#### GPU Support
@ -92,7 +92,7 @@ description: 'Information about the installation of components needed for semi-a
**Note:**
- The number of GPU deployed functions will be limited to your GPU memory.
- See [deploy_gpu.sh](https://github.com/openvinotoolkit/cvat/blob/develop/serverless/deploy_gpu.sh)
- See [deploy_gpu.sh](https://github.com/cvat-ai/cvat/blob/develop/serverless/deploy_gpu.sh)
script for more examples.
- For some models (namely [SiamMask](/docs/manual/advanced/ai-tools#trackers)) you need an [Nvidia driver](https://www.nvidia.com/en-us/drivers/unix/)
version greater than or equal to 450.80.02.

2
site/content/en/docs/administration/basics/AWS-Deployment-Guide.md
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@ -11,7 +11,7 @@ There are two ways of deploying the CVAT.
One of the easy ways to launch CVAT with the tf-annotation app is to use AWS P3 instances,
which provides the NVIDIA GPU.
Read more about [P3 instances here.](https://aws.amazon.com/about-aws/whats-new/2017/10/introducing-amazon-ec2-p3-instances/)
Overall setup instruction is explained in [main readme file](https://github.com/openvinotoolkit/cvat/),
Overall setup instruction is explained in [main readme file](https://github.com/cvat-ai/cvat/),
except Installing Nvidia drivers.
So we need to download the drivers and install it.
For Amazon P3 instances, download the Nvidia Drivers from Nvidia website.

2
site/content/en/docs/administration/basics/installation.md
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@ -389,7 +389,7 @@ your cloud storage as a FUSE and use it later as a share.
You can enable email verification for newly registered users.
Specify these options in the
[settings file](https://github.com/openvinotoolkit/cvat/blob/develop/cvat/settings/base.py) to configure Django allauth
[settings file](https://github.com/cvat-ai/cvat/blob/develop/cvat/settings/base.py) to configure Django allauth
to enable email verification (ACCOUNT_EMAIL_VERIFICATION = 'mandatory').
Access is denied until the user's email address is verified.

2
site/content/en/docs/contributing/development-environment.md
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@ -51,7 +51,7 @@ description: 'Installing a development environment for different operating syste
- Install CVAT on your local host:
```bash
git clone https://github.com/openvinotoolkit/cvat
git clone https://github.com/cvat-ai/cvat
cd cvat && mkdir logs keys
python3 -m venv .env
. .env/bin/activate

8
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@ -2,17 +2,17 @@
title: 'How to add a new annotation format support'
linkTitle: 'New annotation format support'
weight: 10
description: 'Instructions on adding support for new annotation formats. This section on [GitHub](https://github.com/openvinotoolkit/cvat/tree/develop/cvat/apps/dataset_manager/formats).'
description: 'Instructions on adding support for new annotation formats. This section on [GitHub](https://github.com/cvat-ai/cvat/tree/develop/cvat/apps/dataset_manager/formats).'
---
1. Add a python script to `dataset_manager/formats`
2. Add an import statement to [registry.py](https://github.com/openvinotoolkit/cvat/tree/develop/cvat/apps/dataset_manager/formats/registry.py).
2. Add an import statement to [registry.py](https://github.com/cvat-ai/cvat/tree/develop/cvat/apps/dataset_manager/formats/registry.py).
3. Implement some importers and exporters as the format requires.
Each format is supported by an importer and exporter.
It can be a function or a class decorated with
`importer` or `exporter` from [registry.py](https://github.com/openvinotoolkit/cvat/tree/develop/cvat/apps/dataset_manager/formats/registry.py).
`importer` or `exporter` from [registry.py](https://github.com/cvat-ai/cvat/tree/develop/cvat/apps/dataset_manager/formats/registry.py).
Examples:
```python
@ -54,7 +54,7 @@ Exporter arguments:
- _options_ - format-specific options. `save_images` is the option to
distinguish if dataset or just annotations are requested.
[`TaskData`](https://github.com/openvinotoolkit/cvat/blob/develop/cvat/apps/dataset_manager/bindings.py) provides
[`TaskData`](https://github.com/cvat-ai/cvat/blob/develop/cvat/apps/dataset_manager/bindings.py) provides
many task properties and interfaces to add and read task annotations.
Public members:

4
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@ -101,7 +101,7 @@ volumes:
## How to make unassigned tasks not visible to all users
Set [reduce_task_visibility](https://github.com/openvinotoolkit/cvat/blob/develop/cvat/settings/base.py#L424)
Set [reduce_task_visibility](https://github.com/cvat-ai/cvat/blob/develop/cvat/settings/base.py#L455)
variable to `True`.
## Where are uploaded images/videos stored
@ -135,7 +135,7 @@ Follow this [guide](/docs/administration/basics/installation/#windows-10).
## I do not have the Analytics tab on the header section. How can I add analytics
You should build CVAT images with ['Analytics' component](https://github.com/openvinotoolkit/cvat/tree/develop/components/analytics).
You should build CVAT images with ['Analytics' component](https://github.com/cvat-ai/cvat/tree/develop/components/analytics).
## How to upload annotations to an entire task from UI when there are multiple jobs in the task

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@ -33,7 +33,7 @@ There are several formats in CVAT that can be used to export masks:
- `MOTS`
- `ICDAR`
- `COCO` (RLE-encoded instance masks, [guide](/docs/manual/advanced/formats/format-coco))
- `TFRecord` ([over Datumaro](https://github.com/openvinotoolkit/datumaro/blob/develop/docs/user_manual.md), [guide](/docs/manual/advanced/formats/format-tfrecord)):
- `TFRecord` ([over Datumaro](https://github.com/cvat-ai/datumaro/blob/develop/docs/user_manual.md), [guide](/docs/manual/advanced/formats/format-tfrecord)):
- `Datumaro`
An example of exported masks (in the `Segmentation Mask` format):

4
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@ -2,7 +2,7 @@
title: 'Command line interface (CLI)'
linkTitle: 'CLI'
weight: 29
description: 'Guide to working with CVAT tasks in the command line interface. This section on [GitHub](https://github.com/openvinotoolkit/cvat/tree/develop/cvat-cli).'
description: 'Guide to working with CVAT tasks in the command line interface. This section on [GitHub](https://github.com/cvat-ai/cvat/tree/develop/cvat-cli).'
---
## Description
@ -28,7 +28,7 @@ To access the CLI, you need to have python in environment,
as well as a clone of the CVAT repository and the necessary modules:
```bash
pip install 'git+https://github.com/openvinotoolkit/cvat#subdirectory=cvat-cli'
pip install 'git+https://github.com/cvat-ai/cvat#subdirectory=cvat-cli'
```
You can get help with `cvat-cli --help`.

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@ -5,7 +5,7 @@
title: 'Simple command line to prepare dataset manifest file'
linkTitle: 'Dataset manifest'
weight: 30
description: This section on [GitHub](https://github.com/openvinotoolkit/cvat/tree/develop/utils/dataset_manifest)
description: This section on [GitHub](https://github.com/cvat-ai/cvat/tree/develop/utils/dataset_manifest)
---

2
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@ -5,7 +5,7 @@ weight: 1.5
# Datumaro format
[Datumaro](https://github.com/openvinotoolkit/datumaro/) is a tool, which can
[Datumaro](https://github.com/cvat-ai/datumaro/) is a tool, which can
help with complex dataset and annotation transformations, format conversions,
dataset statistics, merging, custom formats etc. It is used as a provider
of dataset support in CVAT, so basically, everything possible in CVAT

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@ -49,7 +49,7 @@ item {
...
```
- supported annotations: Rectangles, Polygons (as masks, manually over [Datumaro](https://github.com/openvinotoolkit/datumaro/blob/develop/docs/user_manual.md))
- supported annotations: Rectangles, Polygons (as masks, manually over [Datumaro](https://github.com/cvat-ai/datumaro/blob/develop/docs/user_manual.md))
How to export masks:
1. Export annotations in `Datumaro` format

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@ -976,14 +976,14 @@ you can use the Ubuntu subsystem, for this do the following:
[opencv-python-github]: https://github.com/opencv/opencv-python
[detectron2-tutorial]: https://detectron2.readthedocs.io/en/latest/tutorials/getting_started.html
[retinanet-model-zoo]: https://github.com/facebookresearch/detectron2/blob/master/MODEL_ZOO.md#retinanet
[faster-rcnn-function]: https://raw.githubusercontent.com/openvinotoolkit/cvat/38b774046d41d604ed85a521587e4bacce61b69c/serverless/tensorflow/faster_rcnn_inception_v2_coco/nuclio/function.yaml
[faster-rcnn-function]: https://raw.githubusercontent.com/cvat-ai/cvat/38b774046d41d604ed85a521587e4bacce61b69c/serverless/tensorflow/faster_rcnn_inception_v2_coco/nuclio/function.yaml
[nuclio-doc]: https://nuclio.io/docs/latest/reference/function-configuration/function-configuration-reference/
[nuclio-http-trigger-doc]: https://nuclio.io/docs/latest/reference/triggers/http/
[nuclio-bkms-doc]: https://nuclio.io/docs/latest/concepts/best-practices-and-common-pitfalls/
[retinanet-function-yaml]: https://github.com/openvinotoolkit/cvat/blob/b2f616859ca64687c385e636b4a25014fbb9d17c/serverless/pytorch/facebookresearch/detectron2/retinanet/nuclio/function.yaml
[retinanet-main-py]: https://github.com/openvinotoolkit/cvat/blob/b2f616859ca64687c385e636b4a25014fbb9d17c/serverless/pytorch/facebookresearch/detectron2/retinanet/nuclio/main.py
[retinanet-function-yaml]: https://github.com/cvat-ai/cvat/blob/b2f616859ca64687c385e636b4a25014fbb9d17c/serverless/pytorch/facebookresearch/detectron2/retinanet/nuclio/function.yaml
[retinanet-main-py]: https://github.com/cvat-ai/cvat/blob/b2f616859ca64687c385e636b4a25014fbb9d17c/serverless/pytorch/facebookresearch/detectron2/retinanet/nuclio/main.py
[nuclio-homepage]: https://nuclio.io/
[cvat-builtin-serverless]: https://github.com/openvinotoolkit/cvat/tree/develop/serverless
[cvat-builtin-serverless]: https://github.com/cvat-ai/cvat/tree/develop/serverless
[cvat-auto-annotation-guide]: /docs/administration/advanced/installation_automatic_annotation
[cvat-installation-guide-windows-10]: /docs/administration/basics/installation/#windows-10
[cvat-installation-guide-ubuntu-1804]: /docs/administration/basics/installation/#ubuntu-1804-x86_64amd64
@ -991,8 +991,8 @@ you can use the Ubuntu subsystem, for this do the following:
[pascal-voc-format]: http://host.robots.ox.ac.uk/pascal/VOC/voc2012/htmldoc/index.html
[faas-wiki]: https://en.wikipedia.org/wiki/Function_as_a_service
[cvat-ai-tools-user-guide]: /docs/manual/advanced/ai-tools/
[cvat-github]: https://github.com/openvinotoolkit/cvat
[siammask-serverless]: https://github.com/openvinotoolkit/cvat/tree/develop/serverless/pytorch/foolwood/siammask/nuclio
[cvat-github]: https://github.com/cvat-ai/cvat
[siammask-serverless]: https://github.com/cvat-ai/cvat/tree/develop/serverless/pytorch/foolwood/siammask/nuclio
[vtest-avi]: https://github.com/opencv/opencv/blob/master/samples/data/vtest.avi?raw=true
[intel-openvino-url]: https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html
[cvat-auto-annotation-user-guide]: /docs/manual/advanced/automatic-annotation/

2
site/content/en/docs/manual/basics/attach-cloud-storage.md
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@ -344,7 +344,7 @@ In the window that appears, select the created bucket and click export.
### Prepare manifest file
Now you need to prepare a manifest file. I used [AWS cli](https://aws.amazon.com/cli/) and
[script for prepare manifest file](https://github.com/openvinotoolkit/cvat/tree/develop/utils/dataset_manifest).
[script for prepare manifest file](https://github.com/cvat-ai/cvat/tree/develop/utils/dataset_manifest).
Perform the installation using the manual [aws-shell](https://github.com/awslabs/aws-shell),
I used `aws-cli 1.20.49` `Python 3.7.9` `Windows 10`.
You can configure credentials by running `aws configure`.

2
site/content/en/docs/manual/basics/interface.md
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@ -52,4 +52,4 @@ If you perform impossible actions, you may receive an error message.
The message may contain information about the error
or a prompt to open the browser console (shortcut `F12`) for information.
If you encounter a bug that you can't solve yourself,
you can [create an issue on GitHub](https://github.com/openvinotoolkit/cvat/issues/new).
you can [create an issue on GitHub](https://github.com/cvat-ai/cvat/issues/new).

6
site/package.json
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@ -11,12 +11,12 @@
},
"repository": {
"type": "git",
"url": "git+https://github.com/openvinotoolkit/cvat.git"
"url": "git+https://github.com/cvat-ai/cvat.git"
},
"author": "Intel",
"license": "MIT",
"bugs": {
"url": "https://github.com/openvinotoolkit/cvat/issues"
"url": "https://github.com/cvat-ai/cvat/issues"
},
"homepage": "https://github.com/openvinotoolkit/cvat#readme"
"homepage": "https://github.com/cvat-ai/cvat#readme"
}

2
tests/cypress/integration/actions_tasks2/case_76_try_create_task_incorrect_dataset_repo.js
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@ -21,7 +21,7 @@ context('Try to create a task with an incorrect dataset repository.', () => {
const directoryToArchive = imagesFolder;
const incorrectDatasetRepoUrl = 'dummyrepo.local';
const incorrectDatasetRepoUrlHttps = 'https://dummyrepo.local';
const repositoryWithMissingAccess = 'https://github.com/openvinotoolkit/cvat';
const repositoryWithMissingAccess = 'https://github.com/cvat-ai/cvat';
before(() => {
cy.visit('auth/login');

2
tests/cypress/integration/actions_tasks3/case_46_create_task_with_files_from_remote_sources.js
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@ -9,7 +9,7 @@ context('Create a task with files from remote sources.', () => {
const labelName = `Case ${caseId}`;
const taskName = `New annotation task for ${labelName}`;
const wrongUrl =
'https://raw.githubusercontent.com/openvinotoolkit/cvat/v1.2.0/cvat/apps/documentation/static/documentation/images/cvatt.jpg';
'https://raw.githubusercontent.com/cvat-ai/cvat/v1.2.0/cvat/apps/documentation/static/documentation/images/cvatt.jpg';
const correctUrl = wrongUrl.replace('cvatt.jpg', 'cvat.jpg');
before(() => {

2
tests/cypress/integration/actions_users/case_38_feedback_button.js
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@ -23,7 +23,7 @@ context('Check feedback button.', () => {
.within(() => {
cy.get('a').then(($a) => {
expect($a.length).be.equal(3);
expect($a[0].href).be.eq('https://github.com/openvinotoolkit/cvat');
expect($a[0].href).be.eq('https://github.com/cvat-ai/cvat');
expect($a[1].href).be.eq('https://gitter.im/opencv-cvat/public');
expect($a[2].href).be.eq($a[1].href);
});

2
tests/rest_api/test_remote_url.py
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@ -56,6 +56,6 @@ class TestGetAnalytics:
def test_can_create(self, find_users):
user = find_users(privilege='admin')[0]['username']
remote_resources = ['https://openvinotoolkit.github.io/cvat/favicons/favicon-32x32.png']
remote_resources = ['https://cvat-ai.github.io/cvat/favicons/favicon-32x32.png']
self._test_can_create(user, self.task_id, remote_resources)

2
utils/README.md
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@ -5,4 +5,4 @@
This folder contains some useful utilities for Computer Vision Annotation Tool (CVAT).
To read about a certain utility please choose a link:
- [Command line interface for working with CVAT tasks](https://openvinotoolkit.github.io/cvat/docs/manual/advanced/cli/)
- [Command line interface for working with CVAT tasks](https://cvat-ai.github.io/cvat/docs/manual/advanced/cli/)

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