210 lines
22 KiB
Markdown
210 lines
22 KiB
Markdown
---
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title: 'CVAT Overview'
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linkTitle: 'Introduction to CVAT'
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weight: 1
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description: 'The open-source tool for image and video annotation'
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---
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Machine learning systems often struggle due to poor-quality data. Without effective tools,
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improving a model can be tough and inefficient.
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[**CVAT**](https://www.cvat.ai/) **is a** versatile **tool** for
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**annotating images and videos**, serving the computer
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vision community worldwide.
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Our goal is to help developers, businesses,
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and organizations globally by using a Data-centric AI approach.
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CVAT offers three versions:
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- [**CVAT Online**](https://app.cvat.ai/): Start online with CVAT,
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**available for free**. You can also choose a [**subscription**](https://www.cvat.ai/pricing/cvat-online)
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for **unlimited data**, **collaboration**, **auto-annotations**, and [**more**](https://www.cvat.ai/post/cvat-ai-pricing-plans-choosing-the-right-plan-for-your-needs).
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- **Self-hosted CVAT Community Edition**: Follow the
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{{< ilink "/docs/administration/basics/installation" "**Self-hosted Installation Guide**" >}}
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for setup.
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- **Self-hosted CVAT Enterprise Edition**: We provide [**Enterprise-level support**](https://www.cvat.ai/pricing/on-prem)
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for this version, **including premium features** like **SSO**, **LDAP**, advanced integrations with
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[**Roboflow and HuggingFace**](https://www.cvat.ai/post/integrating-hugging-face-and-roboflow-models),
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and **advanced analytics**. We also offer **professional training** and **24-hour SLA support**.
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See:
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- [Tools and formats](#tools-and-formats)
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- [Supported formats](#supported-formats)
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- [Annotation tools](#annotation-tools)
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- [Automated labeling](#automated-labeling)
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- [Useful links](#useful-links)
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- [Online](#online)
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- [Self-Hosted](#self-hosted)
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- [Integrations](#integrations)
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- [License Information](#license-information)
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- [Get in touch](#get-in-touch)
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## Tools and formats
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CVAT stands as a comprehensive tool for image and video annotation,
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essential for various computer vision tasks.
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It emphasizes user-friendliness, adaptability, and compatibility with
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a range of formats and tools.
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### Supported formats
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CVAT's supports the following formats:
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- **For 3D**: `.pcd`, `.bin`
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- **For image**: everything supported by the Python
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[**Pillow library**](https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html),
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including formats like `JPEG`, `PNG`, `BMP`, `GIF`, `PPM`and `TIFF`.
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- **For video**: all formats, supported by ffmpeg, including `MP4`, `AVI`, and `MOV`.
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For annotation export and import formats, see
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{{< ilink "/docs/manual/advanced/formats" "**Export annotations and data from CVAT**" >}}
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### Annotation tools
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CVAT offers a wide range of annotation tools, each catering to different aspects of
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image and video labeling:
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| Annotation Tool | Use Cases |
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| -------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------- |
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| {{< ilink "/docs/manual/advanced/3d-object-annotation-advanced" "**3D Object Annotation**" >}} | Ideal for projects that require depth perception and volume estimation, like autonomous vehicle training. |
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| {{< ilink "/docs/manual/advanced/attribute-annotation-mode-advanced" "**Attribute Annotation Mode**" >}} | Useful for adding detailed information to objects, like color, size, or other specific characteristics. |
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| {{< ilink "/docs/manual/advanced/annotation-with-rectangles" "**Annotation with Rectangles**" >}} | Best for simple object detection where objects have a box-like shape, such as detecting windows in a building. |
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| {{< ilink "/docs/manual/advanced/annotation-with-polygons" "**Annotation with Polygons**" >}} | Suited for complex shapes in images, like outlining geographical features in maps or detailed product shapes. |
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| {{< ilink "/docs/manual/advanced/annotation-with-polylines" "**Annotation with Polylines**" >}} | Great for annotating linear objects like roads, pathways, or limbs in pose estimation. |
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| {{< ilink "/docs/manual/advanced/annotation-with-ellipses" "**Annotation with Ellipses**" >}} | Ideal for objects like plates, balls, or eyes, where a circular or oval annotation is needed. |
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| {{< ilink "/docs/manual/advanced/annotation-with-cuboids" "**Annotation with Cuboids**" >}} | Useful for 3D objects in 2D images, like boxes or furniture in room layouts. |
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| {{< ilink "/docs/manual/advanced/skeletons" "**Annotation with Skeletons**" >}} | Ideal for human pose estimation, animation, and movement analysis in sports or medical fields. |
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| {{< ilink "/docs/manual/advanced/annotation-with-brush-tool" "**Annotation with Brush Tool**" >}} | Perfect for intricate and detailed annotations where precision is key, such as in medical imaging. |
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| {{< ilink "/docs/manual/advanced/annotation-with-tags" "**Annotation with Tags**" >}} | Useful for image and video classification tasks, like identifying scenes or themes in a dataset. |
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These tools make CVAT a versatile platform for a range of annotation
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needs, from basic labeling to complex, multidimensional
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tasks in advanced computer vision projects.
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## Automated labeling
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CVAT has an automated labeling features, enhancing the annotation process significantly,
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potentially speeding it up by up to 10 times.
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{{% alert title="Note" color="primary" %}}
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For more information,
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see {{< ilink "/docs/manual/advanced/ai-tools" "**OpenCV and AI Tools**" >}}
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{{% /alert %}}
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Below is a detailed table of the supported algorithms and the platforms they operate on:
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| Algorithm Name | Category | Framework | CPU Support | GPU Support |
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| --------------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | ---------- | ----------- | ----------- |
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| [Segment Anything](https://github.com/cvat-ai/cvat/tree/develop/serverless/pytorch/facebookresearch/sam/nuclio) | Interactor | PyTorch | ✔️ | ✔️ |
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| [Deep Extreme Cut](https://github.com/cvat-ai/cvat/tree/develop/serverless/openvino/dextr/nuclio) | Interactor | OpenVINO | ✔️ | |
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| [Faster RCNN](https://github.com/cvat-ai/cvat/tree/develop/serverless/openvino/omz/public/faster_rcnn_inception_resnet_v2_atrous_coco/nuclio) | Detector | OpenVINO | ✔️ | |
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| [Mask RCNN](https://github.com/cvat-ai/cvat/tree/develop/serverless/openvino/omz/public/mask_rcnn_inception_resnet_v2_atrous_coco/nuclio) | Detector | OpenVINO | ✔️ | |
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| [YOLO v3](https://github.com/cvat-ai/cvat/tree/develop/serverless/openvino/omz/public/yolo-v3-tf/nuclio) | Detector | OpenVINO | ✔️ | |
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| [YOLO v7](https://github.com/cvat-ai/cvat/tree/develop/serverless/onnx/WongKinYiu/yolov7/nuclio) | Detector | ONNX | ✔️ | ✔️ |
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| [Object Reidentification](https://github.com/cvat-ai/cvat/tree/develop/serverless/openvino/omz/intel/person-reidentification-retail-0277/nuclio) | ReID | OpenVINO | ✔️ | |
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| [Semantic Segmentation for ADAS](https://github.com/cvat-ai/cvat/tree/develop/serverless/openvino/omz/intel/semantic-segmentation-adas-0001/nuclio) | Detector | OpenVINO | ✔️ | |
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| [Text Detection v4](https://github.com/cvat-ai/cvat/tree/develop/serverless/openvino/omz/intel/text-detection-0004/nuclio) | Detector | OpenVINO | ✔️ | |
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| [SiamMask](https://github.com/cvat-ai/cvat/tree/develop/serverless/pytorch/foolwood/siammask/nuclio) | Tracker | PyTorch | ✔️ | ✔️ |
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| [TransT](https://github.com/cvat-ai/cvat/tree/develop/serverless/pytorch/dschoerk/transt/nuclio) | Tracker | PyTorch | ✔️ | ✔️ |
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| [Inside-Outside Guidance](https://github.com/cvat-ai/cvat/tree/develop/serverless/pytorch/shiyinzhang/iog/nuclio) | Interactor | PyTorch | ✔️ | |
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| [Faster RCNN](https://github.com/cvat-ai/cvat/tree/develop/serverless/tensorflow/faster_rcnn_inception_v2_coco/nuclio) | Detector | TensorFlow | ✔️ | ✔️ |
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| [RetinaNet](https://github.com/cvat-ai/cvat/tree/develop/serverless/pytorch/facebookresearch/detectron2/retinanet_r101/nuclio) | Detector | PyTorch | ✔️ | ✔️ |
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| [Face Detection](https://github.com/cvat-ai/cvat/tree/develop/serverless/openvino/omz/intel/face-detection-0205/nuclio) | Detector | OpenVINO | ✔️ | |
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## Useful links
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Start here if you're unsure where to begin with CVAT.
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### Online
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| Name | Description |
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| ------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| {{< ilink "/docs/manual" "**User Manual**" >}} | This comprehensive guide covers all CVAT tools available for work. It includes descriptions of all available tools, quality control methods, and procedures for importing and exporting data. This manual is relevant for both CVAT Online and Self-Hosted versions. |
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| {{< ilink "/docs/getting_started/workflow-org" "**CVAT Complete Workflow Guide for Organizations**" >}} | This guide provides a comprehensive overview of using CVAT for collaboration in organizations. |
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| {{< ilink "/docs/enterprise/subscription-management" "**Subscription Management**" >}} | Learn how to [**choose a plan**](https://www.cvat.ai/post/cvat-ai-pricing-plans-choosing-the-right-plan-for-your-needs), subscribe, and manage your subscription effectively. |
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| {{< ilink "/docs/manual/advanced/xml_format" "**XML Annotation Format**" >}} | Detailed documentation on the XML format used for annotations in CVAT essential for understanding data structure and compatibility. |
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### Self-Hosted
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| Name | Description |
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| ---------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| {{< ilink "/docs/administration/basics/installation" "**Self-hosted Installation Guide**" >}} | Start here to install self-hosted solution on your premises. |
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| [**Dataset Management Framework**](https://github.com/cvat-ai/datumaro/blob/develop/README.md) | Specifically for the Self-Hosted version, this framework and CLI tool are essential for building, transforming, and analyzing datasets. |
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| {{< ilink "/docs/api_sdk/api" "**Server API**" >}} | The CVAT server offers a HTTP REST API for interactions. This section explains how client applications, whether they are command line tools, browsers, or scripts, interact with CVAT through HTTP requests and responses. |
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| {{< ilink "/docs/api_sdk/sdk" "**Python SDK**" >}} | The CVAT SDK is a Python library providing access to server interactions and additional functionalities like data validation and serialization. |
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| {{< ilink "/docs/api_sdk/cli" "**Command Line Tool**" >}} | This tool offers a straightforward command line interface for managing CVAT tasks. Currently featuring basic functionalities, it has the potential to develop into a more advanced administration tool for CVAT. |
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| {{< ilink "/docs/manual/advanced/xml_format" "**XML Annotation Format**" >}} | Detailed documentation on the XML format used for annotations in CVAT essential for understanding data structure and compatibility. |
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| {{< ilink "/docs/administration/basics/aws-deployment-guide" "**AWS Deployment Guide**" >}} | A step-by-step guide for deploying CVAT on Amazon Web Services, covering all necessary procedures and tips. |
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| {{< ilink "/docs/faq" "**Frequently Asked Questions**" >}} | This section addresses common queries and provides helpful answers and insights about using CVAT. |
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## Integrations
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CVAT is a global tool, trusted and utilized by teams worldwide.
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Below is a list of key companies that contribute significantly to our
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product support or are an integral part of our ecosystem.
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{{% alert title="Note" color="primary" %}}
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If you're using CVAT, we'd love to
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hear from you at [contact@cvat.ai](mailto:contact+github@cvat.ai).
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{{% /alert %}}
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| Integrated Service | Available In | Description |
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| ----------------------------------------------------------------------------------- | ---------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| [**Human Protocol**](https://hmt.ai) | Online and Self-hosted | Incorporates CVAT to augment annotation services within the Human Protocol framework, enhancing its capabilities in data labeling. |
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| [**FiftyOne**](https://fiftyone.ai) | Online and Self-hosted | An open-source tool for dataset management and model analysis in computer vision, FiftyOne is [closely integrated](https://voxel51.com/docs/fiftyone/integrations/cvat.html) with CVAT to enhance annotation capabilities and label refinement. |
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| [**Hugging Face**](https://huggingface.co/) & [**Roboflow**](https://roboflow.com/) | Online | In CVAT Online, models from Hugging Face and Roboflow can be added to enhance computer vision tasks. For more information, see [**Integration with Hugging Face and Roboflow**](https://www.cvat.ai/post/integrating-hugging-face-and-roboflow-models) |
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## License Information
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CVAT includes the following licenses:
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| License Type | Applicable To | Description |
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| ------------------------------------------------------ | ---------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| [**MIT License**](https://opensource.org/licenses/MIT) | Self-hosted | This code is distributed under the MIT License, a permissive free software license that allows for broad use, modification, and distribution. |
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| [**LGPL License (FFmpeg)**](https://www.ffmpeg.org) | Online and Self-hosted | Incorporates LGPL-licensed components from the FFmpeg project. Users should verify if their use of FFmpeg requires additional licenses. CVAT.ai Corporation does not provide these licenses and is not liable for any related licensing fees. |
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| **Commercial License** | Self-hosted Enterprise | For commercial use of the Enterprise solution of CVAT, a separate commercial license is applicable. This is tailored for businesses and commercial entities. |
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| [**Terms of Use**](https://www.cvat.ai/terms-of-use) | Online and Self-hosted | Outlines the terms of use and confidential information handling for CVAT. Important for understanding the legal framework of using the platform. |
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| [**Privacy Policy**](https://www.cvat.ai/privacy) | Online | Our Privacy Policy governs your visit to <https://cvat.ai> and your use of <https://app.cvat.ai>, and explains how we collect, safeguard and disclose information that results from your use of our Service. |
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## Get in touch
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To get in touch, use one of the following channels:
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| Support Channel | Applicable To | Description |
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| -------------------------------------------------------------------------------------------------- | ---------------------- | ---------------------------------------------------------------------------------------------------- |
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| [**Discord Channel**](https://discord.gg/S6sRHhuQ7K) | Online and Self-hosted | A space for broader discussions, questions, and all things related to CVAT. |
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| [**LinkedIn**](https://www.linkedin.com/company/cvat-ai/) | Online and Self-hosted | Follow for company updates, news, and employment opportunities. |
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| [**YouTube Channel**](https://www.youtube.com/@cvat-ai) | Online and Self-hosted | Find tutorials and screencasts about CVAT tools. |
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| [**GitHub Issues**](https://github.com/cvat-ai/cvat/issues) | Online and Self-hosted | Report bugs or contribute to the ongoing development of CVAT. |
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| [**Customer Support Channel**](https://youtrack.cvat.ai/form/447d9c98-ab4b-466e-bf9d-004f01b22f73) | Online (Paid Users) | Exclusive support for CVAT Online paid users. |
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| **Commercial Support Inquiries** | Online and Self-hosted | For direct commercial support inquiries, email [**contact@cvat.ai**](mailto:contact+github@cvat.ai). |
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