# Labeling Toolboxes

With more than 5 years of constant improvement, proved by hundreds of businesses, Supervisely provides a complete set of labeling toolboxes for various modalities and tasks, starting from images, videos, and including even solutions for 3D point clouds and volumetric data.

## Pre-Requirements

Follow those recommendations for the best results:

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Though we support all common web browsers, we strongly recommend using **Google Chrome** or **Mozilla Firefox**, because we use latest technologies to render annotations. We also advise you to use the latest version of web browser.
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To work with large images and lots of annotations we recommend to use computer with hardware acceleration available. Check if your browser uses hardware acceleration [here](chrome://gpu).
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## Getting Started

First, [import](https://docs.supervisely.com/import-and-export/import) the dataset you would like to annotate. You can upload images, videos, and many other types of data from your computer or import one of our [sample projects](https://ecosystem.supervisely.com/import+images+project) from the Ecosystem.

To open the labeling toolbox, go to the [Projects](https://docs.supervisely.com/labeling/broken-reference) page, select one of the projects and click on a dataset. Depending on the type of your project, you will see a popup where you can select the right toolbox or, if there is one, the labeling toolbox will open automatically.

![](https://1080806899-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-M4BHwRbuyIoH-xoF3Gv%2Fuploads%2Fgit-blob-5bfc9f56b04d348eb46fb7e4b7f574a6d4f0f2f3%2Fnew-toolbox.png?alt=media)

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When opening a labeling toolbox, you can only annotate a single dataset at a time.
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You can also open the labeling toolbox from a [Labeling Job](https://docs.supervisely.com/labeling/jobs) or the [Ecosystem](https://ecosystem.supervisely.com/annotation_tools/image-labeling-tool-v2) page.
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<table data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Images labeling toolbox</strong></td><td>The image labeling toolbox allows you to annotate one image at a time, such as .jpg, .png, .tiff, and many more formats you can import to Supervisely.</td><td><a href="labeling-toolbox/images">images</a></td></tr><tr><td><strong>Multiview images</strong></td><td>Create image groups inside your dataset by assigning a grouping tag.</td><td><a href="labeling-toolbox/multi-view-images">multi-view-images</a></td></tr><tr><td><strong>Overlay</strong></td><td>Inspect a base image together with linked overlay layers and adjust opacity for direct visual comparison.</td><td><a href="labeling-toolbox/overlay">overlay</a></td></tr><tr><td><strong>Videos labeling toolbox</strong></td><td>Label hours-long videos without cutting them into images. In your browser, with multi-track timeline, built-in object tracking and segments tagging tools.</td><td><a href="labeling-toolbox/videos-3.0">videos-3.0</a></td></tr><tr><td><strong>Video tracking</strong></td><td>The most simple and straightforward method of importing is uploading your data using one of our Supervisely Apps.</td><td><a href="labeling-toolbox/video-tracking">video-tracking</a></td></tr><tr><td><strong>3D Point Clouds</strong></td><td>Label comprehensive 3D scenes from LiDAR or RADAR sensors with additional photo and video context, AI object tracking and point cloud segmentation.</td><td><a href="labeling-toolbox/3d-point-clouds">3d-point-clouds</a></td></tr><tr><td><strong>3D Point Clouds Episodes</strong></td><td>Our toolbox for 3D Point Cloud labeling is a great solution for annotation a single point cloud at a time.</td><td><a href="labeling-toolbox/3d-point-cloud-episodes-2">3d-point-cloud-episodes-2</a></td></tr><tr><td><strong>Sensor-fusion</strong></td><td>Additionally to a single point cloud and episodes point clouds toolboxes, Supervisely allows you to provide additional photo and video context for accurate labeling.</td><td><a href="labeling-toolbox/sensor-fusion">sensor-fusion</a></td></tr><tr><td><strong>DICOM</strong></td><td>The most simple and straightforward method of importing is uploading your data using one of our Supervisely Apps.</td><td><a href="labeling-toolbox/dicom">dicom</a></td></tr></tbody></table>