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:
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.
Getting Started
First, 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 from the Ecosystem.
To open the labeling toolbox, go to the Projects 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.

You can also open the labeling toolbox from a Labeling Job or the Ecosystem page.
Images labeling toolbox
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.
Videos labeling toolbox
Label hours-long videos without cutting them into images. In your browser, with multi-track timeline, built-in object tracking and segments tagging tools.
Video tracking
The most simple and straightforward method of importing is uploading your data using one of our Supervisely Apps.
3D Point Clouds
Label comprehensive 3D scenes from LiDAR or RADAR sensors with additional photo and video context, AI object tracking and point cloud segmentation.
3D Point Clouds Episodes
Our toolbox for 3D Point Cloud labeling is a great solution for annotation a single point cloud at a time.
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