> ## Documentation Index
> Fetch the complete documentation index at: https://docs.labellerr.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Segment Anything (SAM)

> Discover how Labellerr integrates Meta AI's Segment Anything Model (SAM) to enable fast and accurate object segmentation with a single click, enhancing your annotation pipeline.

**A new AI model from Meta AI that can "cut out" any object, in any image, with a single click.**

SAM is a promptable segmentation system with zero-shot generalization to unfamiliar objects and images, without the need for additional training.

We have used the capability of **SAM** to build a more accurate and fast annotation pipeline. This feature **enables a user to draw segmentation around an object via only a single click on that object.**

<Note>
  Before going forward, please ensure that you are familiar with the Annotation Projects, Datasets and Annotation Pipelines at Labellerr. If not please visit the below links :-

  1. [How to create a datasets at workspace level?](/tutorials/datasets)
  2. [How to create a new project](/getting-started/create-project)?
  3. [Start Labelling](/actions/start-labelling)
</Note>

First we need to create a polygon type annotation question with the name of object that we want to auto-segment. Select that polygon object. An auto segment icon in the icons list above the file will appear. Click on the auto segment icon , Select ‘**Interact**’.

<Frame>
  <img src="https://cdn.labellerr.com/1%20%20Documentation/05027338-1bc7-4404-94c7-00a04347911a.webp" alt="Auto Segment Icon" />
</Frame>

Click on the required object to auto label in the image. Wait for a few seconds, the object will be segmented.

<Frame>
  <img src="https://cdn.labellerr.com/1%20%20Documentation/e86e75cd-2d6c-4f6d-8b59-5b045c3b3f55.webp" alt="Segmented Object" />
</Frame>

Check the video tutorial to implement this feature.

<iframe className="w-full aspect-video rounded-xl" src="https://www.youtube.com/embed/lxHgRrsNJZQ" title="YouTube video player" frameborder="0" allowfullscreen />

<Note>
  For further assistance contact [support@tensormatics.com](mailto:support@tensormatics.com)
</Note>
