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Segment Anything Model (SAM)

Segment Anything (SAM) is an image segmentation model developed by Meta Research, capable of doing zero-shot segmentation.

Overview

Segment Anything, released in April 2023 by Meta Research, is an image segmentation computer vision model trained using a new dataset. The model itself is called Segment Anything Model (SAM). Using SAM, you can generate segmentation masks for all of the objects in an image that the model can find, or masks for objects that meet a provided text prompt.

SAM has strong zero-shot capabilities, meaning it can segment unrecognized objects without further training. This provides SAM with a large advantage over other segmentation models which may require fine-tuning for different uses.

The dataset on which SAM was trained contains over one billion image masks and 11 million images.

Performance

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Label Data Automatically with Segment Anything Model (SAM)

You can automatically label a dataset using Segment Anything Model (SAM) with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use Segment Anything Model (SAM) to train a computer vision model.

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