Segment Anything Model (SAM): 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...

We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. Using our efficient model in a data collection loop, we built the largest segmentation dataset to date (by far), with over 1 billion masks on 11M licensed and privacy respecting images.

Jun 3, 2024 · In computer vision, segmenting an image into separate segments or regions is a crucial operation. The article "Segment Anything – A Foundation Model for Image Segmentation" provides an introduction to Attention Res-UNet which is an essential model for making separate aspects visible through images.

Apr 18, 2023 · SAM to return a valid segmentation mask for any prompt, where a prompt can be foreground/background points, a rough box or mask, freeform text, or, in general, any information indicating what to...

Apr 13, 2023 · 🔍 Explore this in-depth guide as we walk you through setting up your Python environment, loading SAM, generating segmentation masks, and much more. Master the art of converting object...

Jan 22, 2024 · To use Segment Anything on a local machine, we'll follow these steps: Set up a Python environment; Load the Segment Anything Model (SAM) Generate masks automatically with SAM; Plot masks onto an image with Supervision; Generate bounding boxes …

Jan 4, 2024 · This work focuses on building a foundation model for image segmentation, introducing the promptable segmentation task, SAM model architecture, and the SA-1B dataset.

Python package for segmenting aerial LiDAR data using Segment-Anything Model (SAM) from Meta AI. This package is specifically designed for unsupervised instance segmentation of LiDAR data.

Apr 5, 2025 · SAM forms the heart of the Segment Anything initiative, a groundbreaking project that introduces a novel model, task, and dataset for image segmentation. SAM's advanced design allows it to adapt to new image distributions and tasks without prior knowledge, a feature known as zero-shot transfer.

We also provide instructions on how to easily download the model weights. The Segment Anything Model (SAM) produces high quality object masks from input prompts such as points or boxes, and it can be used to generate masks for all objects in an image.