Segment Anything
VerifiedIntroduction
Meta AI image segmentation model that segments any object
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Segment Anything Product Information
Segment Anything Overview
Segment Anything Model (SAM) is Meta AI foundational image segmentation model that can segment any object in any image with a simple prompt. SAM represents a major advance in AI segmentation by demonstrating zero-shot generalization - the ability to segment objects it was never specifically trained on based only on a prompt click or bounding box. Released as open source, SAM has become the foundation for numerous computer vision applications and research projects.
This product stands out with features such as:
- •Universal Segmentation: Segment any object in any image
- •Zero-Shot Capability: Works on unseen objects without specific training
- •Multiple Prompt Types: Click, box, or text prompts for segmentation
- •Automatic Segmentation: Segment everything in an image automatically
- •High Quality Masks: Precise pixel-level segmentation masks
- •Open Source: Freely available model weights
- •Research Foundation: Foundation for many downstream applications
- •Python Integration: Easy integration through Python library
How to Use Segment Anything
Get started in a few simple steps
Install the Library
Install the SAM Python library from Meta AI GitHub repository. Download the model weights appropriate for your use case.
Load Your Image
Load the image you want to segment into SAM. The model accepts standard image formats.
Prompt and Segment
Click on an object, draw a bounding box, or let SAM segment everything automatically. Receive precise segmentation masks for your target objects.
Segment Anything's Core Features in Detail
Powerful features from Segment Anything
Foundation Model Impact
A model that segments any object without task-specific training creates a foundation that accelerates development of the entire computer vision application ecosystem
Research Acceleration
Segmentation that previously required task-specific model training can now be accomplished with SAM prompts, dramatically reducing research iteration time
Application Building
Applications that need to isolate specific objects from images can use SAM as a segmentation backbone rather than building custom segmentation from scratch
Open Source Value
Free access to a state-of-the-art segmentation model that can be used commercially removes a significant barrier to computer vision application development
Segment Anything Use Cases
Discover how Segment Anything can benefit different users
Computer Vision Researchers
AI researchers use SAM as a segmentation tool in their research and as a baseline for segmentation research
Application Developers
Engineers building applications that require object isolation use SAM as the segmentation component of their vision pipeline
Data Labelers
Teams creating training datasets for AI use SAM to accelerate the segmentation annotation process