Models & resources
Segment Anything（SAM）
The Segment Anything Model (SAM) is a foundation model developed by Meta AI, designed to address image segmentation tasks.
What is Segment Anything（SAM）?
The Segment Anything Model (SAM) is a foundation model developed by Meta AI, designed to address image segmentation tasks.With strong zero-shot transfer capabilities, SAM can quickly identify and segment any object in an image based on prompts such as points, boxes, or text, without requiring additional training on specific datasets.
As the core of the 'Segment Anything' project, SAM offers flexible interactive interfaces and efficient inference speed.It can be used independently or as a component for other computer vision tasks, providing a general-purpose segmentation solution for content creation, data annotation, and medical image analysis.For more technical details, please refer to the official website.
Key features
- Zero-Shot GeneraAchieves high-quality segmentation on unseen data without fine-tuning for specific objects or scenarios.
- Multi-Prompt IntSupports guiding the model to generate segmentation masks via click points, bounding boxes, or text prompts.
- Real-Time PerforOptimized architecture allows for fast inference on standard hardware, meeting interactive application needs.
- High-ResolutionCapable of processing high-resolution images while maintaining accuracy and integrity of edge details.
- Open EcosystemProvides pre-trained model weights and codebases, facilitating developer integration into local workflows.
How to use it
- Visit the Meta AI Demos or official project page to try the online demo.
- Upload the image file you wish to process.
- Click inside or outside the object, or draw a bounding box as a prompt.
- View the segmentation mask results generated by the model in real-time.
- For local deployment, download pre-trained models and code from the official repository.
Where it fits
- Accelerated DataAssists humans in quickly generating segmentation labels for large-scale image datasets, reducing annotation costs.
- Creative EditingPrecisely selects objects in design software for background replacement, effect addition, or asset extraction.
- Scientific ImageApplied to microscope images or satellite remote sensing maps to automatically identify cells, vegetation, or building structures.
Pricing and free quota
Pricing follows the official site
Who it is for
- Computer Vision Researchers
- AI Application Developers
- Digital Content Creators
- Data Annotation Teams
FAQ
Does SAM require training on my data?
No.SAM is a zero-shot model that can be used directly to segment unseen objects without additional training.
What types of prompt inputs are supported?
It supports foreground/background points, bounding boxes, and mask prompts; some versions also support text prompts.
Can I use SAM commercially?
Please check the license files released officially for specific terms; research use is typically open.