About This Site
SAM is a promptable AI segmentation system for zero-shot generalization to objects and images. Segment Anything (SAM) is a promptable segmentation system developed by Meta AI that offers zero-shot generalization to unfamiliar objects and images without requiring additional training. It allows users to "cut out" any object in any image with a single click. SAM uses a variety of input prompts to perform a wide range of segmentation tasks. The model was trained on millions of images and masks collected through a model-in-the-loop "data engine."
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Meta Segment Anything Model 2
Unified model for segmenting objects across images and videos with high precision.
Meta Segment Anything Model 2 (SAM 2) is the first unified model for segmenting objects across images and videos. It allows users to select objects in any image or video frame using a click, box, or mask as input. SAM 2 is designed for fast, precise object selection and offers state-of-the-art performance for object segmentation in both images and videos. The models are open source under an Apache 2.0 license.
Key Features AI
Core Features
Promptable segmentation with zero-shot generalization
Interactive point and box prompts
Automatic segmentation of entire images
Integration with other AI systems
Extensible outputs for use in other applications
Advantages
Zero-shot generalization to unfamiliar objects and images
Flexible promptable design
Efficient model design for web-browser use
Large dataset for training (SA-1B)
Integration with other AI systems
缺点：Currently only supports images or individual video frames
缺点：Requires a GPU for efficient image encoder inference
缺点：Does not produce mask labels, only object masks
缺点：Text prompts are explored in the paper but not released
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