The Segment Anything Model (SAM), developed by Meta AI, is a cutting-edge image segmentation model designed to identify and segment any object within an image or video. SAM utilizes promptable segmentation, allowing users to specify objects of interest through various input prompts, such as points, boxes, or masks. Trained on the extensive SA-1B dataset, SAM demonstrates strong zero-shot performance across diverse segmentation tasks.
Key Features:
- Promptable Segmentation: SAM can segment objects based on different input prompts, offering flexibility in user interaction.
- Zero-Shot Performance: The model exhibits impressive zero-shot capabilities, often competitive with or even superior to prior fully supervised results.
- Large-Scale Training: SAM was trained on a dataset of 11 million images and 1.1 billion masks, enabling it to generalize across various image distributions and tasks.