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Segment Anything

Segment Anything

SAM is an advanced AI-powered segmentation system capable of zero-shot generalization to diverse objects and images through customizable prompts.

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About Segment Anything

Segment Anything (SAM), developed by Meta AI, is a versatile promptable segmentation system that generalizes to new objects and images without additional training. It allows users to easily isolate any object in an image with a single click. SAM supports various input prompts to handle a wide array of segmentation tasks. Trained on millions of images and masks through a data engine, it offers robust performance for diverse applications.

How to Use

Users can interact with SAM by providing prompts such as points, bounding boxes, or automatic segmentation. It can also be integrated into AR/VR systems or object detection pipelines for text-based segmentation. Try the live demo available on the official website to experience its capabilities.

Features

  • Supports customizable outputs for seamless integration
  • Zero-shot promptable segmentation for diverse objects
  • Automatically segments entire images with minimal input
  • Integrates smoothly with other AI and vision systems
  • Interactive prompts using points and bounding boxes

Use Cases

  • Creative image editing and collaging
  • One-click object extraction from images
  • Tracking and analyzing object masks in videos
  • Lifting 2D masks into 3D models
  • Enhancing image editing workflows
  • Text-to-object segmentation for automation

Best For

AI research and developmentImage processing professionalsRobotics and automation engineersComputer vision specialistsAR/VR application developers

Pros

  • Effective zero-shot generalization to unseen objects
  • Optimized for web-browser deployment
  • Seamless integration with AI and vision tools
  • Flexible prompt-based interaction
  • Trained on the extensive SA-1B dataset

Cons

  • Text prompt capabilities are discussed but not publicly available
  • Requires a GPU for efficient processing of images
  • Outputs only object masks, no label annotations
  • Currently limited to still images and individual video frames

FAQs

What types of prompts does SAM support?
SAM supports prompts like points, bounding boxes, and masks. Text prompts are explored but not yet available for public use.
How is the SAM model structured?
It features a ViT-H image encoder that processes each image once to produce an embedding, a prompt encoder for inputs, and a lightweight transformer-based mask decoder to generate object masks.
What data was used to train SAM?
SAM was trained on the extensive SA-1B dataset, which includes millions of images and masks. You can view this dataset through our online viewer.
Does SAM generate mask labels?
No, SAM predicts only object masks and does not produce label annotations.
Can SAM process videos?
Currently, SAM supports only static images or individual frames extracted from videos.