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Segment Anything By Meta

Discover Meta AI's Segment Anything Model (SAM): a versatile tool for precise image segmentation with zero-shot generalization and extensive dataset training.

Image Scanning Updated 22 seconds ago
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Segment Anything By Meta

Segment Anything By Meta's Top Features

Zero-shot generalization to unfamiliar objects and images
Supports various input prompts: interactive points, bounding boxes, masks
Efficient one-time image encoding
Lightweight mask decoder compatible with web browsers
Extensive training on SA-1B dataset (1.1 billion masks from 11 million images)
Integration capability with AR/VR and object detection systems
High-speed inference times
No need for additional training
Versatility for multiple use cases
Advanced transformer-based model architecture

Frequently asked questions about Segment Anything By Meta

SAM supports foreground/background points, bounding boxes, and masks. Text prompts have been explored but not yet released.

The SAM model includes a ViT-H image encoder, a prompt encoder, and a transformer-based mask decoder.

Yes, SAM can take input prompts from other systems such as gaze tracking from AR/VR headsets or bounding box prompts from object detectors.

Yes, SAM can generalize to unfamiliar objects and images without requiring additional training.

SAM was trained on the SA-1B dataset, which includes over 1.1 billion segmentation masks from approximately 11 million images.

The image encoder takes about 0.15 seconds on an NVIDIA A100 GPU, while the prompt encoder and mask decoder take around 50ms on a CPU.

Currently, SAM only works on images and not on videos.

SAM is decoupled into a one-time image encoder and a lightweight mask decoder that can run in web browsers within milliseconds per prompt.

The image encoder is implemented in PyTorch for GPU use, while the prompt encoder and mask decoder can be executed with PyTorch or ONNX runtime on both CPU and GPU.

The image encoder has 632 million parameters, and the prompt encoder and mask decoder have 4 million parameters.

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Category
Image Scanning
Tags
Segment Anything Model
Meta AI
promptable system
zero-shot generalization
image segmentation
no additional training
interactive points
bounding boxes
lightweight mask decoder
web browser compatible

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