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Sam2.1 Hiera Tiny

Developed by facebook
SAM 2 is a foundational model for promptable visual segmentation in images and videos developed by FAIR, supporting efficient segmentation through prompts.
Downloads 12.90k
Release Time : 9/24/2024

Model Overview

SAM 2 is a foundational model for image and video segmentation that can quickly generate high-quality segmentation masks based on user-provided prompts (such as points or boxes).

Model Features

Promptable Segmentation
Supports interactive segmentation through prompts like points or boxes
Image and Video Versatility
The same model architecture supports both image and video segmentation tasks
Efficient Inference
Uses torch.autocast and bfloat16 for efficient inference
State Propagation
Maintains and propagates prompt information across video frames

Model Capabilities

Image Segmentation
Video Segmentation
Interactive Segmentation
Mask Generation

Use Cases

Computer Vision
Image Editing
Quickly isolate objects in images for editing
High-quality object segmentation masks
Video Analysis
Track object movement in videos
Consistent object segmentation across frames
Medical Imaging
Medical Image Segmentation
Segment organs or lesions in CT/MRI scans
Precise medical structure segmentation
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