Sam2.1 Hiera Tiny
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
Featured Recommended AI Models