Sam2.1 Hiera Small
SAM 2 is a foundational model for promptable visual segmentation in images and videos developed by FAIR, supporting efficient segmentation through prompts.
Downloads 7,333
Release Time : 9/24/2024
Model Overview
SAM 2 is a universal visual segmentation model capable of generating high-quality segmentation masks in images and videos based on user-provided prompts (such as points or boxes).
Model Features
Multimodal Prompt Support
Supports interactive segmentation through various prompt methods such as points and boxes.
Video Segmentation Capability
Unique state management mechanism enables temporally consistent segmentation in videos.
Efficient Inference
Supports mixed-precision (bfloat16) inference for optimized computational efficiency.
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 masks
Video Analysis
Track object movements in videos
Temporally consistent video object segmentation
Medical Imaging
Medical Image Segmentation
Segment organs or lesion areas in CT/MRI scans
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