SAM2.1-HIERA-LARGE
| Property | Value |
|---|---|
| Author | |
| License | Apache-2.0 |
| Paper | View Paper |
| Downloads | 17,512 |
| Tags | Mask Generation, SAM2 |
What is sam2.1-hiera-large?
SAM2.1-HIERA-LARGE is Facebook's advanced foundation model designed for promptable visual segmentation in both images and videos. It represents the latest evolution in the Segment Anything Model (SAM) series, offering enhanced capabilities for precise object segmentation and mask generation.
Implementation Details
The model supports both image and video prediction workflows through dedicated predictors. It utilizes PyTorch and can run inference with CUDA acceleration using bfloat16 precision for optimal performance. The implementation allows for both point-based and box-based prompting, making it versatile for various segmentation tasks.
- Supports both image and video segmentation
- Implements efficient CUDA-accelerated inference
- Offers flexible prompting mechanisms
- Provides real-time video propagation capabilities
Core Capabilities
- High-quality mask generation for images
- Real-time video object tracking and segmentation
- Support for multiple prompt types
- Efficient propagation of masks through video frames
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its ability to handle both image and video segmentation tasks with a single architecture, while offering real-time performance and high-quality mask generation capabilities.
Q: What are the recommended use cases?
The model is ideal for applications requiring precise object segmentation in images and videos, including video editing, object tracking, and automated visual analysis tasks.
