Q.What is Meta Segment Anything Model 2 (SAM 2)?
A.SAM 2 is a unified model for segmenting objects across images and videos, allowing users to select objects using clicks, boxes, or masks as input.
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Meta Segment Anything Model 2
★1.2
💬948
💲Free
Meta Segment Anything Model 2 (SAM 2) is a powerful AI tool that enables accurate and interactive object segmentation in both images and videos. With support for click, box, or mask inputs, SAM 2 provides real-time results and strong performance even in complex or unseen scenarios. Open source and highly flexible, it's ideal for developers and researchers working on computer vision tasks.
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Platform
web
AI modelImage segmentationInteractive segmentationMachine learningObject trackingOpen sourceVideo segmentation
What is Meta Segment Anything Model 2?
Meta Segment Anything Model 2 (SAM 2) is the first unified model for segmenting objects in both images and videos. It allows users to select objects using clicks, boxes, or masks as input and delivers fast, precise results. Designed for real-time interactivity, SAM 2 offers state-of-the-art performance and robust zero-shot capabilities on unfamiliar content. The model is open source under an Apache 2.0 license, making it accessible for developers and researchers.
Core Technologies
- AI model
- Image segmentation
- Video segmentation
- Zero-shot learning
- Machine learning
Key Capabilities
- Segment objects in images and videos
- Supports interactive object selection via clicks, boxes, or masks
- Real-time processing and interactivity
- Robust performance on unfamiliar data
- State-of-the-art segmentation accuracy
Use Cases
- Tracking objects across multiple video frames
- Refining segmentation results with additional prompts
- Enhancing video editing workflows with precise object isolation
- Building interactive tools for real-time video analysis
- Training models on diverse image and video datasets
Core Benefits
- Fast and precise object segmentation
- Interactive selection methods for greater control
- Real-time processing for video applications
- Open-source availability under Apache 2.0 license
- Strong performance on new and diverse datasets
Key Features
- Unified image and video segmentation
- Interactive object selection using clicks, boxes, or masks
- Real-time interactivity and results
- Robust zero-shot performance on unfamiliar videos and images
- State-of-the-art performance for object segmentation
How to Use
- 1Provide an image or video frame as input.
- 2Select an object using a click, box, or mask.
- 3Receive real-time segmentation results based on the input.
- 4Refine the output using additional prompts if needed.
Frequently Asked Questions
Q.Is SAM 2 open source?
A.Yes, the models are open source and available under an Apache 2.0 license.
Q.What kind of inputs does SAM 2 accept?
A.SAM 2 accepts clicks, boxes, or masks as input to select an object in an image or video frame.
Q.What is the SA-V dataset?
A.The SA-V dataset is a large and diverse video segmentation dataset used to train SAM 2. It includes ~600K+ masklets collected on ~51K videos from geographically diverse, real-world scenarios.
Pros & Cons (Reserved)
✓ Pros
- Unified model for images and videos
- Open-source and available under Apache 2.0 license
- Strong zero-shot performance
- Real-time interactivity
- State-of-the-art segmentation performance
✗ Cons
- May require additional prompts for optimal results in complex scenes
- Performance may vary depending on video quality and object visibility
Alternatives
No alternatives found.