Meta's foundation model for promptable segmentation in images and video — point/box prompts, multi-object tracking, streaming memory for real-time video, Apache-2.0.
Meta's foundation model for promptable segmentation in images and video — point/box prompts, multi-object tracking, streaming memory for real-time video, Apache-2.0.
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Segment Anything Model 2 (SAM 2) extends promptable visual segmentation from images to video by treating an image as a single-frame video. A transformer architecture with streaming memory enables real-time video processing and multi-object tracking from point or box prompts. SAM 2.1 ships four checkpoint sizes (Tiny 38.9M to Large 224.4M params) with 39.5–91.2 FPS on an A100, PyTorch training/fine-tuning code, and Hugging Face integration. Widely used in robotics perception pipelines for open-vocabulary object segmentation and tracking.
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