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- sam3 |
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--- |
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# SAM 3 |
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This repository mirrors the official **Segment Anything Model 3 (SAM 3)** weights released by Meta Superintelligence Labs. SAM 3 is a unified foundation model for prompt-driven segmentation in images and videos. It supports open-vocabulary text prompts and visual prompts (points/boxes/masks). Compared to SAM 2, SAM 3 exhaustively segments each instance of a requested concept and reaches ~75–80% of human-level performance on the SA-CO benchmark (270K unique concepts). |
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## Highlights |
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- **Presence token** improves discrimination between closely related prompts. |
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- **Decoupled detector + tracker** scales better for long video sequences. |
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- **4M+ automatically annotated concepts** ensure broad coverage of open-world categories. |
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> Original paper: *SAM 3: Segment Anything with Concepts* (Meta AI, 2024). |
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> Resources: [Project Page](https://ai.meta.com/sam3) · [Demo](https://segment-anything.com/) |
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## Files Included |
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- `sam3.safetensors` — detector and tracker weights for image + video segmentation. |
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- Tokenizer/config assets should be copied from the official `facebookresearch/sam3` repository; this mirror only repackages the safetensors weights for self-hosting. |
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## Quickstart |
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```bash |
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pip install torch==2.7.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126 |
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pip install git+https://github.com/facebookresearch/sam3.git |
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python - <<'PY' |
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from sam3 import build_sam3_image_model |
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from sam3.model.sam3_image_processor import Sam3Processor |
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model = build_sam3_image_model( |
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bpe_path="sam3/assets/bpe_simple_vocab_16e6.txt.gz", |
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device="cuda", |
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eval_mode=True, |
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checkpoint_path="sam3.safetensors", |
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load_from_HF=False, |
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) |
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processor = Sam3Processor(model, device="cuda") |
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state = processor.set_image("your_image.jpg") |
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state = processor.set_text_prompt("white bicycle", state) |
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print(state["masks"].shape) |
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PY |
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``` |
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## Integration Notes |
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These mirrored weights are used in the **AILab SAM3 ComfyUI node** (RMBG edition) to enable promptable segmentation workflows directly inside ComfyUI. The node loads `sam3.safetensors`, tokenizer assets, and the SAM3 processors locally, so the entire pipeline stays compatible even when offline. |
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## License & Usage |
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- This mirror preserves Meta's original weights and is subject to the license on [facebook/sam3](https://huggingface.co/facebook/sam3). You must accept Meta's terms before downloading the official release. |
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- When hosting this file in your own Hugging Face repository, keep this notice and credit the original authors. |
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- Cite the SAM 3 paper for any research or product that builds upon these weights. |
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