Create README.md

README.md

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+---
+license: other
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+  By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the Meta Privacy Policy: checkbox
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+language:
+- en
+pipeline_tag: mask-generation
+library_name: transformers
+tags:
+- sam3
+---
+
+# SAM 3
+
+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).
+
+## Highlights
+- **Presence token** improves discrimination between closely related prompts.
+- **Decoupled detector + tracker** scales better for long video sequences.
+- **4M+ automatically annotated concepts** ensure broad coverage of open-world categories.
+
+> Original paper: *SAM 3: Segment Anything with Concepts* (Meta AI, 2024).  
+> Resources: [Project Page](https://ai.meta.com/sam3) · [Demo](https://segment-anything.com/)
+
+## Files Included
+- `sam3.safetensors` — detector and tracker weights for image + video segmentation.
+- Tokenizer/config assets should be copied from the official `facebookresearch/sam3` repository; this mirror only repackages the safetensors weights for self-hosting.
+
+## Quickstart
+```bash
+pip install torch==2.7.0 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126
+pip install git+https://github.com/facebookresearch/sam3.git
+
+python - <<'PY'
+from sam3 import build_sam3_image_model
+from sam3.model.sam3_image_processor import Sam3Processor
+model = build_sam3_image_model(
+    bpe_path="sam3/assets/bpe_simple_vocab_16e6.txt.gz",
+    device="cuda",
+    eval_mode=True,
+    checkpoint_path="sam3.safetensors",
+    load_from_HF=False,
+)
+processor = Sam3Processor(model, device="cuda")
+state = processor.set_image("your_image.jpg")
+state = processor.set_text_prompt("white bicycle", state)
+print(state["masks"].shape)
+PY
+```
+
+## Integration Notes
+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.
+
+## License & Usage
+- 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.
+- When hosting this file in your own Hugging Face repository, keep this notice and credit the original authors.
+- Cite the SAM 3 paper for any research or product that builds upon these weights.
+