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 ~75โ€“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 ยท Demo

Files Included

  • sam3.safetensors โ€” 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

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. 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.
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