swin-unetr-mlx
Segment 13 abdominal organs in CT with MONAI SwinUNETR and native MLX.
Abdominal CT → multi-organ segmentation.
| Input | Output |
|---|---|
| 3D abdominal CT · NIfTI | Organ mask on the input grid |
Apple Silicon · Metal · Python 3.13 / 3.14 · uv
Quick start
uv venv --python 3.13
source .venv/bin/activate
uv pip install "swin-unetr-mlx[conversion]" huggingface-hub
Download and convert the checkpoint once, then run:
from pathlib import Path
from huggingface_hub import hf_hub_download
from swin_unetr_mlx import convert_checkpoint
from swin_unetr_mlx.medmlx import run
checkpoint = hf_hub_download("MONAI/swin_unetr_btcv_segmentation", "models/model.pt")
convert_checkpoint(Path(checkpoint), Path("model.safetensors"))
result = run(image_path="ct.nii.gz", weights_path="model.safetensors", output_dir="out")
print(result["outputs"]["mask"])
License
Apache-2.0. See third-party notices. Model weights retain their publisher terms.
For research and education. Outputs require human review.
1 maintainer
Metadata
1 maintainer
Release files for swin-unetr-mlx 0.2.2
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| swin_unetr_mlx-0.2.2.tar.gz | 27.3 kB | Without provenance | Details for swin_unetr_mlx-0.2.2.tar.gz |
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| swin_unetr_mlx-0.2.2-py3-none-any.whl | Python 3 | none | any | Details for swin_unetr_mlx-0.2.2-py3-none-any.whl |
Total release size: 64.2 kB
Release files / swin_unetr_mlx-0.2.2.tar.gz
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