Image Segmentation
MLX
Safetensors
English
native-mlx
apple-silicon
medical-imaging
x-ray
segmentation
noncommercial
research
Instructions to use MedMLX/flexray-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use MedMLX/flexray-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download MedMLX/flexray-mlx --local-dir flexray-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
FleXray · Radiographs
Segment anatomical structures in radiographs with the released FleXray flux0375 member.
| Input | Output |
|---|---|
| Radiograph | Anatomical segmentation |
Apple Silicon · Metal · Python 3.13 / 3.14
Quick start
uv venv --python 3.13
source .venv/bin/activate
repo="https://github.com/MedMLX/flexray-mlx"
release="$repo/releases/download/v0.2.1"
uv pip install "$release/flexray_mlx-0.2.1-py3-none-any.whl"
uv tool install huggingface-hub
hf download MedMLX/flexray-mlx --local-dir models
Replace the example input paths with your own files.
from flexray_mlx.medmlx import run
result = run(
image_path='chest.png',
weights_path='models',
output_dir='outputs',
label_name='lungs',
ensemble=False,
)
print(result["outputs"])
Includes the flux0375 member. Keep ensemble=False.
Use & license
For research and education. Not validated for clinical use.
Weights: CC-BY-NC-4.0 · noncommercial. Notices.
Hardware compatibility
Log In to add your hardware
Quantized
Model tree for MedMLX/flexray-mlx
Base model
VictorButoi/flexray
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download MedMLX/flexray-mlx --local-dir flexray-mlx