brainchop 0.1.11

Portable and lightweight brain segmentation using tinygrad

BrainChop

BrainChop is a lightweight tool for brain segmentation that runs on pretty much everything.

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Installation

You can install BrainChop using pip (Python > 3.10)

pip install brainchop

Usage

To use BrainChop, run the following command:

brainchop input.nii.gz -o output.nii.gz

Docker

You can also install BrainChop using docker

git clone [e-mail]:neuroneural/brainchop-cli.git
cd brainchop-cli
docker build -t brainchop .

Then to run, use

docker run --rm -it --device=nvidia.com/gpu=all -v [[output directory]]:/app brainchop [[input nifti file]] -o [[output nifti file]]

On some systems (like recent 25.05 nixos), the docker run command will need to be prepended with

docker run --rm -it --device=nvidia.com/gpu=all

Where:

• input.nii.gz is your input NIfTI file
• output.nii.gz is the desired output file name

Requirements

• Python 3.10+
• tinygrad : our tiny and portable (but powerful) ML inference engine
• numpy : basic tensor operations
• nibabel : to read nifti files
• requests : to download models

License

This project is licensed under the MIT License.