Metadata-Version: 2.1
Name: brats
Version: 0.0.2
Summary: BraTS algorithms
Author: Marcel Rosier
Author-email: marcel.rosier@tum.de
Requires-Python: >=3.8
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: PyYAML (>=6.0.1)
Requires-Dist: dacite (>=1.8.0)
Requires-Dist: docker (>=7.0.0)
Requires-Dist: halo (>=0.0.31)
Requires-Dist: loguru (>=0.6.0)
Requires-Dist: rich (>=13.0.0)
Requires-Dist: tqdm (>=4.66.4)
Description-Content-Type: text/markdown

[![PyPI version brats-algorithms](https://badge.fury.io/py/brats-algorithms.svg)](https://pypi.python.org/pypi/brats-algorithms/)
[![Documentation Status](https://readthedocs.org/projects/brats-algorithms/badge/?version=latest)](http://brats-algorithms.readthedocs.io/?badge=latest)
[![tests](https://github.com/BrainLesion/brats-algorithms/actions/workflows/tests.yml/badge.svg)](https://github.com/BrainLesion/brats-algorithms/actions/workflows/tests.yml)

# brats-algorithms

Top performing algorithms from the Brain Tumor Segmentation (BraTS) challenges, providing state-of-the-art models for brain lesion segmentation.

## Features

- Access to top-performing algorithms from recent BraTS challenges.
- Easy-to-use inference API.
- Extensive documentation and examples. (TODO!)

## Installation

With a Python 3.10+ environment, you can install `PACKAGE_NAME` directly from [PyPI](https://pypi.org/project/PACKAGE_NAME/):

```sh
pip install PACKAGE_NAME
```

### Docker and NVIDIA Container Toolkit Setup

To run `PACKAGE_NAME` in a Docker container with GPU support (required for most algorithms), ensure you have Docker and NVIDIA Docker installed. Instructions:
- **Docker**: Installation instructions on the official [website](https://docs.docker.com/get-docker/)
- **NVIDIA Container Toolkit**: Installation instructions on the official [GitHub page](https://github.com/NVIDIA/nvidia-container-toolkit) 

## Use Cases and Tutorials

*TODO*

## Contributing

We welcome contributions from the community, including bug reports, feature requests, and code contributions. For more information on how to contribute, please see our [CONTRIBUTING.md](CONTRIBUTING.md) file.

## License
*TODO*
