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pyproject.toml
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[project]
name = "yucca"
version = "2.2.3"
authors = [
{ name="Sebastian Llambias", email="[email protected]" },
{ name="Asbjørn Munk", email="[email protected]" },
{ name="Jakob Ambsdorf", email="[email protected]" },
]
description = "The modern framework for sandbox experimentation and out-of-the box machine learning on medical data."
readme = "README.md"
requires-python = ">=3.10"
classifiers = [
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
]
keywords = ['deep learning', 'image segmentation', 'medical image analysis','medical image segmentation']
dependencies = [
"batchgenerators>=0.23",
"connected_components_3d>=3.12.4",
"einops>=0.8.0",
"flake8-unused-arguments>=0.0.13",
"fvcore>=0.1.5",
"lightning>=2.2.1",
"matplotlib>=3.8.3",
"monai>=1.3.0",
"nibabel>=5.2.1",
"numpy>=1.26.4",
"pandas>=2.2.1",
"python-dotenv==1.0.0",
"scikit_image>=0.22.0",
"scikit_learn>=1.4.1.post1",
"seaborn>=0.13.2",
"SimpleITK>=2.3.1",
"tqdm>=4.66.2",
"timm>=0.9.8",
"torchmetrics>=1.4.0.post0",
"wandb>=0.16.3",
"weave>=0.39.0",
]
[project.optional-dependencies]
test = [
'pytest>=7.3',
'flake8>=6.1.0',
'black>=23.10.1',
'mypy>=1.6.0',
]
[project.scripts]
yucca_preprocess = 'yucca.pipeline.run.run_preprocessing:main'
yucca_train = 'yucca.pipeline.run.run_training:main'
yucca_inference = 'yucca.pipeline.run.run_inference:main'
yucca_evaluation = 'yucca.pipeline.run.run_evaluation:main'
yucca_finetune = 'yucca.pipeline.run.run_finetune:main'
yucca_convert_task = 'yucca.pipeline.run.run_task_conversion:main'
yucca_ensemble = 'yucca.pipeline.run.run_ensemble:main'
[project.urls]
"Homepage" = "https://github.com/sllambias/yucca"
"Bug Tracker" = "https://github.com/sllambias/yucca/issues"
[project.entry-points.pyinstaller40]
hook-dirs = 'yucca:_pyinstaller_hooks_dir'
[build-system]
requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"
[tool.black]
line-length = 127