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- from setuptools import setup, find_namespace_packages
-
- setup(name='nnunet',
- packages=find_namespace_packages(include=["nnunet", "nnunet.*"]),
- version='1.7.0',
- description='nnU-Net. Framework for out-of-the box biomedical image segmentation.',
- url='https://github.com/MIC-DKFZ/nnUNet',
- author='Division of Medical Image Computing, German Cancer Research Center',
- author_email='f.isensee@dkfz-heidelberg.de',
- license='Apache License Version 2.0, January 2004',
- install_requires=[
- "torch>1.10.0",
- "tqdm",
- "dicom2nifti",
- "scikit-image>=0.14",
- "medpy",
- "scipy",
- "batchgenerators>=0.23",
- "numpy",
- "scikit-learn",
- "SimpleITK",
- "pandas",
- "requests",
- "nibabel",
- "tifffile",
- "matplotlib",
- ],
- entry_points={
- 'console_scripts': [
- 'nnUNet_convert_decathlon_task = nnunet.experiment_planning.nnUNet_convert_decathlon_task:main',
- 'nnUNet_plan_and_preprocess = nnunet.experiment_planning.nnUNet_plan_and_preprocess:main',
- 'nnUNet_train = nnunet.run.run_training:main',
- 'nnUNet_train_DP = nnunet.run.run_training_DP:main',
- 'nnUNet_train_DDP = nnunet.run.run_training_DDP:main',
- 'nnUNet_predict = nnunet.inference.predict_simple:main',
- 'nnUNet_ensemble = nnunet.inference.ensemble_predictions:main',
- 'nnUNet_find_best_configuration = nnunet.evaluation.model_selection.figure_out_what_to_submit:main',
- 'nnUNet_print_available_pretrained_models = nnunet.inference.pretrained_models.download_pretrained_model:print_available_pretrained_models',
- 'nnUNet_print_pretrained_model_info = nnunet.inference.pretrained_models.download_pretrained_model:print_pretrained_model_requirements',
- 'nnUNet_download_pretrained_model = nnunet.inference.pretrained_models.download_pretrained_model:download_by_name',
- 'nnUNet_download_pretrained_model_by_url = nnunet.inference.pretrained_models.download_pretrained_model:download_by_url',
- 'nnUNet_determine_postprocessing = nnunet.postprocessing.consolidate_postprocessing_simple:main',
- 'nnUNet_export_model_to_zip = nnunet.inference.pretrained_models.collect_pretrained_models:export_entry_point',
- 'nnUNet_install_pretrained_model_from_zip = nnunet.inference.pretrained_models.download_pretrained_model:install_from_zip_entry_point',
- 'nnUNet_change_trainer_class = nnunet.inference.change_trainer:main',
- 'nnUNet_evaluate_folder = nnunet.evaluation.evaluator:nnunet_evaluate_folder',
- 'nnUNet_plot_task_pngs = nnunet.utilities.overlay_plots:entry_point_generate_overlay',
- ],
- },
- keywords=['deep learning', 'image segmentation', 'medical image analysis',
- 'medical image segmentation', 'nnU-Net', 'nnunet']
- )
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