import setuptools

from medseg import __version__

with open("README.md", "r") as fh:

    long_description = fh.read()

found = setuptools.find_packages()

print(f"Found these packages to add: {found}")

setuptools.setup(

    name="medseg",

    version=__version__,

    author="Diedre Carmo",

    author_email="diedre@dca.fee.unicamp.br",

    description="Modified EfficientDet published in: Multitasking segmentation of lung and COVID-19 findings in CT scans using modified EfficientDet, UNet and MobileNetV3 models",

    long_description=long_description,

    long_description_content_type="text/markdown",

    url="https://github.com/MICLab-Unicamp/medseg",

    packages=found,

    classifiers=[

        "Programming Language :: Python :: 3",

        "License :: OSI Approved :: MIT License",

        "Operating System :: OS Independent",

    ],

    python_requires='>=3.6',

    install_requires=['setuptools', 'numpy', 'rich', 'pillow', 'scipy', 'tqdm', 'torch', 'pandas', 'torchvision', 'pytorch-lightning', 'efficientnet_pytorch', 'connected-components-3d', 'psutil', 'gputil', 'opencv-python', 'SimpleITK==2.0.2', 'pydicom', 'matplotlib'],

    entry_points={

        'console_scripts': ["medseg = medseg.run:main", "medseg_cpu = medseg.run:main_cpu"]

    },

    include_package_data=True,

    package_data={'medseg': ["best_coedet.ckpt", "icon.png", "poly_lung.ckpt", "sing_a100_up_awd_step_raw_medseg_pos.ckpt", "sme2d_coedet_fiso.ckpt", "airway.ckpt", "parse.ckpt"]}

)