from setuptools import setup, find_packages

setup(
    name="EMCADNet",
    version="0.1.0",
    author="Your Name",
    author_email="your.email@example.com",
    description="EMCADNet: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation",
    long_description=open("README.md").read(),
    long_description_content_type="text/markdown",
    url="https://github.com/learnljs/EMCAD",
    packages=find_packages(where="src"),
    package_dir={"": "src"},
    classifiers=[
        "Programming Language :: Python :: 3",
        "License :: OSI Approved :: MIT License",
        "Operating System :: OS Independent",
    ],
    python_requires=">=3.8",
    install_requires=[
        "torch>=1.11.0",
        "torchvision>=0.12.0",
        "numpy>=1.22.0",
        "h5py>=3.0.0",
        "scipy>=1.5.0",
        "matplotlib>=3.3.0",
        "tqdm>=4.50.0",
        "tensorboardX>=2.2",
        "nibabel>=3.2.0",
        "medpy>=0.4.0",
        "ptflops>=0.6.4",
        "thop>=0.0.31",
        "segmentation-mask-overlay>=0.3.0",
        "timm>=0.6.0",
    ],
    entry_points={
        "console_scripts": [
            "emcad-train=scripts.train_synapse:main",
            "emcad-test=scripts.test_synapse:main",
        ],
    },
    include_package_data=True,
    package_data={
        "": ["*.md", "*.txt"],
    },
)