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