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setup.py
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setup.py
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import io
import os
import re
import setuptools
BASE_DIR = os.path.abspath(os.path.dirname(__file__))
print(BASE_DIR)
def get_long_description():
with io.open(os.path.join(BASE_DIR, "README.md"), encoding="utf-8") as f:
return f.read()
def get_requirements():
try:
with open(os.path.join(BASE_DIR, "requirements.txt"), encoding="utf-8") as f:
return f.read().split("\n")
except:
return []
def get_version():
version_file = os.path.join(BASE_DIR, "backbones_unet", "__init__.py")
with io.open(version_file, encoding="utf-8") as f:
return re.search(r'^__version__ = [\'"]([^\'"]*)[\'"]', f.read(), re.M).group(1)
setuptools.setup(
name="pretrained-backbones-unet",
version=get_version(),
author="Berkay Mayali",
license="MIT",
description="Packaged version of the timm pretrained model backbones for Unet architecture",
long_description=get_long_description(),
long_description_content_type="text/markdown",
url="https://github.com/mberkay0/pretrained-backbones-unet",
packages=setuptools.find_packages(),
python_requires=">=3.7",
install_requires=get_requirements(),
classifiers=[
"Development Status :: 5 - Production/Stable",
"Operating System :: OS Independent",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Topic :: Software Development :: Libraries",
"Topic :: Software Development :: Libraries :: Python Modules",
"Topic :: Education",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
keywords="machine-learning, deep-learning, pytorch, vision, semantic-segmentation, image-pixel-classification, object-detection, convnext, unet",
)