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from setuptools import setup, find_packages
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, "README.md"), encoding="utf-8") as f:
long_description = f.read()
with open(path.join(here, 'requirements.txt')) as f:
install_requires = [x for x in f.read().splitlines() if len(x)]
exec(open("gcvit/version.py").read())
setup(
name="gcvit",
version=__version__,
description="Tensorflow 2.0 Implementation of GCViT: Global Context Vision Transformer. https://github.com/awsaf49/gcvit-tf",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/awsaf49/gcvit-tf",
author="Awsaf",
author_email="[email protected]",
classifiers=[
# How mature is this project? Common values are
# 3 - Alpha
# 4 - Beta
# 5 - Production/Stable
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Software Development",
"Topic :: Software Development :: Libraries",
"Topic :: Software Development :: Libraries :: Python Modules",
],
# Note that this is a string of words separated by whitespace, not a list.
keywords="tensorflow computer_vision image classification transformer",
packages=find_packages(exclude=["tests"]),
include_package_data=True,
install_requires=install_requires,
python_requires=">=3.6",
license="MIT",
) |