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setup.py
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setup.py
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# --- built in ---
import os
import re
from setuptools import find_packages, setup
package_name = 'dungeon_maps'
def get_version():
with open(os.path.join(package_name, '__init__.py'), 'r') as f:
return re.search(r'^__version__ = [\'"]([^\'"]*)[\'"]', f.read(), re.M).group(1)
setup(
name=package_name,
version=get_version(),
description='A tiny PyTorch library for depth map manipulations',
long_description=open('README.md', encoding='utf8').read(),
long_description_content_type='text/markdown',
url='https://github.com/Ending2015a/dungeon_map',
author='JoeHsiao',
author_email='[email protected]',
license='MIT',
python_requires=">=3.6",
classifiers=[
# How mature is this project? Common values are
# 3 - Alpha
# 4 - Beta
# 5 - Production/Stable
'Development Status :: 2 - Pre-Alpha',
# Indicate who your project is intended for
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Software Development :: Libraries :: Python Modules',
# Pick your license as you wish (should match "license" above)
'License :: OSI Approved :: MIT License',
# Specify the Python versions you support here. In particular, ensure
# that you indicate whether you support Python 2, Python 3 or both.
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
],
keywords='deep learning, computer vision, machine learning, '
'robotics, depth map, point cloud, orthographic projection',
packages=[
# exclude deprecated module
package for package in find_packages()
if package.startswith(package_name)
],
package_data={
package_name: [
'sim/data/*.fs', # shaders
'sim/data/*.vs'
]
},
install_requires=[
'numpy',
'torch>=1.8.0',
'torch-scatter'
],
extras_require={
'sim': [
'moderngl',
'opencv-python'
]
}
)