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setup.py
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setup.py
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from setuptools import setup, find_packages
from pathlib import Path
this_directory = Path(__file__).parent
long_description = (this_directory / "README.md").read_text()
# Environment-specific dependencies.
extras = {
"baselines": ["skrl==0.10.2", "ray[rllib]==2.2.0", "stable-baselines3==1.8.0", "rl-games==1.6.0",
"mujoco_py==2.1.2.14", "gym[all]==0.26.2", "gymnasium[all]==0.28.1", "mujoco-py<2.2,>=2.1"],
}
setup(
name="rofunc",
version="0.0.2.6",
description='Rofunc: The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation',
long_description=long_description,
long_description_content_type='text/markdown',
author="Junjia Liu",
author_email="[email protected]",
url='https://github.com/Skylark0924/Rofunc',
packages=find_packages(),
include_package_data=True,
extras_require=extras,
install_requires=["shutup",
"setuptools==57.4.0",
"omegaconf==2.3.0",
'opencv-python==4.7.0.72',
'tqdm==4.67.1',
'pandas==2.0.3',
'hydra-core==1.3.2',
'trimesh==4.5.3',
'lxml==5.3.0',
"pytorch_kinematics==0.7.2",
'nestle==0.2.0',
'gdown==5.2.0',
"transformations==2022.9.26",
'gym>=0.26.2',
"numpy<=1.23.0",
'wandb==0.18.7',
"gymnasium==1.0.0",
"tensorboard==2.14.0",
"transformers==4.46.3"
],
python_requires=">=3.7,<3.11",
keywords=['robotics', 'robot learning', 'learning from demonstration', 'reinforcement learning',
'robot manipulation'],
license='MIT',
entry_points={
'console_scripts': [
'rf=rofunc._main:main',
],
},
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
)