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setup.py
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setup.py
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# AGPL-3.0 license
import re
from pathlib import Path
import pkg_resources as pkg
from setuptools import find_packages, setup
# Settings
FILE = Path(__file__).resolve()
PARENT = FILE.parent # root directory
README = (PARENT / 'README.md').read_text(encoding='utf-8')
REQUIREMENTS = [f'{x.name}{x.specifier}' for x in pkg.parse_requirements((PARENT / 'requirements.txt').read_text())]
def get_version():
file = PARENT / 'boxmot/__init__.py'
version = re.search(r'__version__\s*=\s*[\'\"](.+?)[\'\"]', file.read_text(encoding='utf-8')).group(1)
return version
setup(
name='boxmot', # name of pypi package
version=get_version(), # version of pypi package
python_requires='>=3.8',
license='AGPL-3.0',
description=('SOTA tracking methods for detection, segmentation and pose estimation models.'),
long_description=README,
long_description_content_type='text/markdown',
url='https://github.com/mikel-brostrom/yolo_tracking',
project_urls={
'Bug Reports': 'https://github.com/mikel-brostrom/yolo_tracking/issues',
'Source': 'https://github.com/mikel-brostrom/yolo_tracking'},
author='Mikel Broström',
author_email='[email protected]',
packages=find_packages(), # required
include_package_data=True,
install_requires=REQUIREMENTS,
extras_require={
'dev': [
'pytest',
'pytest-cov',
'coverage',
'pre-commit'
],
'export': [
'onnx>=1.12.0 ', # ONNX export
'onnxsim>=0.4.1 ', # ONNX simplifier
'nvidia-pyindex', # TensorRT export
'nvidia-tensorrt', # TensorRT export
'openvino-dev>=2022.3', # OpenVINO export
'onnx2tf>=1.10.0', # TFLite export
'onnx_graphsurgeon', # TFLite export
'sng4onnx', # TFLite export
],
'evolve': [
'optuna', # ONNX export
'plotly', # ONNX simplifier
'kaleido', # TensorRT export
'joblib', # TensorRT export
],
'yolo': [
'yolox==0.3.0', # yolox inference
'thop', # yolox dependency
'super-gradients==3.1.1', # yolo_nas inference
'ultralytics==8.1.29', # Tyolov8 inference
],
},
platforms=["linux", "windows"],
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Intended Audience :: Education',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Programming Language :: Python :: 3.11',
'Topic :: Software Development',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Scientific/Engineering :: Image Recognition',
'Topic :: Scientific/Engineering :: Image Processing',
],
keywords='machine-learning, deep-learning, vision, ML, DL, AI, YOLO',
)