monoloco/setup.py
Lorenzo Bertoni 8f02f79918
pip install monoloco (#7)
* add box visualization

* add box visualization and change thresholds for pif preprocessing

* refactor printer

* change default values

* change confidence definition

* remove redundant function

* add debug plot in preprocessing

* add task error in evaluation

* add horizontal flipping

* add evaluation table

* add evaluation table with verbosity

* add tabulate requirement and command line option verbose

* refactor evaluate

* add task error with mean absolute deviation

* add stereo baseline

* integrate stereo baseline

* refactor factory preprocessing

* add stereo command for evaluation

* fix category bug

* add interquartile range for stereo

* use left tt for translation

* refactor stereo functions

* remvove redundant functions

* change names of constants

* add pixel error as function of depth

* fix bug on output directory

* add now time at the moment of saving

* add person sitting category

* remove box in pifpaf predictions

* fix printing name

* add printing of number of matches

* add cyclist category

* fix assertion error

* add travis file

* working eval

* working eval

* change source file

* renaming

* add pylint file

* fix pylint

* fix import

* add pyc files in gitignore

* pylint fix

* pylint fix

* add pytest cache

* update readme

* fix pylint

* fix pylint

* add travis file

* add pylint in pip install

* fix pylint

* add eggs file in gitignore

* update readme

* add readme
2019-07-19 17:16:33 +02:00

37 lines
1.0 KiB
Python

from setuptools import setup
# extract version from __init__.py
with open('monoloco/__init__.py', 'r') as f:
VERSION_LINE = [l for l in f if l.startswith('__version__')][0]
VERSION = VERSION_LINE.split('=')[1].strip()[1:-1]
setup(
name='monoloco',
version=VERSION,
packages=[
'monoloco',
'monoloco.train',
'monoloco.predict',
'monoloco.eval',
'monoloco.prep',
'monoloco.visuals',
'monoloco.utils'
],
license='GNU AGPLv3',
description='MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation',
long_description=open('README.md').read(),
long_description_content_type='text/markdown',
author='Lorenzo Bertoni',
author_email='lorenzo.bertoni@epfl.ch',
url='https://github.com/vita-epfl/monoloco',
zip_safe=False,
install_requires=[
'openpifpaf',
'nuscenes-devkit', # for nuScenes dataset preprocessing
'tabulate', # For evaluation
'pylint',
'pytest',
],
)