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Commit abe54c25 authored by Lucia D. Hradecka's avatar Lucia D. Hradecka
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uploading to pypi

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dist-1/
bio_volumentations.egg-info/
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...@@ -14,7 +14,7 @@ in terms of design and user interface. Therefore, it can easily be adopted by de ...@@ -14,7 +14,7 @@ in terms of design and user interface. Therefore, it can easily be adopted by de
# Installation # Installation
Install the package from PyPi using: Install the package from pip using:
```python ```python
pip install bio-volumentations pip install bio-volumentations
``` ```
...@@ -60,6 +60,8 @@ The `Compose` class automatically checks and adjusts image format, datatype, sta ...@@ -60,6 +60,8 @@ The `Compose` class automatically checks and adjusts image format, datatype, sta
individual transforms to a pipeline, and outputs the image as a contiguous array. individual transforms to a pipeline, and outputs the image as a contiguous array.
Optionally, it can also convert the transformed image to a desired format. Optionally, it can also convert the transformed image to a desired format.
More at the [documentation pages](https://www.google.com).
Below, there are several examples of how to use this library. Below, there are several examples of how to use this library.
### Example: Transforming a Single Image ### Example: Transforming a Single Image
......
__version__ = "1.1.0" __version__ = "1.1.1"
[build-system]
requires = ["setuptools >= 61.0"]
build-backend = "setuptools.build_meta"
[project]
# Put the name of your project on PyPI.
name = "bio-volumentations"
# Put the version of your project. This field is required, although it is often marked as dynamic:
version = "1.1.1"
#dynamic = ["version"]
# https://stackoverflow.com/questions/21064581/how-to-overwrite-pypi-package-when-doing-upload-from-command-line
# If your project has dependencies, list them like this:
dependencies = [
"numpy",
"scipy",
"scikit-image",
"matplotlib",
"SimpleITK",
]
# You may want to make some of your dependencies optional, if they are only needed for a specific feature of your package.
# In that case, put them in optional-dependencies.
# https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#dependencies-and-requirements
# Declare the minimum version of Python that you support:
requires-python = ">=3.1"
# Authors (identified by a name and/or an email address)
authors = [
{name = "Lucia Hradecká", email = "lucia.d.hradecka@gmail.com"},
{name = "Filip Lux", email = "lux.filip@gmail.com"},
{name = "Samuel Šuľan"},
]
# Optionally, can also include the maintainers field
# A one-line description of your project, to show as the “headline” of your project page on PyPI
# and other places such as lists of search results:
description = "Library for 3D-5D augmentations of volumetric multi-dimensional biomedical images"
# A longer description - can use readme.md
readme = "README.md"
# Lincense - two possibilities
#license = {file = "LICENSE"}
license = {text = "MIT License"}
# Keywords to help PyPI’s search box to suggest your project when people search for these keywords
keywords = ["image", "augmentation", "3D", "volumetric", "biomedical", "bioimage",
"preprocessing", "transformation"]
# Classifiers: this information is used for searching and browsing projects on PyPI
# https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#classifiers
classifiers = [
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
]
# A list of URLs associated with your project, displayed on the left sidebar of your PyPI project page.
[project.urls]
Homepage = "https://gitlab.fi.muni.cz/cbia/bio-volumentations/-/tree/v1-1-0?ref_type=heads"
Documentation = "https://biovolumentations.readthedocs.io/v1-1-1/"
Repository = "https://gitlab.fi.muni.cz/cbia/bio-volumentations/-/tree/v1-1-0?ref_type=heads"
# MISSING FROM SETUP.PY
# entry_points={
# 'console_scripts': [
# 'bioVolumentation=bio_volumentations:__init__'
# ]
# }
# packages=setuptools.find_packages()
\ No newline at end of file
# ============================================================================================= #
# Author: Samuel Šuľan, Lucia Hradecká, Filip Lux #
# Copyright: Lucia Hradecká : lucia.d.hradecka@gmail.com #
# Filip Lux : lux.filip@gmail.com #
# #
# MIT License. #
# #
# Permission is hereby granted, free of charge, to any person obtaining a copy #
# of this software and associated documentation files (the "Software"), to deal #
# in the Software without restriction, including without limitation the rights #
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell #
# copies of the Software, and to permit persons to whom the Software is #
# furnished to do so, subject to the following conditions: #
# #
# The above copyright notice and this permission notice shall be included in all #
# copies or substantial portions of the Software. #
# #
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR #
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, #
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE #
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER #
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, #
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE #
# SOFTWARE. #
# ============================================================================================= #
try:
from setuptools import setup, find_packages
except ImportError:
from distutils.core import setup
setup(
name='bio_volumentations',
version='1.1.0',
author='Samuel Šuľan, Lucia Hradecká, Filip Lux',
packages=find_packages(),
url='https://gitlab.fi.muni.cz/cbia/bio-volumentations',
description='Library for 3D augmentations of multi-dimensional biomedical images',
keywords='image,augmentation,volumetric,bioimage,biomedical,preprocessing,transformation',
long_description_content_type='text/markdown',
long_description='''Bio-Volumentations is an image augmentation and preprocessing package for 3D, 4D, and 5D
(volumetric, multi-channel, and time-lapse) biomedical images.
This library offers a wide range of image transformations implemented efficiently for large-volume image data.
This includes both preprocessing transformations (such as intensity normalisation, padding, and type casting) and
augmentation transformations (such as affine transform, noise addition and removal, and contrast manipulation).
The Bio-Volumentations library is a suitable tool for data manipulation in machine learning applications.
It can be used with any major Python deep learning library, including PyTorch, PyTorch Lightning, TensorFlow, and Keras.
This library builds upon wide-spread libraries such as Albumentations (see the Contributions section below)
in terms of design and user interface. Therefore, it can easily be adopted by developers.
More details can be found at the project's GitLab (https://gitlab.fi.muni.cz/cbia/bio-volumentations)
or at the documentation pages.
The Bio-Volumentations library was inspired by:
- Albumentations: https://github.com/albumentations-team/albumentations
- 3D Conversion: https://github.com/ashawkey/volumentations
- Continued Development: https://github.com/ZFTurbo/volumentations
- Enhancements: https://github.com/qubvel/volumentations
- Further Enhancements: https://github.com/muellerdo/volumentations
The Bio-Volumentations library is distributed under the MIT License.
Copyright (c) 2024 Samuel Šuľan, Lucia Hradecká, Filip Lux
''',
install_requires=[
'numpy',
'scipy',
'scikit-image',
'matplotlib',
'SimpleITK',
],
entry_points={
'console_scripts': [
'bioVolumentation=bio_volumentations:__init__'
]
}
)
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