generate docs and update README.md

README.md

 # Bio-Volumentations
 
-Image augmentation and preprocessing package for 3D, 4D, and 5D biomedical images.
+`Bio-Volumentations` is an image augmentation and preprocessing package for 3D, 4D, and 5D biomedical images.
 
+It offers a range of image transformations implemented efficiently for time-lapse multi-channel volumetric 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. 
+Importantly, it can be used with any major Python deep learning library.
+
+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 users.
 
 # Installation
 
-Install the package from pip using
+Install the package from PyPi using
 ```python
 pip install bio-volumentations
 ```
@@ -56,10 +65,10 @@ Below, there are several examples of how to use this library.
 ### Example: Transforming a Single Image
 
 ```python
-# Create the transformation using Compose from a list of transformations
 import numpy as np
 from bio_volumentations import Compose, RandomGamma, RandomRotate90, GaussianBlur
 
+# Create the transformation using Compose from a list of transformations
 aug = Compose([
         RandomGamma(gamma_limit = (0.8, 1,2), p = 0.8),
         RandomRotate90(axes = [1, 2, 3], p = 1),
@@ -97,7 +106,7 @@ as stand-alone targets (see below).
 If a `Random...` transform receives multiple targets on its input in a single call,
 the same random numbers are used to transform all of these targets.
 
-however, some transformations might behave slightly differently for the individual
+However, some transformations might behave slightly differently for the individual
 target types. For example, `RandomCrop` works in the same way for all target types, while
 `RandomGaussianNoise` only affects the `image` target and leaves the `mask` and
 `float_mask` targets unchanged. Please consult the documentation of respective transforms
@@ -229,7 +238,7 @@ We would thus like to thank their authors, namely:
 
 # Citation
 
-TODO
+TBA
 
 
 

__init__.py

-# ============================================================================================= #
-#  Author:       Pavel Iakubovskii, ZFTurbo, ashawkey, Dominik Müller,                          #
-#                Samuel Šuľan, Lucia Hradecká, Filip Lux                                        #
-#  Copyright:    albumentations:    : https://github.com/albumentations-team                    #
-#                Pavel Iakubovskii  : https://github.com/qubvel                                 #
-#                ZFTurbo            : https://github.com/ZFTurbo                                #
-#                ashawkey           : https://github.com/ashawkey                               #
-#                Dominik Müller     : https://github.com/muellerdo                              #
-#                Lucia Hradecká     : lucia.d.hradecka@gmail.com                                #
-#                Filip Lux          : lux.filip@gmail.com                                       #
-#                                                                                               #
-#  Volumentations History:                                                                      #
-#       - Original:                 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                 #
-#       - Biomedical Enhancements:  https://gitlab.fi.muni.cz/cbia/bio-volumentations           #
-#                                                                                               #
-#  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.                                                                                    #
-# ============================================================================================= #
-
-from .bio_volumentations.augmentations.transforms import *
-from .bio_volumentations.conversion.transforms import *
-from .bio_volumentations.core.composition import *
-from .bio_volumentations.core.transforms_interface import *
-

docs/Makefile

@@ -5,8 +5,8 @@
 # from the environment for the first two.
 SPHINXOPTS    ?=
 SPHINXBUILD   ?= sphinx-build
-SOURCEDIR     = .
-BUILDDIR      = _build
+SOURCEDIR     = source
+BUILDDIR      = build
 
 # Put it first so that "make" without argument is like "make help".
 help:

docs/_build/html/_sources/index.rst.txt

-.. volumentations_biomedicine documentation master file, created by
-   sphinx-quickstart on Fri Sep 22 13:30:00 2023.
-   You can adapt this file completely to your liking, but it should at least
-   contain the root `toctree` directive.
-
-Text pred modulami. 
-Text je *reStructuredText*. Zoznam možností čo sa dá s týmto formátom robiť sa nachádza na: tejto 
-`stránke <https://www.sphinx-doc.org/en/master/usage/restructuredtext/index.html>`_
-
-
-Welcome to volumentations_biomedicine's documentation!
-======================================================
-
-.. toctree::
-   :maxdepth: 3
-   :titlesonly:
-   :caption: Contents:
-
-   Augumentations <volumentations_biomedicine.augmentations>
-   Conversions <volumentations_biomedicine.conversion>
-   Composition <volumentations_biomedicine.composition>
-   Transforms interface <volumentations_biomedicine.transforms_interface>
-
-
-
-Text po moduloch.   
-   
-

docs/_build/html/_sources/volumentations_biomedicine.augmentations.rst.txt

-
-volumentations\_biomedicine.augmentations.transforms module
------------------------------------------------------------
-
-.. automodule:: volumentations_biomedicine.augmentations.transforms
-   :members:
-   :undoc-members:
-   :show-inheritance:

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