Metadata-Version: 2.1
Name: med-dataloader
Version: 0.1.14
Summary: A general-purpose Dataloader for Tensorflow 2.x. It supports many medical image formats.
Home-page: https://github.com/mrossi93/med_dataloader
Author: Matteo Rossi
Author-email: rossimatteo1993@gmail.com
License: MIT license
Keywords: med_dataloader
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.5
Description-Content-Type: text/x-rst
License-File: LICENSE
License-File: AUTHORS.rst

=========================
Medical Images Dataloader
=========================


.. image:: https://img.shields.io/pypi/v/med_dataloader.svg
        :target: https://pypi.python.org/pypi/med_dataloader


.. image:: https://img.shields.io/travis/com/mrossi93/med_dataloader?branch=master
        :target: https://travis-ci.com/mrossi93/med_dataloader
        

.. image:: https://readthedocs.org/projects/med-dataloader/badge/?version=latest
        :target: https://med-dataloader.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status


.. image:: https://pyup.io/repos/github/mrossi93/med_dataloader/shield.svg
     :target: https://pyup.io/repos/github/mrossi93/med_dataloader/
     :alt: Updates



A general-purpose Dataloader for Tensorflow 2.x. It supports many medical image formats.


* Free software: MIT license
* Documentation: https://med-dataloader.readthedocs.io.


Features
--------

* TODO

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

0.1.14 (2022-05-16)
-------------------

* Improved handling of img_size parameters for both 2D and 3D images.
  
  * User can now declare img_size as a 2- or 3-elements list.
  
  * Automatic zero-padding or center-based cropping is performed to adapt the size of the image to the declare img_size parameter.

* New features: 3D volumes can be patched into smaller cubic patches. Overlapping between patches is also supported.

0.1.13 (2022-03-10)
-------------------

* New function: now dataset can be generated also by reading a json file containing list of file paths.

0.1.12 (2021-10-29)
-------------------

* Fixed minor bug in function norm_with_bounds

0.1.11 (2021-09-10)
-------------------

* Fixed support for 3D Images
* Fixed minor bugs

0.1.10 (2021-05-11)
-------------------

* Added support one-hot encoding in case of multi-class label

0.1.9 (2021-05-11)
------------------

* Added support for RGB Images
* Fixed some bugs related to norm_bounds types

0.1.8 (2021-05-09)
------------------

* Main Changes in the package structure. Now there are two main functions: 
  generate_dataset and get_dataset, both leveraging on DataLoader class.
* The generation of the dataset can be handled also by CLI, to simplify usage.
* Processed data can live by themself. No more need to transfer also original
  file (e.g. to Drive to make use of them on Colab)

0.1.6 (2021-05-06)
------------------

* Improved flexibility for image data types. Now cache dimension reflects the
  actual dataset dimension.

0.1.5 (2021-04-30)
------------------

* Added support for 3D files: now Dataloader automatically detects whether a
  file is 2D or 3D and returns the properly sized dataset. Please remember that
  med_dataloader returns tf.data.Dataset object for 2D tasks, 3D is not yet
  supported.
* Added new notebook in examples folder.

0.1.4 (2021-04-29)
------------------

* Improved code flexibility:
    * It is possibile to choose which type of data augmentation is performed
    * Boundaries for data normalization can be set by the user
    * Images can be resized automatically by the user
* Added basic_usage example also as a notebook

0.1.1 (2021-04-20)
------------------

* Added code for package
* Basic example of usage inside folder "examples"
* Partial documentation

0.1.0 (2021-04-16)
------------------

* First release on PyPI.


