Custom Advanced Tensorflow Objects to Preprocess, Upload, Model and Augment
Project description
| Authors | Project | Build Status | License | Docs |
|---|---|---|---|---|
| R. Biondi | CATOPUMA | Windows : Ubuntu : |
Customizable Advanced Tensorflow Objects for Preoproces, Upload, Model and Augment
Overview
CATOPUMA is a Python package that offers customizable advanced TensorFlow objects for tasks such as preprocessing, uploading, modeling, and augmenting. It includes several classes that facilitate the loading, augmentation, and preprocessing of images for deep learning models.
The main functionalities of CATOPUMA are as follows:
-
Feeder: This module contains claasses to helps load images batch-wise from local directories and eventuallly perform data augmentation and image preprocessing on the fly.
-
Losses: The losses module provide a series of custom losses. The overload if the arimetic operators allows to easy combine different losses.
-
Preprocessing: CATOPUMA provides the implementation of some classes to easily perform the basic preprocessing steps on images and labels
-
Core: the core functionality of catopèuma are the bastract classess providing a base for each of the basic functionality (like preprocessin, loss, data augmentation, etc.), allowing an easy customization of the various objects,,
Overall, CATOPUMA simplifies the process of preparing image datasets for deep learning models by providing convenient classes and functions for loading, augmenting, and preprocessing images
Installation
CATOPUMA offers different installation way. The installation process is the same for each Operative System
Install with pip
pip installer is not yet available
Install with conda
conda installer is no yet availabel
Install from source
Download the project or the latest release:
git clone https://github.com/RiccardoBiondi/Catopuma
Now install the required packages:
python -m pip install -r requirements.txt
And you are ready to build the package:
python setup.py develop --user
Testing
We have provide a test routine in test directory. This routine use:
-
pytest >= 3.0.7
-
hypothesis >= 4.13.0
Please install these packages to perform the test. You can run the full set of test with:
python -m pytest
Getting Started
License
The CATOPUMA package is licensed under the MIT "Expat" License.
Contribute
Any contribution is more than welcome. Just fill an issue or a pull request and we will check ASAP!
How to Commit
Authors
References
Iakubovskii, P. Segmentation Models. GitHub repository (2019). https://github.com/qubvel/segmentation_models
Citation
If you have found CATOPUMA helpful in your project
@misc{catopuma,
author = {Biondi, Riccardo},
title = {CATOPUMA - Customizable Advanced Tensorflow Objects to Preprocess, Upload, Model and Augment},
year = {2023},
publisher = {GitHub},
howpublished = {\url{https://github.com/RiccardoBiondi/Catopuma}},
}
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