Metadata-Version: 2.1
Name: GenericSNN
Version: 1.0.1
Summary: Python package that implements generic functionalities for Spiking Neural Network creation, fit and prediction.
Home-page: https://gitlab.eesysmart.de/public-ai-team/genericsnn
Author: Eesy-Innovation GmbH
License: Proprietary
Classifier: Programming Language :: Python
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.rst
Requires-Dist: tensorflow==2.9
Requires-Dist: nengo==3.2
Requires-Dist: nengo_dl==3.5
Requires-Dist: nengo_extras==0.5.0
Requires-Dist: numpy==1.24.2
Requires-Dist: opencv-python==4.7.0.68
Requires-Dist: matplotlib==3.6.3

GenericSNN is a Python package for developing Spiking Neural Networks based on Nengo and Nengo DL. This package allows you to build SNN models, simulate, train and test them. GenericSNN enables the user to easily define all these steps and provide general configuration, if required, based on a selection of the problem type by the user. As a result, the whole process is easier than using other tools which aims at an expert user. It is not designed for detailed simulation of biological networks.

# Installation instructions
Use pip to install GenericSNN and required dependencies

More details about the package can be found in the website of the Eesy innovation GmbH or in the Gitlab page of this package: https://gitlab.eesysmart.de/public-ai-team/genericsnn

# License
GenericSNN is released under a GPL license. 
