Skip to content

Revise README with installation and usage details #40

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
nathanchenseanwalter merged 1 commit into from
Dec 27, 2025
Merged

Revise README with installation and usage details #40

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
46 changes: 25 additions & 21 deletions README.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,18 +2,11 @@
keras2c
#######

|Python-Publish| |Python-Versions| |Codecov|
|Python-Publish| |Python-Versions| |Codecov|

|License| |DOI|

IMPORTANT: Keras2C has started updating to be compatible with newer versions of Python on July 9th, 2025. Changes may be breaking. To use the original/stable version, use the Release v1.0.2. https://github.com/PlasmaControl/keras2c/releases/tag/v1.0.2 with the command

.. code-block:: bash

git clone git@github.com:PlasmaControl/keras2c.git --branch v1.0.2

keras2c is a library for deploying keras neural networks in C99, using only standard libraries.
It is designed to be as simple as possible for real time applications.
keras2c is a library for deploying keras neural networks in C99, using only standard libraries. It is designed to be as simple as possible for real-time applications.

Please cite `this paper <https://doi.org/10.1016/j.engappai.2021.104182>`_ if you use this work in your research:

Expand All @@ -22,13 +15,27 @@ Please cite `this paper <https://doi.org/10.1016/j.engappai.2021.104182>`_ if yo
R. Conlin, K. Erickson, J. Abbate, and E. Kolemen, “Keras2c: A library for converting Keras neural networks to real-time compatible C,”
Engineering Applications of Artificial Intelligence, vol. 100, p. 104182, Apr. 2021, doi: 10.1016/j.engappai.2021.104182.

Quickstart
**********
Installation
************

**Recommended Installation**

The modern way to install keras2c is via pip:

.. code-block:: bash

For windows, make sure that you have gcc installed. We recommend CYGWIN with make and gcc
pip install keras2c

After cloning the repo, install the necessary packages with ``pip install -r requirements.txt``.
Alternatively, create a conda environment using ``conda env create -f environment.yml``.
To use the original/stable version, use the Release v1.0.2 (https://github.com/PlasmaControl/keras2c/releases/tag/v1.0.2) with the command:

.. code-block:: bash

git clone git@github.com:PlasmaControl/keras2c.git --branch v1.0.2

For Windows, make sure that you have **gcc** installed. We recommend **CYGWIN** with make and gcc.

Quickstart
**********

keras2c can be used from the command line:

Expand All @@ -50,21 +57,21 @@ keras2c can be used from the command line:
-t , --num_tests Number of tests to generate. Default is 10


It can also be used with a python environment in the following manner:
It can also be used within a python environment:

.. code-block:: python

from keras2c import k2c
k2c(model, function_name, malloc=False, num_tests=10, verbose=True)

For more information, see `Installation <https://f0uriest.github.io/keras2c/installation.html>`_ and `Usage <https://f0uriest.github.io/keras2c/usage.html>`_
For more information, see `Installation <https://f0uriest.github.io/keras2c/installation.html>`_ and `Usage <https://f0uriest.github.io/keras2c/usage.html>`_


Supported Layers
****************
- **Core Layers**: Dense, Activation, Dropout, Flatten, Input, Reshape, Permute, RepeatVector, ActivityRegularization, SpatialDropout1D, SpatialDropout2D, SpatialDropout3D
- **Core Layers**: Dense, Activation, Dropout, Flatten, Input, Reshape, Permute, RepeatVector, ActivityRegularization, SpatialDropout1D, SpatialDropout2D, SpatialDropout3D
- **Convolution Layers**: Conv1D, Conv2D, Conv3D, Cropping1D, Cropping2D, Cropping3D, UpSampling1D, UpSampling2D, UpSampling3D, ZeroPadding1D, ZeroPadding2D, ZeroPadding3D
- **Pooling Layers**: MaxPooling1D, MaxPooling2D, AveragePooling1D, AveragePooling2D, GlobalMaxPooling1D, GlobalAveragePooling1D, GlobalMaxPooling2D, GlobalAveragePooling2D, GlobalMaxPooling3D,GlobalAveragePooling3D
- **Pooling Layers**: MaxPooling1D, MaxPooling2D, AveragePooling1D, AveragePooling2D, GlobalMaxPooling1D, GlobalAveragePooling1D, GlobalMaxPooling2D, GlobalAveragePooling2D, GlobalMaxPooling3D, GlobalAveragePooling3D
- **Recurrent Layers**: SimpleRNN, GRU, LSTM, SimpleRNNCell, GRUCell, LSTMCell
- **Embedding Layers**: Embedding
- **Merge Layers**: Add, Subtract, Multiply, Average, Maximum, Minimum, Concatenate, Dot
Expand All @@ -83,8 +90,6 @@ ToDo
- **Merge Layers**: Broadcasting merge between different sizes
- **Misc**: models made from submodels



Contribute
**********

Expand All @@ -97,7 +102,6 @@ License

The project is licensed under the LGPLv3 license.


.. |Codecov| image:: https://codecov.io/gh/f0uriest/keras2c/branch/master/graph/badge.svg
:target: https://codecov.io/gh/f0uriest/keras2c
:alt: Code Coverage
Expand Down