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A TensorFlow framework for light field deep learning.

Project description

lfcnn - A TensorFlow framework for light field deep learning

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License and Usage

This software is licensed under the GNU GPLv3 license (see below).

If you use this software in your scientific research, please cite our paper:

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Quick Start

Have a look at the Documentation for notes on usage.

Furthermore, you can find some useful examples in the examples folder which can help you to get started.


It is recommended to use Conda to setup a new environment with tensorflow and GPU support. To install with GPU support, run

conda create -n lfcnn python=3.8 tensorflow-gpu=2.2 tensorflow numpy scipy imageio h5py cudnn cudatoolkit
conda activate lfcnn

Then, install the provided package using pip:

pip install lfcnn

Optional dependencies

Optionally, for some of LFCNN's features, install the following:

  • matplotlib (via conda or pip)
  • sacred (via pip)
  • pymongo (via conda or pip)
  • mdbh (via pip)

Installation on Windows

LFCNN is mostly compatible with all TF versions TensorFlow >= 2.0, however there is a bug in tf.keras that causes OOMs with data generators (which LFCNN uses) and multithreading and -processing. Therefore, we specify tensorflow >= 2.2 as a dependency, for which this bug has been resolved.

However, as of July 2020, TF 2.2 and TF 2.3 are not released on Anaconda for Windows. So for Windows, it is necessary to install TF via pip. However, installation of the compatible cuDNN and CUDA should still be performed via conda for simplicity. To setup the new environment with the correct CUDA and cuDNN versions, run

conda create -n lfcnn python=3.8 numpy scipy imageio h5py cudnn=7.6.5 cudatoolkit=10.1
conda activate lfcnn
pip install tensorflow==2.3 tensorflow-gpu==2.3

Furthermore, the Visual C++ redistributable has to be installed on Windows.

Finally, install LFCNN via pip as usual:

pip install lfcnn


You can manually run the tests using pytest:

$ pytest <path-to-lfcnn>/test/


Uninstall lfcnn using

$ pip uninstall lfcnn


If you are interested in contributing to LFCNN, feel free to create an issue or fork the project and submit a merge request. As this project is still undergoing restructuring and extension, help is always welcome!

For Programmers

Please stick to the PEP 8 Python coding styleguide.

The docstring coding style of the reStructuredText follows the googledoc style.


Copyright (C) 2020 The LFCNN Authors

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see

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