Skip to main content

A TensorFlow framework for light field deep learning.

Project description

lfcnn - A TensorFlow framework for light field deep learning

build status coverage report PyPI PyPI PyPI

Image

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:

Not yet available. Please check back later.

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.

Installation

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 is 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==2.2 tensorflow-gpu==2.2

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

Finally, install LFCNN via pip as usual:

pip install lfcnn

Testing

You can manually run the tests using pytest:

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

Uninstallation

Uninstall lfcnn using

$ pip uninstall lfcnn

Contribute

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.

License

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 https://www.gnu.org/licenses/.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lfcnn-0.3.tar.gz (59.0 kB view details)

Uploaded Source

Built Distribution

lfcnn-0.3-py3-none-any.whl (116.2 kB view details)

Uploaded Python 3

File details

Details for the file lfcnn-0.3.tar.gz.

File metadata

  • Download URL: lfcnn-0.3.tar.gz
  • Upload date:
  • Size: 59.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3

File hashes

Hashes for lfcnn-0.3.tar.gz
Algorithm Hash digest
SHA256 031f61dfd87314e4d5e418c558debd3007295dfbc4635b93cb14522b322d5b88
MD5 26e9843a633a69b8bf935bbb836d7247
BLAKE2b-256 113098d34035a30f30e72d253a50e8c591a0badf5d599da6f52ec1afbd626972

See more details on using hashes here.

File details

Details for the file lfcnn-0.3-py3-none-any.whl.

File metadata

  • Download URL: lfcnn-0.3-py3-none-any.whl
  • Upload date:
  • Size: 116.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3

File hashes

Hashes for lfcnn-0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 dbe59714cf2da21813b33a08e01aee29d1b28c4444a7413f516e6af27523ad1f
MD5 1f5bdb0fac65cc70240a33c374b50652
BLAKE2b-256 ebe349d6a8d6306898b18ca59d31718eef440bf2665edffb8c68fbf7fa0566b4

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page