Skip to main content

A highly configurable toolkit for training 3d/2d CNNs and general Neural Networks

Project description

https://badge.fury.io/py/elektronn.svg http://anaconda.org/conda-forge/elektronn/badges/version.svg

ELEKTRONN is a highly configurable toolkit for training 3D/2D CNNs and general Neural Networks.

It is written in Python 2 and based on Theano, which allows CUDA-enabled GPUs to significantly accelerate the pipeline.

The package includes a sophisticated training pipeline designed for classification/localisation tasks on 3D/2D images. Additionally, the toolkit offers training routines for tasks on non-image data.

ELEKTRONN was created by Marius Killinger and Gregor Urban at the Max Planck Institute For Medical Research to solve connectomics tasks.

Logo+Example

Membrane and mitochondria probability maps. Predicted with a CNN with recursive training. Data: zebra finch area X dataset j0126 by Jörgen Kornfeld.

Toy Example

$ elektronn-train MNIST_CNN_warp_config.py

This will download the MNIST data set and run a training defined in an example config file. The plots are saved to ~/CNN_Training/2D/MNIST_example_warp.

File structure

ELEKTRONN
├── doc                     # Documentation source files
├── elektronn
│   ├── examples            # Example scripts and config files
│   ├── net                 #  Neural network library code
│   ├── scripts             #  Training script and profiling script
│   ├── training            #  Training library code
│   └── ...
├── LICENSE.rst
├── README.rst
└── ...

Project details


Download files

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

Files for elektronn, version 1.0.14
Filename, size File type Python version Upload date Hashes
Filename, size elektronn-1.0.14-cp27-cp27m-manylinux1_x86_64.whl (484.1 kB) File type Wheel Python version cp27 Upload date Hashes View
Filename, size elektronn-1.0.14-cp27-cp27mu-manylinux1_x86_64.whl (484.1 kB) File type Wheel Python version cp27 Upload date Hashes View
Filename, size elektronn-1.0.14.tar.gz (109.0 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page