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.gitignore finished readme except arxiv link Apr 27, 2017
DataProvider2D.lua Initial Commit Apr 7, 2017
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train_model_2D.lua updates Apr 25, 2017

Torch Integrated Cell

Model Architecture

Image-driven generative cell modelling with adversarial autoencoders:

For the updated 3D version, please see:

Building a 3D Integrated Cell


Installing on linux is recommended.


Running on docker is recommended, though not required.

  • install torch on docker / nvidia-docker as in e.g. this guide:
  • download the training images: aws s3 cp s3:// . --recursive --no-sign-request


After you clone this repository, you will need to edit the mount points for the images in to point to where you saved them. Once those locations are properly set, you can start the docker image with


Once you're in the docker container, you can train the model with


This will take a while, probably about 12-18 hours.

Project website

Example outputs of this model can be viewed at


If you find this code useful in your research, please consider citing the following paper:

   title={Generative Modeling with Conditional Autoencoders: Building an Integrated Cell},
   author={Gregory R. Johnson, Rory M. Donovan-Maiye, Mary M. Maleckar},
   journal={arXiv preprint arXiv:1705.00092},


Gregory Johnson E-mail:


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