emptymalei / caffe-unet-docker

The U-Net Segmentation server (caffe_unet) for Docker

Added Dockerfile for CPU based model

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The U-Net segmentation server (caffe_unet) - in Docker

This repository contains a Dockerfile and scripts to build and run the U-Net Segmentation server (caffe_unet) in Docker containers.

Author: Thorsten Falk ([email protected])

If you use this project or parts of it in your research, please cite the corresponding paper:

@Article{FMBCAMBBR19,
  author       = "T. Falk and D. Mai and R. Bensch and {\"O}. {\c{C}}i{\c{c}}ek and A. Abdulkadir and Y. Marrakchi and A. B{\"o}hm and J. Deubner and Z. J{\"a}ckel and K. Seiwald and A. Dovzhenko and O. Tietz and C. Dal Bosco and S. Walsh and D. Saltukoglu and T. L. Tay and M. Prinz and K. Palme and M. Simons and I. Diester and T. Brox and O. Ronneberger",
  title        = "U-Net – Deep Learning for Cell Counting, Detection, and Morphometry",
  journal      = "Nature Methods",
  volume       = "16",
  pages        = "67--70",
  month        = "Jan",
  year         = "2019",
  url          = "http://lmb.informatik.uni-freiburg.de/Publications/2019/FMBCAMBBR19"
}

See the paper and the project page for more details.

0. Requirements

We use nvidia-docker for reliable GPU support in the containers. This is an extension to Docker and can be easily installed with just two commands. To run the networks, you need an nVidia GPU with >1GB of memory (at least Kepler).

1. Building the Docker image

Simply run make. This will create two Docker images: The OS base (an Ubuntu 18.04 base extended by nVidia, with CUDA 10.0 and CuDNN 7.3), and the "lmb-unet-server" image on top. In total, about 2.6GB of space will be needed after building. This build will simply download the binary package from our project page, setup the environment to use it and when running the image start an SSH server that can be accessed via port 2222 of the docker host machine.

Alternatively you can run make src to build caffe_unet from source. The resulting image "lmb-unet-server-src" should work identical, but requires more space (about 6.7GB). It is mainly intended to show you how caffe_unet can be built in a fresh Ubuntu installation.

2. Running containers

Run the startServer.sh script. It will ask you to set the password for unetuser. Then the ssh server is started and you get an interactive shell in the container and the server awaits U-Net jobs on port 2222. Closing the session also terminates the server.

4. License

The files in this repository are under the GNU General Public License v3.0