Docker image for deep learning on geo-spatial imagery

Requires

• nvidia-docker

Features

• Built on ubuntu 16.04 with CUDA 8.0 and cudnn 6
• Python 3.5.2
  • tensorflow and keras (GPU enabled)
  • scikit-learn, scikit-image, pandas
  • Jupyter Notebook
  • pycharm community (2017.3)
• R (most recent)
  • sf, raster, velox (including system dependencies)
  • tensorflow for R
  • RStudio Server (1.1.383)
• git & subversion

Usage

Run container in background with GUI support:

nvidia-docker run -td -u coder -p 8787:8787 -p 8888:8888 -p 8008:8008 -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix:ro geo_deeplearn

Option	Descr
-td	makes sure container runs in background
-u coder	login as user 'coder'
-e and -v	ensure GUI support (for pycharm)
-p 8787:8787	port forwarding for rstudio
-p 8888:8888	port forwarding for jupyter
-p 8008:8008	port forwarding for tensorboard

Don't forget to run xhost + on local machine for GUI support [warning: not safe].

Enter the running container:

docker exec -it [container_id] bash 

Start the Rstudio Server

sudo rstudio-server start

Start Jupyter Notebook

jupyter notebook --ip=0.0.0.0 --no-browser

Start pycharm

pycharm