A few weeks ago the blogosphere [1] went kinda crazy when A Neural Algorithm of Artistic Style was published. I have to admit, I thought the results were pretty impressive and was looking forward to playing with the algorithm myself. All I needed was

  1. Someone to implement the algorithm for me (too busy and lazy to do it myself)
  2. A GPU
  3. Some free time

The following are some notes I took on how to get started. I hope they help.

The Setup

I started with launching an GPU instance, pre-installed with CUDA, etc. on Amazon’s US-East data center (ami-55deaf30). I actually initially tried to install the software myself, but was unable so I moved on. I have a separate repo for my installation work here.

After your instance is running, login and you need to start installing software. First we need to install cudarray.

git clone https://github.com/andersbll/cudarray cd cudarray

I also followed the directions and set the following variables up before building anything (add these to your bashrc and do not forget to call source before building)

export CUDNN_ENABLED=1 export INSTALL_PREFIX=/usr/local/ export CUDA_PREFIX=/usr/local/cuda-7.5/

Now it is time to build the library:

make; sudo make install;

Assuming you do not have any issues with building the library, you can now install the python bindings:

sudo python setup.py install

Next, we need to install the deeppy library.

git clone https://github.com/andersbll/deeppy cd deeppy sudo python setup.py install

I had no problem at this point but when I ran the command the software could not find the CUDA libraries:

ubuntu@ip-172-31-16-25:~/neural_artistic_style$ python neural_artistic_style.py --subject images/tuebingen.jpg --style images/starry_night.jpg /usr/lib/python2.7/dist-packages/pkg_resources.py:1031: UserWarning: /home/ubuntu/.python-eggs is writable by group/others and vulnerable to attack when used with get_resource_filename. Consider a more secure location (set with .set_extraction_path or the PYTHON_EGG_CACHE environment variable). warnings.warn(msg, UserWarning) CUDArray: CUDA back-end not available, using NumPy.

Fixing this was as simple as setting the LD_LIBRARY_PATH so the software could find the appropriate shared libarires:

export LD_LIBRARY_PATH='/home/ubuntu/cudarray/build/;/usr/local/cuda-7.5/targets/x86_64-linux/lib/'

That is it, I was able to utlize the library and make neural art:

input

output

output

output

output

[1] http://www.dailymail.co.uk/sciencetech/article-3214634/The-algorithm-learn-copy-artist-Neural-network-recreate-snaps-style-Van-Gogh-Picasso.html