An implementation of "A Neural Algorithm of Artistic Style" (http://arxiv.org/abs/1508.06576) in Keras

The code present in this repository is presented in this blog.

The code is written in Keras 2.2.2

This is a 5-sec gif of Chicago city painted in the style of Rain Princess

Content Image	Style Image

KeSTra is built using Python 3.5. The easiest way to set up a compatible environment is to use Conda. This will set up a virtual environment with the exact version of Python used for development along with all the dependencies needed to run KeSTra.

1. Download and install Conda.
2. Create a Conda environment with Python 3.

(Note: enter cd ~ to go on $HOME , then perform these commands)

``` conda create --name *your env name* python=3.5 ``` 

You will get the following, kestra-test is the env name used in this example

Solving environment: done ## Package Plan ## environment location: /home/user/anaconda3/envs/kestra-test added / updated specs: - python=3.5 The following NEW packages will be INSTALLED: ca-certificates: 2018.12.5-0 certifi: 2018.8.24-py35_1 libedit: 3.1.20181209-hc058e9b_0 libffi: 3.2.1-hd88cf55_4 libgcc-ng: 8.2.0-hdf63c60_1 libstdcxx-ng: 8.2.0-hdf63c60_1 ncurses: 6.1-he6710b0_1 openssl: 1.0.2p-h14c3975_0 pip: 10.0.1-py35_0 python: 3.5.6-hc3d631a_0 readline: 7.0-h7b6447c_5 setuptools: 40.2.0-py35_0 sqlite: 3.26.0-h7b6447c_0 tk: 8.6.8-hbc83047_0 wheel: 0.31.1-py35_0 xz: 5.2.4-h14c3975_4 zlib: 1.2.11-h7b6447c_3 Proceed ([y]/n)? *Press y* Preparing transaction: done Verifying transaction: done Executing transaction: done # # To activate this environment, use: # > source activate kestra-test # # To deactivate an active environment, use: # > source deactivate # 

The environment is successfully created.

3. Now activate the Conda environment.

   source activate *your env name* 

   You will get the following

   (kestra-test) amogh@hp15X34:~$ 

   Enter conda list to get the list of available packages

    (kestra-test) amogh@hp15X34:~$ conda list # packages in environment at /home/amogh/anaconda3/envs/mlwp-test: # # Name Version Build Channel ca-certificates 2018.12.5 0 certifi 2018.8.24 py35_1 libedit 3.1.20181209 hc058e9b_0 libffi 3.2.1 hd88cf55_4 libgcc-ng 8.2.0 hdf63c60_1 libstdcxx-ng 8.2.0 hdf63c60_1 ncurses 6.1 he6710b0_1 openssl 1.0.2p h14c3975_0 pip 10.0.1 py35_0 python 3.5.6 hc3d631a_0 readline 7.0 h7b6447c_5 setuptools 40.2.0 py35_0 sqlite 3.26.0 h7b6447c_0 tk 8.6.8 hbc83047_0 wheel 0.31.1 py35_0 xz 5.2.4 h14c3975_4 zlib 1.2.11 h7b6447c_3 

4. Install the required dependencies.

   (kestra-test) amogh@hp15X34:~$ conda install --yes --file *path to requirements.txt* 

5. In case you are not able to install the packages or getting PackagesNotFoundError Use the following command conda install -c conda-forge *list of packages separated by space*.

• It is well tested
• It passes style checks (PEP8 compliant)
• It can compile in its current state (and there are relatively no issues)

• FAQs (coming soon)
• Documentation (coming soon)

Feel free to submit issues and enhancement requests.

Please refer to each project's style guidelines and guidelines for submitting patches and additions. In general, we follow the "fork-and-pull" Git workflow.

1. Fork the repo on GitHub
2. Clone the project to your own machine
3. Commit changes to your own branch
4. Push your work back up to your fork
5. Submit a Pull request so that we can review your changes

NOTE: Be sure to merge the latest from "upstream" before making a pull request!