Convolutional neural networks for artistic style transfer

This repository contains (TensorFlow and Keras) code that goes along
with a related blog post and talk
(PDF). Together, they act as a systematic look at
convolutional neural networks from theory to practice, using artistic
style transfer as a motivating example. The blog post provides context
and covers the underlying theory, while working through the Jupyter
notebooks in this repository offers a more hands-on learning
experience.

If you have any questions about any of this stuff, feel free to open
an issue or tweet at me: @copingbear.

Setup

Install Python (2.7), pip and virtualenv on your machine. The
instructions to do this depend on your operating system (Linux, macOS,
Windows), but there are many tutorials on the internet that should
help you get started.
Once you have the above setup, it is quite easy to setup the
requirements for the notebooks in this repository. First you clone a
copy of this repository:
```
git clone https://github.com/hnarayanan/artistic-style-transfer.git
```
Then you navigate to this folder in your shell and then install the
requirements needed for the Jupyter notebooks.
```
cd artistic-style-transfer
virtualenv venv
source venv/bin/activate
pip install -r requirements.txt
```

If it doesn’t exist, create a file called ~/.keras/keras.json and
make sure it looks like the following:

{
    "image_dim_ordering": "tf",
    "epsilon": 1e-07,
    "floatx": "float32",
    "backend": "tensorflow"
}

That’s it! You can now start Jupyter and browse, open, run and
modify the notebooks.
```
jupyter notebook
```

Convolutional neural networks for artistic style transfer

Setup

Contents

iPython Notebooks

External Resources