How-to-Generate-Art-Demo

This is the code for "How to Generate Art - Intro to Deep Learning #8' by Siraj Raval on YouTube

##Overview

This is the code for this video on Youtube by Siraj Raval as part of the Intro to Deep Learning Nanodegree with Udacity. We're going to re-purpose the pre-trained VGG16 convolutional network that won the ImageNet competition in 2014 for image classification to transfer the style of a given image to another. This is the original paper on the topic.

##Dependencies

run pip install -r requirements.txt to install the necessary dependencies

##Usage

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"
}

Then you can run the code via typing jupyter notebook into terminal

#Coding Challenge - Due Date is Thursday, March 9th at 12 PM PST

Use 2 different style images and transfer them both onto a base image. This can be done several ways, take your pic! And if you want even more of a challenge, bonus points are given if you instead perform basic style transfer on video. Remember, a video is just a series of image frames. You'll learn a lot about matrix operations by doing this. Good luck!

##Credits

The credits for this code go to hnarayanan. I've merely created a wrapper to get people started.