Neural Style Transfer

Introduction

This is a Keras implementation of the paper A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. The paper presents an algorithm for combining the content of one image with the style of another image using convolutional neural networks. Here are some examples of the results that can be obtained with this algorithm:

Dependencies

• Python
• Keras 2.2.4
• Pandas 0.23.4
• Numpy 1.16.2
• Scipy 1.1.0
• Matplotlib

Usage

1. Clone the repository

git clone https://github.com/Roshan818/Neural-Style-Transfer.git
cd Neural-Style-Transfer
pip install -r requirements.txt

mkdir input
cd input
mkdir vgg19
mkdir best-artworks-of-all-time
mkdir image-classification
cd ..

2. Download the VGG-19 model and dataset

• Download the VGG-19 model here and place it in the input/vgg19 folder.
• Download the best-artworks-of-all-time dataset here and place it in the input\best-artworks-of-all-time.
• Download the image-classification dataset here and place it in the input\image-classification.

3. Run the script

Run the file style-transfer-deep-learning-algorithm.ipynb in Jupyter Notebook.

4. Results

References

• A Neural Algorithm of Artistic Style
• Neural Style Transfer: A Review