Deep Learning with PyTorch

Style Transfer with Deep Neural Networks

In this notebook, we’ll recreate a style transfer method that is outlined in the paper, Image Style Transfer Using Convolutional Neural Networks, by Gatys in PyTorch

In this paper, style transfer uses the features found in the 19-layer VGG Network, which is comprised of a series of convolutional and pooling layers, and a few fully-connected layers. In the image below, the convolutional layers are named by stack and their order in the stack. Conv_1_1 is the first convolutional layer that an image is passed through, in the first stack. Conv_2_1 is the first convolutional layer in the second stack. The deepest convolutional layer in the network is conv_5_4.

It was a part of Deep learning Nanodegree by Udacity

Setup

1. Clone this repo:

git clone https://github.com/keshav787/cnn-style-transfer.git  

2. Install all the dependencies
3. Follow Instructions in cnn_Style_Transfer.ipynb