This project was done as part of the Udacity's PyTorch Scholarship Challenge from Facebook. as part of this project I'll recreate style transfer method that is outlined in the paper, Image Style Transfer Using Convolutional Neural Networks, by Gatys in PyTorch.
Style transfer relies on separating the content and style of an image. Given one content image and one style image, we aim to create a new, target image which should contain our desired content and style components:
- objects and their arrangement are similar to that of the content image
- style, colors, and textures are similar to that of the style image
An example is shown below, where the content image is of a cat, and the style image is of Hokusai's Great Wave. The generated target image still contains the cat but is stylized with the waves, blue and beige colors, and block print textures of the style image!
