Neural Style Transfer

This project is a experimentation of the popular Neural Style Transfer by Gatys et al.

This script automatically explores the parameter space by randomly selecting pairs of images, learning rate, and relative importance of style and content images.

Setup

1. In the root directory of this project, create folder pretrained-model and place the model you wish to use (in .mat format) in the folder. To download pretrained model, visit MatConvNet and download the imagenet-vgg-verydeep-19.

2. In the root directory of this project, create folder images and place images of dimensions CONFIG.IMAGE_WIDTH X CONFIG.IMAGE_HEIGHT. See utils.py for configurations.

Run

Navigate to src directory and execute python main.py.

Reference

Gatys, L. A., Ecker, A. S., & Bethge, M. (2016). Image style transfer using convolutional neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2414-2423).