Socially-Dead-Team

Content Overview

• Prerequisites
• Code Organization
• Dataset
• Slow Style Transfer
• Fast Style Transfer
• Examples
  • Demonstration of Reconstruction with White Noise Image
  • Style Images
  • Cotent Images
  • Result Images
  • Slow Style Transfer Results
  • Fast Style Transfer Results

Prerequisites

1. pytorch: 3.6.4
2. NumPy: 1.14.2
3. matplotlib: 2.2.0
4. Pillow: 5.1.0
5. cv2: 4.0.0
6. GPU: NVIDIA GPU is advised

Code Organization

SlowStyleTransfer

  1. slow_style_utils.py: some utility functions and classes 
  2. slow_style_transfer.py: the class for the implementation of slow style transfer
  3. slow_style_main.py: get code run 
  4. utils.py: some utility functions making style_transfer_learning.ipynb clean

FaststyleTransfer

  1. utils.py: helper functions 
  2. fast_style_transfer.py: main function package that contains all functions for this project
  3. transformer_net.py: class for the transform network 
  4. vgg.py: class for the vgg loss network

style_transfer_learning.ipynb
	For demonstrating the results of this project.
fast_style_training.ipynb
	For training style models for fast style transfer implementation.

Dataset

All data from COCO-2015

Demonstration of Reconstruction with White Noise Image

Slow Style Transfer

This is the implementation of Gatys method on Neural Style Transfer. For rerunning the slow style transfer, please go to the demonstration file. These are two examples of our implementation of slow style transfer with the style targets starry night and sunflowers respectively.

Fast Style Transfer

Related architecture and techniques are introduced in this paper. The main structure we utilize is demonstrated below

Examples

Style Images

Cotent Images

Result Images

Slow Style Transfer Results

Fast Style Transfer Results