Style Transfer (Neural Style)

Tensorflow implementation of Image Style Transfer (Neural Style)

Preferred Environments

• OS : Windows 10 or Ubuntu 14.04 ~
• GPU : ~
• Library : TF 1.x with CUDA ~ + CuDNN ~
• Python 3.x

Prerequisites

• Python 3.x
• Tensorflow 1.x
• Scipy
• Pillow
• Internet :) (for downloading VGG19 pre-trained model)

Usage

$ python style_transfer.py --content <content image> --style <style image> ...

Example : python style_transfer.py --content content/deadpool.jpg --style style/guernica.jpg

Arguments

Required

• --content : file path of a content image, default : contents/deadpool.jpg
• --style : file path of a style image, default : styles/guernica.jpg

Optional

• --content_w : weight of content loss, default : 0.05
• --style_w : weight of style loss, default : 0.02
• --image_width : file path of a content image, default : 333
• --image_height : file path of a style image, default : 250
• --train_steps : total training epochs, default : 500

Repo Tree

│
├── checkpoints       (model checkpoint)
│    ├── checkpoint
│    ├── ...
│    └── xxx.ckpt
├── contents          (content images)
│    ├── deadpool.jpg
│    └── ...
├── styles            (style images)
│    ├── guernica.jpg
│    └── ...
├── outputs           (results of style-transfer)
│    ├── deadpool_guernica_xxx.jpg
│    └── ...
├── graphs            (tensorboard)
│    └── ...
├── utils.py          (image utils & download pre-trained model)
├── vgg19.py          (VGG19 model)
└── style_transfer.py (style transfer)

Sample results

DeadPool with guernica & monet & vangogh (333 x 250)

conetent\style	guernica	monet	vangogh

Stata with wave & udnie (1024 x 679)

conetent\style	wave	udnie

Author

HyeongChan Kim / (@kozistr, @zer0day)