https://github.com/mingtaoguo/real-time-arbitrary-style-transfer-adain-tensorflow

This code mainly implement the paper ' Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization ' by TensorFlow
https://github.com/mingtaoguo/real-time-arbitrary-style-transfer-adain-tensorflow

arbitrary-style-transfer real-time-style-transfer style-transfer tensorflow vgg19

Last synced: about 2 months ago
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This code mainly implement the paper ' Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization ' by TensorFlow

• Host: GitHub
• URL: https://github.com/mingtaoguo/real-time-arbitrary-style-transfer-adain-tensorflow
• Owner: MingtaoGuo
• License: mit
• Created: 2018-02-21T13:21:55.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2018-07-24T09:36:56.000Z (about 7 years ago)
• Last Synced: 2025-07-10T16:46:14.582Z (3 months ago)
• Topics: arbitrary-style-transfer, real-time-style-transfer, style-transfer, tensorflow, vgg19
• Language: Python
• Homepage:
• Size: 4.28 MB
• Stars: 17
• Watchers: 4
• Forks: 5
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
Introduction

--------------

This code mainly implement the paper [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization](https://arxiv.org/abs/1703.06868) which address the problem of arbitrary style transfer in real-time. The main contribution of this paper is 'Adaptive Instance Normalization(AdaIN)' proposed by Xun Huang etc. 

![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/AdaIN.jpg)

Procedure of this method is as shown in follow figure.

![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/style_transfer_network.jpg)

How to train the network

------------------------

Python packages you need:

1. python 3.x

2. tensorflow 1.4.0

3. numpy

4. scipy

5. pillow

Data sets you need:

1. Content images data sets ([MSCOCO](http://images.cocodataset.org/zips/train2017.zip))

    Firstly, Unzip the MSCOCO dataset, and then put all images into the folder 'content'

2. Style images data sets ([wikiart](https://www.kaggle.com/c/painter-by-numbers/data))

    Firstly, Unzip the wikiart dataset, and then put all images into the folder 'style'

    

Pretrained model vgg19:

1. Please click [BaiduYun](https://pan.baidu.com/s/1CO-A2GOoym7eCw0hQsvEyw) to download

    when you have downloaded the file 'vgg.mat', put it into the folder 'vgg_para'.

Results of our code

--------------------

Style | ![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/ori.jpg) | ![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/ori1.jpg)

:-- | :--: | --:

![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/s1.jpg) | ![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/result1.jpg)  | ![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/result3.jpg)

![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/s2_3.jpg) | ![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/result6.jpg)  | ![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/result5.jpg)

![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/fire.jpg) | ![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/result7.jpg)  | ![](https://github.com/MingtaoGuo/Real-time-Arbitrary-Style-Transfer/blob/master/Figures/result4.jpg)