# FastPhotoStyle

**Repository Path**: mirrors/FastPhotoStyle

## Basic Information

- **Project Name**: FastPhotoStyle
- **Description**: FastPhotoStyle 是英伟达开源的照片风格转移深度学习算法实现库，给定目标照片和样式参考照片，代码可以将样式照片的风格转换至目标照片，从而生成新的风格化照片
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: https://www.oschina.net/p/fastphotostyle
- **GVP Project**: No

## Statistics

- **Stars**: 22
- **Forks**: 4
- **Created**: 2018-02-24
- **Last Updated**: 2025-11-08

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

[![License CC BY-NC-SA 4.0](https://img.shields.io/badge/license-CC4.0-blue.svg)](https://raw.githubusercontent.com/NVIDIA/FastPhotoStyle/master/LICENSE.md)
![Python 2.7](https://img.shields.io/badge/python-2.7-green.svg)
![Python 3.5](https://img.shields.io/badge/python-3.5-green.svg)

## FastPhotoStyle

### License
Copyright (C) 2018 NVIDIA Corporation.  All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).

<img src="https://raw.githubusercontent.com/NVIDIA/FastPhotoStyle/master/teaser.png" width="800" title="Teaser results"> 


### What's new
 
 | Date     | News |
 |----------|--------------|
 |2018-07-25| Migrate to pytorch 0.4.0. For pytorch 0.3.0 user, check out [FastPhotoStyle for pytorch 0.3.0](https://github.com/NVIDIA/FastPhotoStyle/releases/tag/f33e07f). |
 |          | Add a [tutorial](TUTORIAL.md) showing 3 ways of using the FastPhotoStyle algorithm.|
 |2018-07-10| Our paper is accepted by the ECCV 2018 conference!!! | 


### About

Given a content photo and a style photo, the code can transfer the style of the style photo to the content photo. The details of the algorithm behind the code is documented in our arxiv paper. Please cite the paper if this code repository is used in your publications.

[A Closed-form Solution to Photorealistic Image Stylization](https://arxiv.org/abs/1802.06474) <br> 
[Yijun Li (UC Merced)](https://sites.google.com/site/yijunlimaverick/), [Ming-Yu Liu (NVIDIA)](http://mingyuliu.net/), [Xueting Li (UC Merced)](https://sunshineatnoon.github.io/), [Ming-Hsuan Yang (NVIDIA, UC Merced)](http://faculty.ucmerced.edu/mhyang/), [Jan Kautz (NVIDIA)](http://jankautz.com/) <br>
European Conference on Computer Vision (ECCV), 2018 <br>


### Tutorial

Please check out the [tutorial](TUTORIAL.md).