# STYLE2PAINTS
**Repository Path**: zwb_scott/STYLE2PAINTS
## Basic Information
- **Project Name**: STYLE2PAINTS
- **Description**: STYLE2PAINTS 是新一代的线稿上色 AI ,可根据用户上传的自定义色彩给线稿进行上色
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 33
- **Created**: 2017-11-02
- **Last Updated**: 2020-12-19
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# Lastest News
**Our new UI is under construction now. You can try it directly!**
PaintsTransfer: [http://paintstransfer.com/](http://paintstransfer.com/)




# You have just found STYLE2PAINTS
:pushpin:[GithubPage](https://lllyasviel.github.io/) :pushpin:[GithubPageChinese](https://lllyasviel.github.io/chinese) :pushpin:[StyleTransfer](https://github.com/lllyasviel/style2paints/blob/master/AnimeStyleTransfer.md)
*The previous version is now at 52.80.94.56:8000*
The AI can paint on a sketch according to a given specific color style.
The AI can transfer illustrations' style.




# Tuitions
[tuition 001](https://www.bilibili.com/video/av15014229/)
# Example 1 (Google Search results test)

A content sketch (**the first google image search result of key word 'anime sketch'**) and some style images:
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Results:
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# Example 2 (western sketch)
A western content sketch and 2 style images:
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# Example 3 (messy sketch)
A messy content sketch and 2 style images:
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# Example 4 (detailed sketch)
A detailed content sketch and 2 style images:
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# Example 5 (simple sketch)
A simple content sketch **without shadow rendering** and 2 style images:
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# CPU Server for Beginner
*you need a python 3 environment.*
pip install tensorflow
pip install keras
pip install chainer
pip install bottle
pip install gevent
pip install h5py
pip install opencv-python
git clone https://github.com/lllyasviel/style2paints.git
(then download all pretrained models from 'release' page and then put them in 'style2paints/server')
cd style2paints/server
python server.py cpu
# GPU Server for Reseachers
*you need a CUDA python 3.6 environment.*
pip install tensorflow_gpu
pip install keras
pip install chainer
pip install cupy
pip install bottle
pip install gevent
pip install h5py
pip install opencv-python
git clone https://github.com/lllyasviel/style2paints.git
(then download all pretrained models from 'release' page and then put them in 'style2paints/server')
cd style2paints/server
python server.py
# Model
Models are available in 'release' page.
1. base_generator.net -> all rights reserved 2017 style2paints
2. style2paints.net -> all rights reserved 2017 style2paints
3. google_net.net -> from [nico-opendata](https://nico-opendata.jp/en/demo/tag/index.html)
# Training Datasets
1. The recommended training dataset of illustrations is the 400k images from [nico-opendata](https://nico-opendata.jp/en/seigadata/index.html)
2. The recommended training sketches is from [sketchKeras](https://github.com/lllyasviel/sketchKeras)
# Community
QQ Group ID: 184467946
## Acknowledgements
Thanks a lot to TaiZan. This project could not be achieved without his great help.