# style2paints
**Repository Path**: bit2atom/style2paints
## Basic Information
- **Project Name**: style2paints
- **Description**: sketch + style = paints !
- **Primary Language**: JavaScript
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-25
- **Last Updated**: 2020-12-19
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# STYLE2PAINTS
[ZhiHu](https://zhuanlan.zhihu.com/p/29331219) [BiliBili](https://www.bilibili.com/video/av14443094/)
The AI can paint on a sketch accroding to a given specific color style.

# 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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# Requirement
pip install tensorflow_gpu
pip install keras
pip install chainer
pip install cupy
pip install bottle
pip install h5py
pip install opencv-python
# Launch Server
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 avaliable in 'release' page.
1. base_generator.net all rights reserved 2017 style2paints
2. paintschainer.net from [paintschainer](https://github.com/pfnet/PaintsChainer)
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
# Paper Reference
The paper is accecped by ACPR 2017.
@article{StyleTansferForAnime,
Author = {Lvmin Zhang and Yi Ji and Xin Lin},
Title = {Style Transfer for Anime Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN},
Journal = {arXiv:1706.03319},
Year = {2017}
}