waifu2x
Image Super-Resolution for anime/fan-art using Deep Convolutional Neural Networks.
Demo-Application can be found at http://waifu2x.udp.jp/ .
Summary
Click to see the slide show.
References
waifu2x is inspired by SRCNN [1]. 2D character picture (HatsuneMiku) is licensed under CC BY-NC by piapro [2].
- [1] Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang, "Image Super-Resolution Using Deep Convolutional Networks", http://arxiv.org/abs/1501.00092
- [2] "For Creators", http://piapro.net/en_for_creators.html
Public AMI
AMI name: waifu2x server
AMI ID: ami-75f01931
Region: N. California
Instance: g2.2xlarge (require a GPU)
OS: Ubuntu 14.04
User: ubuntu
Dependencies
Hardware
- NVIDIA GPU (Compute Capability 3.0 or later)
Platform
Packages (luarocks)
- cutorch
- cunn
- cudnn
- graphicsmagick
- turbo
- md5
- uuid
NOTE: Turbo 1.1.3 has bug in file uploading. Please install from the master branch on github.
Installation
Setting Up the Command Line Tool Environment
(on Ubuntu 14.04)
Install Torch7
sudo apt-get install curl
curl -s https://raw.githubusercontent.com/torch/ezinstall/master/install-all | sudo bash
Install CUDA and cuDNN.
Google! Search keyword is "install cuda ubuntu" and "install cudnn ubuntu"
Install packages
sudo luarocks install cutorch
sudo luarocks install cunn
sudo luarocks install cudnn
sudo apt-get install graphicsmagick libgraphicsmagick-dev
sudo luarocks install graphicsmagick
Test the waifu2x command line tool.
th waifu2x.lua
Setting Up the Web Application Environment (if you needed)
Install luajit 2.0.4
curl -O http://luajit.org/download/LuaJIT-2.0.4.tar.gz
tar -xzvf LuaJIT-2.0.4.tar.gz
cd LuaJIT-2.0.4
make
sudo make install
Install packages
Install luarocks packages.
sudo luarocks install md5
sudo luarocks install uuid
Install turbo.
git clone https://github.com/kernelsauce/turbo.git
cd turbo
sudo luarocks make rockspecs/turbo-dev-1.rockspec
Web Application
Please edit the first line in web.lua.
local ROOT = '/path/to/waifu2x/dir'
Run.
th web.lua
View at: http://localhost:8812/
Command line tools
Noise Reduction
th waifu2x.lua -m noise -noise_level 1 -i input_image.png -o output_image.png
th waifu2x.lua -m noise -noise_level 2 -i input_image.png -o output_image.png
2x Upscaling
th waifu2x.lua -m scale -i input_image.png -o output_image.png
Noise Reduction + 2x Upscaling
th waifu2x.lua -m noise_scale -noise_level 1 -i input_image.png -o output_image.png
th waifu2x.lua -m noise_scale -noise_level 2 -i input_image.png -o output_image.png
See also images/gen.sh.
Training Your Own Model
Data Preparation
Genrating a file list.
find /path/to/image/dir -name "*.png" > data/image_list.txt
(You should use PNG! In my case, waifu2x is trained with 3000 high-resolution-beautiful-PNG images.)
Converting training data.
th convert_data.lua
Training a Noise Reduction(level1) model
th train.lua -method noise -noise_level 1 -test images/miku_noisy.png
th cleanup_model.lua -model models/noise1_model.t7 -oformat ascii
You can check the performance of model with models/noise1_best.png.
Training a Noise Reduction(level2) model
th train.lua -method noise -noise_level 2 -test images/miku_noisy.png
th cleanup_model.lua -model models/noise2_model.t7 -oformat ascii
You can check the performance of model with models/noise2_best.png.
Training a 2x UPscaling model
th train.lua -method scale -scale 2 -test images/miku_small.png
th cleanup_model.lua -model models/scale2.0x_model.t7 -oformat ascii
You can check the performance of model with models/scale2.0x_best.png.