Image Super-Resolution for Anime-style art using Deep Convolutional Neural Networks. And it supports photo.
Demo-Application can be found at http://waifu2x.udp.jp/ .
Click to see the slide show.
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
Region: us-east-1 (N.Virginia)
AMI ID: ami-568f823c
AMI NAME: waifu2x-server
Instance Type: g2.2xlarge
OS: Ubuntu 14.04
User: ubuntu
Created at: 2016-03-22
See ~/README.md
Please update the git repo first.
git pull
If you are a windows user, I recommend you to use waifu2x-caffe(Just download from releases tab) or waifu2x-conver-cpp.
- NVIDIA GPU
- lua-csnappy
- md5
- uuid
- turbo
(on Ubuntu 14.04)
See: NVIDIA CUDA Getting Started Guide for Linux
Download CUDA
sudo dpkg -i cuda-repo-ubuntu1404_7.5-18_amd64.deb
sudo apt-get update
sudo apt-get install cuda
sudo apt-get install libsnappy-dev
sudo apt-get install libgraphicsmagick-dev
See: Getting started with Torch
And install luarocks packages.
luarocks install graphicsmagick # upgrade
luarocks install lua-csnappy
luarocks install md5
luarocks install uuid
PREFIX=$HOME/torch/install luarocks install turbo # if you need to use web application
git clone --depth 1 https://github.com/nagadomi/waifu2x.git
Testing the waifu2x command line tool.
th waifu2x.lua
th web.lua
View at: http://localhost:8812/
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
th waifu2x.lua -m noise -noise_level 3 -i input_image.png -o output_image.png
th waifu2x.lua -m scale -i input_image.png -o output_image.png
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
th waifu2x.lua -m noise_scale -noise_level 3 -i input_image.png -o output_image.png
find /path/to/imagedir -name "*.png" -o -name "*.jpg" > image_list.txt
th waifu2x.lua -m scale -l ./image_list.txt -o /path/to/outputdir/prefix_%d.png
See also th waifu2x.lua -h.
Please add -model_dir models/photo to command line option, if you want to use photo model.
For example,
th waifu2x.lua -model_dir models/photo -m scale -i input_image.png -o output_image.png
* avconv is alias of ffmpeg on Ubuntu 14.04.
Extracting images and audio from a video. (range: 00:09:00 ~ 00:12:00)
mkdir frames
avconv -i data/raw.avi -ss 00:09:00 -t 00:03:00 -r 24 -f image2 frames/%06d.png
avconv -i data/raw.avi -ss 00:09:00 -t 00:03:00 audio.mp3
Generating a image list.
find ./frames -name "*.png" |sort > data/frame.txt
waifu2x (for example, noise reduction)
mkdir new_frames
th waifu2x.lua -m noise -noise_level 1 -resume 1 -l data/frame.txt -o new_frames/%d.png
Generating a video from waifu2xed images and audio.
avconv -f image2 -r 24 -i new_frames/%d.png -i audio.mp3 -r 24 -vcodec libx264 -crf 16 video.mp4
Notes: If you have cuDNN library, you can use cudnn kernel with -backend cudnn option. And you can convert trained cudnn model to cunn model with tools/cudnn2cunn.lua.
Genrating a file list.
find /path/to/image/dir -name "*.png" > data/image_list.txt
You should use noise free images. In my case, waifu2x is trained with 6000 high-resolution-noise-free-PNG images.
Converting training data.
th convert_data.lua
mkdir models/my_model
th train.lua -model_dir models/my_model -method noise -noise_level 1 -test images/miku_noisy.png
th cleanup_model.lua -model models/my_model/noise1_model.t7 -oformat ascii
# usage
th waifu2x.lua -model_dir models/my_model -m noise -noise_level 1 -i images/miku_noisy.png -o output.png
You can check the performance of model with models/my_model/noise1_best.png.
th train.lua -model_dir models/my_model -method noise -noise_level 2 -test images/miku_noisy.png
th cleanup_model.lua -model models/my_model/noise2_model.t7 -oformat ascii
# usage
th waifu2x.lua -model_dir models/my_model -m noise -noise_level 2 -i images/miku_noisy.png -o output.png
You can check the performance of model with models/my_model/noise2_best.png.
th train.lua -model_dir models/my_model -method scale -scale 2 -test images/miku_small.png
th cleanup_model.lua -model models/my_model/scale2.0x_model.t7 -oformat ascii
# usage
th waifu2x.lua -model_dir models/my_model -m scale -scale 2 -i images/miku_small.png -o output.png
You can check the performance of model with models/my_model/scale2.0x_best.png.