195 lines
4.8 KiB
Markdown
195 lines
4.8 KiB
Markdown
# v1.0 branch
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This branch is under construction. This would break backwards compatibility sometimes.
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# waifu2x
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Image Super-Resolution for anime-style-art using Deep Convolutional Neural Networks.
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Demo-Application can be found at http://waifu2x.udp.jp/ .
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## Summary
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Click to see the slide show.
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## References
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waifu2x is inspired by SRCNN [1]. 2D character picture (HatsuneMiku) is licensed under CC BY-NC by piapro [2].
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- [1] Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang, "Image Super-Resolution Using Deep Convolutional Networks", http://arxiv.org/abs/1501.00092
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- [2] "For Creators", http://piapro.net/en_for_creators.html
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## Public AMI
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```
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AMI ID: ami-0be01e4f
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AMI NAME: waifu2x-server
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Instance Type: g2.2xlarge
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Region: US West (N.California)
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OS: Ubuntu 14.04
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User: ubuntu
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Created at: 2015-08-12
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```
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## Third Party Software
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[Third-Party](https://github.com/nagadomi/waifu2x/wiki/Third-Party)
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## Dependencies
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### Hardware
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- NVIDIA GPU
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### Platform
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- [Torch7](http://torch.ch/)
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- [NVIDIA CUDA](https://developer.nvidia.com/cuda-toolkit)
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### lualocks packages (excludes torch7's default packages)
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- md5
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- uuid
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- [turbo](https://github.com/kernelsauce/turbo)
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## Installation
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### Setting Up the Command Line Tool Environment
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(on Ubuntu 14.04)
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#### Install CUDA
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See: [NVIDIA CUDA Getting Started Guide for Linux](http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-linux/#ubuntu-installation)
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Download [CUDA](http://developer.nvidia.com/cuda-downloads)
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```
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sudo dpkg -i cuda-repo-ubuntu1404_7.0-28_amd64.deb
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sudo apt-get update
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sudo apt-get install cuda
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```
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#### Install Torch7
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See: [Getting started with Torch](http://torch.ch/docs/getting-started.html)
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#### Validation
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Test the waifu2x command line tool.
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```
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th waifu2x.lua
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```
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### Setting Up the Web Application Environment (if you needed)
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#### Install packages
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```
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luarocks install md5
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luarocks install uuid
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PREFIX=$HOME/torch/install luarocks install turbo
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```
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## Web Application
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Run.
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```
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th web.lua
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```
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View at: http://localhost:8812/
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## Command line tools
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### Noise Reduction
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```
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th waifu2x.lua -m noise -noise_level 1 -i input_image.png -o output_image.png
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```
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```
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th waifu2x.lua -m noise -noise_level 2 -i input_image.png -o output_image.png
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```
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### 2x Upscaling
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```
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th waifu2x.lua -m scale -i input_image.png -o output_image.png
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```
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### Noise Reduction + 2x Upscaling
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```
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th waifu2x.lua -m noise_scale -noise_level 1 -i input_image.png -o output_image.png
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```
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```
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th waifu2x.lua -m noise_scale -noise_level 2 -i input_image.png -o output_image.png
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```
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See also `images/gen.sh`.
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### Video Encoding
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\* `avconv` is `ffmpeg` on Ubuntu 14.04.
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Extracting images and audio from a video. (range: 00:09:00 ~ 00:12:00)
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```
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mkdir frames
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avconv -i data/raw.avi -ss 00:09:00 -t 00:03:00 -r 24 -f image2 frames/%06d.png
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avconv -i data/raw.avi -ss 00:09:00 -t 00:03:00 audio.mp3
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```
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Generating a image list.
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```
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find ./frames -name "*.png" |sort > data/frame.txt
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```
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waifu2x (for example, noise reduction)
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```
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mkdir new_frames
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th waifu2x.lua -m noise -noise_level 1 -resume 1 -l data/frame.txt -o new_frames/%d.png
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```
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Generating a video from waifu2xed images and audio.
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```
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avconv -f image2 -r 24 -i new_frames/%d.png -i audio.mp3 -r 24 -vcodec libx264 -crf 16 video.mp4
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```
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## Training Your Own Model
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### Data Preparation
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Genrating a file list.
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```
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find /path/to/image/dir -name "*.png" > data/image_list.txt
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```
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(You should use PNG! In my case, waifu2x is trained with 3000 high-resolution-noise-free-PNG images.)
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Converting training data.
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```
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th convert_data.lua
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```
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### Training a Noise Reduction(level1) model
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```
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mkdir models/my_model
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th train.lua -model_dir models/my_model -method noise -noise_level 1 -test images/miku_noisy.png
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th cleanup_model.lua -model models/my_model/noise1_model.t7 -oformat ascii
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# usage
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th waifu2x.lua -model_dir models/my_model -m noise -noise_level 1 -i images/miku_noisy.png -o output.png
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```
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You can check the performance of model with `models/my_model/noise1_best.png`.
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### Training a Noise Reduction(level2) model
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```
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th train.lua -model_dir models/my_model -method noise -noise_level 2 -test images/miku_noisy.png
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th cleanup_model.lua -model models/my_model/noise2_model.t7 -oformat ascii
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# usage
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th waifu2x.lua -model_dir models/my_model -m noise -noise_level 2 -i images/miku_noisy.png -o output.png
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```
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You can check the performance of model with `models/my_model/noise2_best.png`.
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### Training a 2x UpScaling model
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```
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th train.lua -model_dir models/my_model -method scale -scale 2 -test images/miku_small.png
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th cleanup_model.lua -model models/my_model/scale2.0x_model.t7 -oformat ascii
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# usage
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th waifu2x.lua -model_dir models/my_model -m scale -scale 2 -i images/miku_small.png -o output.png
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```
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You can check the performance of model with `models/my_model/scale2.0x_best.png`.
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