Image Super-Resolution for Anime-Style Art
fork from : https://github.com/nagadomi/waifu2x.git
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10 gadi atpakaļ | |
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appendix | 10 gadi atpakaļ | |
assets | 10 gadi atpakaļ | |
cache | 10 gadi atpakaļ | |
data | 10 gadi atpakaļ | |
images | 10 gadi atpakaļ | |
lib | 10 gadi atpakaļ | |
models | 10 gadi atpakaļ | |
.gitignore | 10 gadi atpakaļ | |
LICENSE | 10 gadi atpakaļ | |
NOTICE | 10 gadi atpakaļ | |
README.md | 10 gadi atpakaļ | |
cleanup_model.lua | 10 gadi atpakaļ | |
convert_data.lua | 10 gadi atpakaļ | |
train.lua | 10 gadi atpakaļ | |
train.sh | 10 gadi atpakaļ | |
waifu2x.lua | 10 gadi atpakaļ | |
web.lua | 10 gadi atpakaļ |
Image Super-Resolution for anime/fan-art using Deep Convolutional Neural Networks.
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].
NOTE: Turbo 1.1.3 has bug in file uploading. Please install from the master branch on github.
Please edit the first line in web.lua
.
local ROOT = '/path/to/waifu2x/dir'
Run.
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 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
See also images/gen.sh
.
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 by 3000 PNG images.)
Converting training data.
th convert_data.lua
th train.lua -method noise -noise_level 1 -test images/miku_noise.png
th cleanup_model.lua -model models/noise1_model.t7 -oformat ascii
You can check the performance of model with models/noise1_best.png
.
th train.lua -method noise -noise_level 2 -test images/miku_noise.png
th cleanup_model.lua -model models/noise2_model.t7 -oformat ascii
You can check the performance of model with models/noise2_best.png
.
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
.