This is a Chainer implementation of waifu2x [1]. Note that the training procedure of waifu2x-chainer may be slightly different from original waifu2x.
pip install chainer
pip install pillow
Install CuPy precompiled binary package which includes the latest version of cuDNN library.
See: CuPy Installation Guide
git clone https://github.com/tsurumeso/waifu2x-chainer.git
cd waifu2x-chainer
python waifu2x.py
Omitting --gpu (-g) option run on CPU.
python waifu2x.py --method noise --noise_level 1 --input path/to/image/or/directory --arch VGG7 --gpu 0
python waifu2x.py -m noise -n 0 -i path/to/image/or/directory -a 0 -g 0
python waifu2x.py -m noise -n 2 -i path/to/image/or/directory -a 0 -g 0
python waifu2x.py -m noise -n 3 -i path/to/image/or/directory -a 0 -g 0
python waifu2x.py --method scale --input path/to/image/or/directory --arch VGG7 --gpu 0
python waifu2x.py -m scale -i path/to/image/or/directory -a 0 -g 0
python waifu2x.py --method noise_scale --noise_level 1 --input path/to/image/or/directory --arch VGG7 --gpu 0
python waifu2x.py -m noise_scale -n 0 -i path/to/image/or/directory -a 0 -g 0
python waifu2x.py -m noise_scale -n 2 -i path/to/image/or/directory -a 0 -g 0
python waifu2x.py -m noise_scale -n 3 -i path/to/image/or/directory -a 0 -g 0
sudo apt install libmagickwand-dev
pip install wand
For more details, please refer template training script at appendix/linux or appendix/windows . In my case, 5000 JPEG images are used for pretraining and 1000 noise-free-PNG images for finetuning.
pip install onnx-chainer
cd appendix
python convert_models.py
Results are saved at the same directory of the original models
(e.g. models/vgg7/anime_style_scale_rgb.npz to models/vgg7/anime_style_scale_rgb.caffemodel).
Note: Since chainer.CaffeFunction
does not currently support Slice
layer, some models are not converted to caffemodel.