waifu2x

Image Super-Resolution for Anime-style art using Deep Convolutional Neural Networks. And it supports photo. Note: waifu2x requires little-cms2 linked graphicsmagick. if you use macOS/homebrew, See 174. Command line tools Notes: If you have cuDNN library, than you can use cuDNN with -force cudnn 1 option. cuDNN is too much faster than default kernel. If you got GPU out of memory error, you can avoid it with -crop size option (e.g. -crop size 128 ). Please add -model dir models/photo to command line option, if you want to use photo model. For example, Train Your Own Model Note1: 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/rebuild.lua . You should use noise free images. In my case, waifu2x is trained with 6000 high-resolution-noise-free-PNG images. You can check the performance of model with models/my model/noise1 best.png . You can check the performance of model with models/my model/noise2 best.png . You can check the performance of model with models/my model/scale2.0x best.png . You can check the performance of model with models/my model/noise1 scale2.0x best.png . Note that running waifu2x in without JIT caching is very slow, which is what would happen if you use docker. For a workaround, you can mount a host volume to the CUDA CACHE PATH , for instance,