try to use autoencoder with embedding on individual anime, then PCA and the widget like in https://www.youtube.com/watch?v=wXWKWyALxYM?t=286
try to go through tips in: https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/docs/tips.md try the StyleGAN paper https://arxiv.org/abs/1812.04948 and also try the original neural style paper take a look at DiscoGAN take a look at https://www.cs.ru.nl/bachelors-theses/2018/Robin_Elbers___4225678___On_the_replication_of_CycleGAN.pdf take a look at CartoonGAN take a look at Deep Analogy (Visual Attribute Transfer through Deep Image Analogy) take a look at CNNMRF https://arxiv.org/pdf/1601.04589.pdf
- historical averaging
- but nowhere implemented. I'd have to keep X versions of all weights - too much memory consuming - not good idea
- try things from https://ssnl.github.io/better_cycles/report.pdf
- try architecture from https://colab.research.google.com/drive/1Enc-pKlP4Q3cimEBfcQv0B_6hUvjVL3o?sandboxMode=true#scrollTo=5oONZ70XXq7D
- generally, try architectures from different papers and implementations
- add the hyper-parameter tuning and orchestration
- use https://github.com/automl/ConfigSpace and SMAC
- integrate TFGAN's inception score and FID
- create original neural style transfer - should work and learn more quickly
- compare PCA, autoencoder and variational autoencoder for individual animes
- compare random sampling style image from anime with selecting components from dimension reduction as style image
video for CartoonGAN https://www.youtube.com/watch?v=r4zzhN8Aibw&ab_channel=ZivZone to lecture - faces from it mention in lecture https://github.com/luanfujun/deep-painterly-harmonization (the most funny of them) definitely describe https://www.gwern.net/Faces, and https://www.thiswaifudoesnotexist.net/ try something with trained network from that blog mention waifu2x mention makegirlsmoe
for installing lua - did not get that working:
install lua from https://github.com/rjpcomputing/luaforwindows/releases
for installing torch:
install cmake manually by conda install -c anaconda cmake
clone https://github.com/BTNC/distro-win.git
then follow win instructions, but for beware problems with outputting things to files
download zips manually, there is problem with them