/AnimeGANv2

[Open Source]. The improved version of AnimeGAN.

Primary LanguagePython

AnimeGANv2

[Open Source]. The improved version of AnimeGAN.

Focus:

Anime style Film Picture Number Quality Download link
Miyazaki Hayao The Wind Rises 1752 1080p TBD
Makoto Shinkai Your Name 1642 BD TBD
Kon Satoshi Paprika 1255 BDRip TBD

     Different styles of training have different loss weights!

News:

The improvement directions of AnimeGANv2 mainly include the following 4 points:  
  • 1. Solve the problem of high-frequency artifacts in the generated image.

  • 2. It is easy to train and directly achieve the effects in the paper.

  • 3. Further reduce the number of parameters of the generator network. (generator size: 8.17 Mb)

  • 4. Use new high-quality style data, which come from BD movies as much as possible.

          AnimeGAN can be accessed from here.


Requirements

  • python 3.6
  • tensorflow-gpu
    • tensorflow-gpu 1.8.0 (ubuntu, GPU 1080Ti or Titan xp, cuda 9.0, cudnn 7.1.3)
    • tensorflow-gpu 1.15.0 (ubuntu, GPU 2080Ti, cuda 10.0.130, cudnn 7.6.0)
  • opencv
  • tqdm
  • numpy
  • glob
  • argparse

Usage

1. Inference

python test.py --checkpoint_dir checkpoint/generator_Hayao_weight --test_dir dataset/test/HR_photo --style_name Paprika/HR_photo

2. Convert video to anime

python video2anime.py --video video/input/お花見.mp4 --checkpoint_dir checkpoint/generator_Paprika_weight


Results

😍 Photo to Paprika Style













😍 Photo to Hayao Style













😍 Photo to Shinkai Style
TBD