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	Weathering with you	5908	BD	TBD
Kon Satoshi	Paprika	1255	BD	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.

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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

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Results

😍 Photo to Paprika Style

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😍 Photo to Hayao Style

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😍 Photo to Shinkai Style
TBD