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[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime

Python 100.00%

animeganv2's Introduction

AnimeGANv2

[Open Source]. The improved version of AnimeGAN.
Landscape photos/videos to anime

Focus:

Anime style Film Picture Number Quality Download Style Dataset
Miyazaki Hayao The Wind Rises 1752 1080p Link
Makoto Shinkai Your Name & Weathering with you 1445 BD
Kon Satoshi Paprika 1284 BDRip

     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 Hayao/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











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