A Tensorflow implementation of AnimeGAN for fast photo animation !!!
This is the Open source of the paper <AnimeGAN: a novel lightweight GAN for photo animation>, which uses the GAN framwork to transform real-world photos into anime images.
Some suggestions: since the real photos in the training set are all landscape photos, if you want to stylize the photos with people as the main body, you may as well add at least 3000 photos of people in the training set and retrain to obtain a new model.
- python 3.6.8
- tensorflow-gpu 1.8
1. Download vgg19 or Pretrained model
2. Download dataset
3. Do edge_smooth
python edge_smooth.py --dataset Haoyao --img_size 256
python main.py --phase train --dataset Haoyao --epoch 101 --init_epoch 1
python main.py --phase test --dataset Hayao
python test.py --checkpoint_dir checkpoint/AnimeGAN_Hayao_lsgan_300_300_1_3_10 --test_dir dataset/test/real --style_name H
This code is based on the CartoonGAN-Tensorflow and Anime-Sketch-Coloring-with-Swish-Gated-Residual-UNet. Thanks to the contributors of this project.