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Anime_GAN

This repository records my GAN models with Anime.

Dependencies

DCGAN

you need to download the dataset (onedrive, or baiduyun) named faces.zip, then execute the first step——Cloning the repository, and extract and move it in Anime_GAN/DCGAN/.

1. Cloning the repository

$ git clone https://github.com/FangYang970206/Anime_GAN.git
$ cd Anime_GAN/DCGAN/

2. run the code

$ python main.py 

3. 500 epochs result

WGAN

The WGAN implemented by pytorch has bugs. If anyone can find them, i will appreciate you so much! I implement a keras version Anime_WGAN. Like DCGAN, you should download the dataset (onedrive, or baiduyun) named faces.zip(the same as DCGAN), then execute the first step——Cloning the repository, and extract and move it in Anime_GAN/WGAN_keras/faces/.

1. Cloning the repository

$ git clone https://github.com/FangYang970206/Anime_GAN.git
$ cd Anime_GAN/WGAN_keras/

2. run the code

$ python wgan_keras.py 

3. 100000 steps result

ConditionalGAN

you need to download the dataset (onedrive or baiduyun) named images.zip, then execute the first step——Cloning the repository, and extract and move it in Anime_GAN/ConditionalGAN/.The tag.csv file is dataset label, include hair color and eye color.The test.txt is test label file used to generate test images.

1. Cloning the repository

$ git clone https://github.com/FangYang970206/Anime_GAN.git
$ cd Anime_GAN/ConditionalGAN/

2. run the code

Two mode: train or infer. In infer mode, make sure you have trained the ConditionalGAN.

$ python main.py --mode "train"
$ python main.py --mode "infer"  

3. 55000 steps result

4. GUI

Before run GUI.py, you should train the conditionalGAN to get the generate.t7.

$ python GUI.py

Reference