This repository records my GAN models with Anime.
- Python 3.6+
- PyTorch 0.4.0
- numpy 1.14.1, matplotlib 2.2.2, scipy 1.1.0
- imageio 2.3.0
- tqdm 4.24.0
- keras 2.1.2(for WGAN_keras)
- tensorflow 1.2.1(for WGAN_keras)
- cv2 --
pip install opencv-python(for ConditionalGAN)
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/.
$ git clone https://github.com/FangYang970206/Anime_GAN.git
$ cd Anime_GAN/DCGAN/$ python main.py 
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/.
$ git clone https://github.com/FangYang970206/Anime_GAN.git
$ cd Anime_GAN/WGAN_keras/$ python wgan_keras.py 
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.
$ git clone https://github.com/FangYang970206/Anime_GAN.git
$ cd Anime_GAN/ConditionalGAN/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" 
Before run GUI.py, you should train the conditionalGAN to get the generate.t7.
$ python GUI.py