Implementation of "なんちゃって" StackGAN model using Keras.
"なんちゃって" is a phrase that means that it is not genuine.
- Python 3.0 or newer
- Keras 2.0 or newer (Tensorflow backend)
- Pillow
- numpy
- tqdm
- h5py
- Clone this repository:
git clone https://github.com/kcct-fujimotolab/StackGAN.git
cd StackGAN/- Make a directory for data sets:
mkdir images- Collect images (more than 2000-3000 works better):
ls images/
data0000.jpg data0001.jpg ... data9999.jpg- Start training by specifying image size, number of epochs, data set directory, etc.:
python train.py --input images/ --size 128 128 --epoch 5000--help -h: show information
--input -i: data sets path (default -i images/)
--size -z: image size during training, 2 values required, must be multiples of 8 (default -z 128 128)
--epoch -e: number of epochs (default -e 3000)
--batch -b: batch size (default -b 64)
--dim -d: input dimension of generator (default -d 100)
--output -o: output directory path (default -o gen/)
--save -s: taking snapshot interval (default -s 100)
We extracted 4096 images from the face data provided by Labeled Faces in the Wild, and trained with Keras model.
Fujimoto Lab at Kobe City College of Technology
Undergraduate Student of Electronics Department
@yoidea