CycleGAN

Cycle GAN implementation in tensorflow 2.0

Requirnments

1. Tensorflow 2.0
2. Matplotlib

Dataset

Dataset for training of CycleGAN can be downloaded with following code. This dataset contain images of Horses and Zebras. Our goal is to generate zebras from horses from image to image translation with unpaired training.

_URL = 'https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/horse2zebra.zip'

path_to_zip = tf.keras.utils.get_file('horse2zebra.zip',
                                      origin=_URL,
                                      extract=True)

PATH = os.path.join(os.path.dirname(path_to_zip), 'dataset/')

Sample Image

Dataset Structure

  ├── dataset                   # Dataset folder
    ├── trainA                  # folder contains Horses
    │   ├── *.jpg         
    |   |........
    |   └── *.jpg        
    ├── trainB                  # folder contains Zebras
    │   ├── *.jpg          
    |   |........
    |   └── *.jpg
    ├── testA                   # test folder contains Horses
    │   ├── *.jpg          
    |   |........
    |   └── *.jpg
    └── testB                   # test folder contains Zebras
        ├── *.jpg          
        |........
        └── *.jpg
     

Train the Model

Windows

python cyclegan.py

Linux and MAC

CUDA_VISIBLE_DEVICES='GPU_NO' python cyclegan.py

Test

In code change mode in **kwargs

kwargs = {'epochs': 500, 
	  'path': 'dataset',
	  'mode':'test', 
	  'output_path':'Exp_1',
          'batch_size':1,
}

Run same command for testing

python cyclegan.py