def main(**kwargs):
from types import SimpleNamespace
_ = SimpleNamespace(**kwargs)
loader = ImageLoader(_.folder)
data = loader.setup(datalen=_.datalen)
dcgan = DCGAN(loader.shape_x, loader.shape_y, loader.channels, data)
dcgan.train(epochs=_.epochs, batch_size=_.batch_size, save_interval=50)
def __init__(self):
self.img_rows = 256
self.img_cols = 256
self.channel = 3
# self.x_train = input_data.read_data_sets("mnist",\
# one_hot=True).train.images
# self.x_train = self.x_train.reshape(-1, self.img_rows,\
# self.img_cols, 1).astype(np.float32)
# self.x_train = self.x_train.reshape(-1, 28,\
# 28, 1).astype(np.float32)
folder = 'C:/Users/lhrfxg/workspace/1902_fastai/datasets/codalab/'
from image_loader import ImageLoader
loader = ImageLoader(folder)
data = loader.setup(datalen=100)
self.x_train = np.array(data)
self.DCGAN = DCGAN()
self.discriminator = self.DCGAN.discriminator_model()
self.adversarial = self.DCGAN.adversarial_model()
self.generator = self.DCGAN.generator()
