''' client to produce generator images from latent space '''
import numpy as np
from keras.models import load_model

MODEL = './generator_model_2800.h5'

z_noise = np.random.randn(100*25)
z_noise = z_noise.reshape(25, 100)

model = load_model(MODEL)
X = model.predict(z_noise)
X = (X+1) / 2.0

plt.imshow(X[4])

# show multiple designs
shoe_index = 0
fig, ax = plt.subplots(4, 4, figsize=(11, 11))
fig.subplots_adjust(hspace=0, wspace=0)
for i in range(4):
    for j in range(4):
        ax[i, j].imshow(X[shoe_index])
        ax[i, j].axis('off')
        shoe_index += 1
plt.tight_layout()