8-working_example.py

# example of using saved cyclegan models for image translation
from numpy import load
from numpy import expand_dims
from keras.models import load_model
from matplotlib import pyplot

# load an image to the preferred size
def load_image(filename, size=(256,256)):
	# load and resize the image
	pixels = load_img(filename, target_size=size)
	# convert to numpy array
	pixels = img_to_array(pixels)
	# transform in a sample
	pixels = expand_dims(pixels, 0)
	# scale from [0,255] to [-1,1]
	pixels = (pixels - 127.5) / 127.5
	return pixels

# load the image
image_src = load_image('../dicaprio/licensed-image.jpeg')
# load the model
cust = {'InstanceNormalization': InstanceNormalization}
model_AtoB = load_model('../g_model_AtoB_000700.h5', cust)
# translate image
image_tar = model_AtoB.predict(image_src)
# scale from [-1,1] to [0,1]
image_tar = (image_tar + 1) / 2.0
# plot the translated image
pyplot.imshow(image_tar[0])
pyplot.show()