import gradio as gr

from huggan.pytorch.pix2pix.modeling_pix2pix import GeneratorUNet
from PIL import Image
from torchvision.utils import save_image
from torchvision.transforms import Compose, Resize, ToTensor, Normalize, ToPILImage
from diffusers.utils import load_image, make_image_grid

transform = Compose(
    [
        Resize((256, 256), Image.BICUBIC),
        ToTensor(),
        Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
    ]
)

transform2 = Compose(
    [
        #Resize((256, 256), Image.BICUBIC),
        ToPILImage(),
        #Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
    ]
)

generator = GeneratorUNet.from_pretrained("debisoft/gimp-pred-gan")

def greet(input):
	coord_zxy = input
	image = load_image("https://c.basemaps.cartocdn.com/rastertiles/voyager_labels_under" + coord_zxy + ".png")
	pixel_values = transform(image).unsqueeze(0)
	output = generator(pixel_values)

	return transform2(output[0])

iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="coord_zxy", value="/18/73237/95677")], outputs=[gr.Image(type="pil", width=256, label="Output Image")])
iface.queue(api_open=True);
iface.launch()