1st commit.

app.py

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+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()

requirements.txt

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+ipython
+torch
+torchvision
+diffusers
+git+https://github.com/huggingface/community-events.git