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Browse files- app.py +37 -0
- requirements.txt +5 -0
app.py
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import gradio as gr
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from huggan.pytorch.pix2pix.modeling_pix2pix import GeneratorUNet
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from PIL import Image
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from torchvision.utils import save_image
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from torchvision.transforms import Compose, Resize, ToTensor, Normalize, ToPILImage
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from diffusers.utils import load_image, make_image_grid
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transform = Compose(
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[
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Resize((256, 256), Image.BICUBIC),
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ToTensor(),
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Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
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]
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)
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transform2 = Compose(
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[
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#Resize((256, 256), Image.BICUBIC),
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ToPILImage(),
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#Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
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]
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)
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generator = GeneratorUNet.from_pretrained("debisoft/stamen-wc-can-gan")
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def greet(input):
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coord_zxy = input
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image = load_image("https://c.basemaps.cartocdn.com/rastertiles/voyager_labels_under" + coord_zxy + ".png")
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pixel_values = transform(image).unsqueeze(0)
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output = generator(pixel_values)
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return transform2(output[0])
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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")])
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iface.queue(api_open=True);
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iface.launch()
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requirements.txt
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ipython
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torch
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torchvision
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diffusers
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git+https://github.com/huggingface/community-events.git
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