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Create app.py
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app.py
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import gradio as gr
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from torchvision.transforms import Compose, Resize, ToTensor, Normalize
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from PIL import Image
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from torchvision.utils import save_image
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from huggan.pytorch.pix2pix.modeling_pix2pix import GeneratorUNet
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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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model = GeneratorUNet.from_pretrained('Guldeniz/pix2pix_maps')
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def predict_fn(img):
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inp = transform(img).unsqueeze(0)
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out = model(inp)
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save_image(out, 'out.png', normalize=True)
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return 'out.png'
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gr.Interface(predict_fn, inputs=gr.inputs.Image(type='pil'), outputs='image', examples=[['img.png'], ['real.jpeg'], ['real2.jpg']]).launch()
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