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app.py
CHANGED
@@ -54,6 +54,9 @@ article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1609.051
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# ['examples/2000-08-18-18-23-46_L5_rgb.jpg'],['examples/2000-09-19-18-24-18_L5_rgb.jpg'],['examples/2000-10-21-18-24-43_L5_rgb.jpg']]
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examples= [[l] for l in glob('examples/tiles/*.jpg')]
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iface = gr.Interface(
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fn=infer,
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@@ -61,8 +64,6 @@ iface = gr.Interface(
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description = "This space is a demo of the keras tutorial 'Image Super-Resolution using an Efficient Sub-Pixel CNN' based on the paper 'Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network' 👀",
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article = article,
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inputs=gr.inputs.Image(label="Input Image"),
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outputs=[
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gr.outputs.Image(label="Super-resolution x3 image")
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],
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examples=examples,
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).launch()
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# ['examples/2000-08-18-18-23-46_L5_rgb.jpg'],['examples/2000-09-19-18-24-18_L5_rgb.jpg'],['examples/2000-10-21-18-24-43_L5_rgb.jpg']]
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examples= [[l] for l in glob('examples/tiles/*.jpg')]
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out1 = gr.outputs.Image(label="Cropped input image")
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out2 = gr.outputs.Image(label="Super-resolution x3 image")
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out3 = gr.outputs.Dataframe(label='Summary', headers=["Input (px)", "Output (px)"], type='pandas')
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iface = gr.Interface(
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fn=infer,
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description = "This space is a demo of the keras tutorial 'Image Super-Resolution using an Efficient Sub-Pixel CNN' based on the paper 'Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network' 👀",
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article = article,
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inputs=gr.inputs.Image(label="Input Image"),
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outputs=[out1,out2,out3],
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examples=examples,
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).launch()
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