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Update app.py
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app.py
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@@ -326,37 +326,53 @@ If you have any questions, please feel free to reach me out at <b>iceclearwjy@gm
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<center><img src='https://visitor-badge.laobi.icu/badge?page_id=IceClear/StableSR' alt='visitors'></center>
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"""
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gr.
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value=
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label="
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label=
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)
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demo.queue(concurrency_count=1)
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<center><img src='https://visitor-badge.laobi.icu/badge?page_id=IceClear/StableSR' alt='visitors'></center>
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"""
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with gr.Blocks(title=title) as demo:
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gr.Markdown(description)
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gr.Markdown(article)
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with gr.Row():
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with gr.Column():
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image = gr.Image(type="filepath", label="Input")
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upscale = gr.Number(value=1, label="Rescaling_Factor (Large images require huge time)")
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dec_w = gr.Slider(0, 1, value=0.5, step=0.01, label='CFW_Fidelity (0 for better quality, 1 for better identity)')
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seed = gr.Number(value=42, label="Seeds")
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model_type = gr.Dropdown(
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choices=["512", "768v"],
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value="512",
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label="Model"
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)
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ddpm_steps = gr.Slider(10, 1000, value=200, step=1, label='Sampling timesteps for DDPM')
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colorfix_type = gr.Dropdown(
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choices=["none", "adain", "wavelet"],
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value="adain",
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label="Color_Correction"
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)
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run_btn = gr.Button("Run Inference")
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with gr.Column():
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output_image = gr.Image(type="numpy", label="Output")
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output_file = gr.File(label="Download the output")
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# Inference trigger
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run_btn.click(
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fn=inference,
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inputs=[image, upscale, dec_w, seed, model_type, ddpm_steps, colorfix_type],
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outputs=[output_image, output_file]
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)
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# Example section
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gr.Examples(
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examples=[
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['./01.png', 4, 0.5, 42, "512", 200, "adain"],
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['./02.png', 4, 0.5, 42, "512", 200, "adain"],
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['./03.png', 4, 0.5, 42, "512", 200, "adain"],
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['./04.png', 4, 0.5, 42, "512", 200, "adain"],
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['./05.png', 4, 0.5, 42, "512", 200, "adain"]
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],
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fn=inference,
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inputs=[image, upscale, dec_w, seed, model_type, ddpm_steps, colorfix_type],
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outputs=[output_image, output_file],
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cache_examples=True
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)
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demo.queue(concurrency_count=1)
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