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Update app.py
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app.py
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@@ -215,14 +215,15 @@ iface = gr.Interface(fn=run, inputs=[
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# gr.Image(image_mode="L", source="canvas", type="pil", shape=(256,256), invert_colors=False, tool="editor"),
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gr.inputs.Radio(label="Input Mode - The type of your input", choices=["mask", "sketch"],default="sketch"),
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gr.inputs.Slider(label="sample_c - The strength of classifier-free guidance",default=1.4, minimum=1.0, maximum=2.0),
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gr.inputs.Slider(label="Number of samples - How many samples you wish to generate", default=
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gr.inputs.Slider(label="Number of Steps - How many steps you want to use", default=100, step=10, minimum=50, maximum=1000),
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],
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outputs=[image],
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css=css,
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title="Generate images from sketches with PITI",
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description="<div>By uploading a sketch map or a semantic map and pressing submit, you can generate images based on your input. As the computing device is CPU, the running may be slow.</div>",
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examples=[["1.png", "sketch", 1.3,
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iface.launch(enable_queue=True)
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# gr.Image(image_mode="L", source="canvas", type="pil", shape=(256,256), invert_colors=False, tool="editor"),
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gr.inputs.Radio(label="Input Mode - The type of your input", choices=["mask", "sketch"],default="sketch"),
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gr.inputs.Slider(label="sample_c - The strength of classifier-free guidance",default=1.4, minimum=1.0, maximum=2.0),
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gr.inputs.Slider(label="Number of samples - How many samples you wish to generate", default=2, step=1, minimum=1, maximum=8),
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gr.inputs.Slider(label="Number of Steps - How many steps you want to use", default=100, step=10, minimum=50, maximum=1000),
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],
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outputs=[image],
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css=css,
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title="Generate images from sketches with PITI",
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description="<div>By uploading a sketch map or a semantic map and pressing submit, you can generate images based on your input. As the computing device is CPU, the running may be slow.</div>",
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examples=[["1.png", "sketch", 1.3, 2, 100], ["2.png", "sketch", 1.3, 2, 100],["3.png", "sketch", 1.3, 2, 100],["4.png", "mask", 1.3, 2, 100],["5.png", "mask", 1.3, 2, 100],["6.png", "mask", 1.3, 2, 100]],
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cache_examples=False)
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iface.launch(enable_queue=True)
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