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Update app.py
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app.py
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@@ -44,45 +44,15 @@ from gradio_seg2image import create_demo as create_demo_seg
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from model import Model
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MAX_IMAGES = 1
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DESCRIPTION = '''# ControlNet
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If you are interested in trying out other base models, check out [this Space](https://huggingface.co/spaces/hysts/ControlNet-with-other-models) as well.
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'''
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if (SPACE_ID := os.getenv('SPACE_ID')) is not None:
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DESCRIPTION += f'''<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings.<br/>
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<a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true">
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<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
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<p/>
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'''
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model = Model()
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with gr.Blocks(css='style.css') as demo:
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with gr.Tabs():
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with gr.TabItem('Canny'):
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create_demo_canny(model.process_canny, max_images=MAX_IMAGES)
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with gr.TabItem('Hough'):
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create_demo_hough(model.process_hough, max_images=MAX_IMAGES)
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with gr.TabItem('HED'):
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create_demo_hed(model.process_hed, max_images=MAX_IMAGES)
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with gr.TabItem('Scribble'):
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create_demo_scribble(model.process_scribble, max_images=MAX_IMAGES)
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with gr.TabItem('Scribble Interactive'):
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create_demo_scribble_interactive(
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model.process_scribble_interactive, max_images=MAX_IMAGES)
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with gr.TabItem('Fake Scribble'):
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create_demo_fake_scribble(model.process_fake_scribble,
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max_images=MAX_IMAGES)
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with gr.TabItem('Pose'):
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create_demo_pose(model.process_pose, max_images=MAX_IMAGES)
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with gr.TabItem('Segmentation'):
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create_demo_seg(model.process_seg, max_images=MAX_IMAGES)
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with gr.TabItem('Depth'):
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create_demo_depth(model.process_depth, max_images=MAX_IMAGES)
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with gr.TabItem('Normal map'):
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create_demo_normal(model.process_normal, max_images=MAX_IMAGES)
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demo.queue(api_open=False).launch()
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from model import Model
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MAX_IMAGES = 1
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DESCRIPTION = '''# Bake-a-Cake, powered by ControlNet"
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Put a picture of anything, and ControlNet will turn it into a hyperrealistic cake:
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'''
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model = Model()
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with gr.Blocks(css='style.css') as demo:
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create_demo_canny(model.process_canny, max_images=MAX_IMAGES)
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demo.queue(api_open=False).launch()
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