Spaces:
Running
on
Zero
Running
on
Zero
Update UI
Browse files
app.py
CHANGED
@@ -73,13 +73,10 @@ def infer(
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### Description
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header =
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<
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Official Gradio demo for <a href='https://dariant.github.io/publications/ID-Booth' target='_blank'>ID-Booth: Identity-consistent Face Generation with Diffusion Models</a>
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"""
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footer = r"""
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---
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📝 **Citation**
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<br>
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If you find ID-Booth helpful, please consider citing our paper:
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@@ -93,20 +90,18 @@ If you find ID-Booth helpful, please consider citing our paper:
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```
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"""
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css =
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max-width: 960px;
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}
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"""
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with gr.Blocks(css=css) as demo:
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# description
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gr.Markdown(header)
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with gr.Column(elem_id="col-container"):
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with gr.Row():
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with gr.Row():
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for id in id_list:
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@@ -139,7 +134,7 @@ with gr.Blocks(css=css) as demo:
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value=poses_list[0],
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)
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run_button = gr.Button("Generate", scale=0, variant="primary")
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#result = gr.Image(label="Result", show_label=False)
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result = gr.Gallery(label="Generated Images", show_label=False)
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@@ -152,7 +147,7 @@ with gr.Blocks(css=css) as demo:
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value="cartoon, cgi, render, illustration, painting, drawing, black and white, bad body proportions, landscape",
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)
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num_inference_steps = gr.Slider(
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label="Number of
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minimum=1,
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maximum=100,
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step=1,
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### Description
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header = " # ID-Booth: Identity-consistent Face Generation with Diffusion Models"
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description = "This is an official Gradio demo for the paper <a href='https://dariant.github.io/publications/ID-Booth' target='_blank'>ID-Booth: Identity-consistent Face Generation with Diffusion Models</a>"
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footer = r"""
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📝 **Citation**
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<br>
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If you find ID-Booth helpful, please consider citing our paper:
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```
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"""
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css = '''
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.gradio-container {width: 60% !important}
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'''
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with gr.Blocks(css=css) as demo:
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# description
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gr.Markdown(header)
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gr.Markdown(description)
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with gr.Column(elem_id="col-container"):
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# with gr.Row():
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# gr.Markdown("### Choose an identity, background, and pose:")
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with gr.Row():
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for id in id_list:
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value=poses_list[0],
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)
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run_button = gr.Button("Generate in-the-wild images", scale=0, variant="primary")
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#result = gr.Image(label="Result", show_label=False)
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result = gr.Gallery(label="Generated Images", show_label=False)
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value="cartoon, cgi, render, illustration, painting, drawing, black and white, bad body proportions, landscape",
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)
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num_inference_steps = gr.Slider(
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label="Number of sampling steps",
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minimum=1,
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maximum=100,
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step=1,
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