JingyeChen commited on
Commit
a6470eb
1 Parent(s): 7585c5c
Files changed (1) hide show
  1. app.py +2 -2
app.py CHANGED
@@ -418,7 +418,7 @@ with gr.Blocks() as demo:
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  with gr.Column(scale=1):
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  prompt = gr.Textbox(label="Prompt. You can let language model automatically identify keywords, or provide them below", placeholder="A beautiful city skyline stamp of Shanghai")
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  keywords = gr.Textbox(label="(Optional) Keywords. Should be seperated by / (e.g., keyword1/keyword2/...)", placeholder="keyword1/keyword2")
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- positive_prompt = gr.Textbox(label="(Optional) Positive prompt", value=", showing different kinds of quails, digital art, very detailed, fantasy, high definition, cinematic light, dnd, trending on artstation")
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  with gr.Accordion("(Optional) Template - Click to paint", open=False):
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  with gr.Row():
@@ -436,11 +436,11 @@ with gr.Blocks() as demo:
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  skip_button.click(skip_fun, [i,t])
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  radio = gr.Radio(["TextDiffuser-2", "TextDiffuser-2-LCM"], label="Choice of models", value="TextDiffuser-2")
 
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  slider_step = gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Sampling step", info="The sampling step for TextDiffuser-2. You may decease the step to 4 when using LCM.")
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  slider_guidance = gr.Slider(minimum=1, maximum=13, value=7.5, step=0.5, label="Scale of classifier-free guidance", info="The scale of cfg and is set to 7.5 in default. When using LCM, cfg is set to 1.")
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  slider_batch = gr.Slider(minimum=1, maximum=6, value=4, step=1, label="Batch size", info="The number of images to be sampled.")
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  slider_temperature = gr.Slider(minimum=0.1, maximum=2, value=0.7, step=0.1, label="Temperature", info="Control the diversity of layout planner. Higher value indicates more diversity.")
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- slider_natural = gr.Checkbox(label="Natural image generation", value=False, info="The text position and content info will not be incorporated.")
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  # slider_seed = gr.Slider(minimum=1, maximum=10000, label="Seed", randomize=True)
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  button = gr.Button("Generate")
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  with gr.Column(scale=1):
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  prompt = gr.Textbox(label="Prompt. You can let language model automatically identify keywords, or provide them below", placeholder="A beautiful city skyline stamp of Shanghai")
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  keywords = gr.Textbox(label="(Optional) Keywords. Should be seperated by / (e.g., keyword1/keyword2/...)", placeholder="keyword1/keyword2")
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+ positive_prompt = gr.Textbox(label="(Optional) Positive prompt", value=", digital art, very detailed, fantasy, high definition, cinematic light, dnd, trending on artstation")
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  with gr.Accordion("(Optional) Template - Click to paint", open=False):
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  with gr.Row():
 
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  skip_button.click(skip_fun, [i,t])
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  radio = gr.Radio(["TextDiffuser-2", "TextDiffuser-2-LCM"], label="Choice of models", value="TextDiffuser-2")
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+ slider_natural = gr.Checkbox(label="Natural image generation", value=False, info="The text position and content info will not be incorporated.")
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  slider_step = gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Sampling step", info="The sampling step for TextDiffuser-2. You may decease the step to 4 when using LCM.")
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  slider_guidance = gr.Slider(minimum=1, maximum=13, value=7.5, step=0.5, label="Scale of classifier-free guidance", info="The scale of cfg and is set to 7.5 in default. When using LCM, cfg is set to 1.")
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  slider_batch = gr.Slider(minimum=1, maximum=6, value=4, step=1, label="Batch size", info="The number of images to be sampled.")
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  slider_temperature = gr.Slider(minimum=0.1, maximum=2, value=0.7, step=0.1, label="Temperature", info="Control the diversity of layout planner. Higher value indicates more diversity.")
 
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  # slider_seed = gr.Slider(minimum=1, maximum=10000, label="Seed", randomize=True)
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  button = gr.Button("Generate")
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