TheAwakenOne commited on
Commit
609484b
·
1 Parent(s): 0baa9f7
Files changed (1) hide show
  1. app.py +5 -5
app.py CHANGED
@@ -213,9 +213,9 @@ with gr.Blocks() as demo:
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  with gr.Row():
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  with gr.Column():
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- steps = gr.Slider(minimum=1, maximum=100, value=25, step=1, label="Steps")
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  cfg_scale = gr.Slider(minimum=1, maximum=20, value=3.5, step=0.1, label="CFG Scale")
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- lora_scale = gr.Slider(minimum=0, maximum=1, value=1, step=0.05, label="LoRA Scale")
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  with gr.Column():
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  width = gr.Slider(minimum=256, maximum=1024, value=512, step=64, label="Width")
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  height = gr.Slider(minimum=256, maximum=1024, value=512, step=64, label="Height")
@@ -230,8 +230,8 @@ with gr.Blocks() as demo:
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  # Event handlers
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  gallery.select(update_selection, [width, height], [prompt, selected_lora, gr.State(), width, height])
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- randomize_seed.change(lambda x: gr.update(visible=not x), randomize_seed, seed_input)
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- generate_event = generate.click(run_lora, inputs=[prompt, image_input, image_strength, cfg_scale, steps, gr.State(), randomize_seed, seed_input, width, height, lora_scale], outputs=[result, seed_output, progress_bar])
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- cancel.click(lambda: None, None, None, cancels=[generate_event])
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  demo.queue().launch()
 
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  with gr.Row():
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  with gr.Column():
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+ steps = gr.Slider(minimum=1, maximum=100, value=28, step=1, label="Steps")
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  cfg_scale = gr.Slider(minimum=1, maximum=20, value=3.5, step=0.1, label="CFG Scale")
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+ lora_scale = gr.Slider(minimum=0, maximum=1, value=0.8, step=0.05, label="LoRA Scale")
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  with gr.Column():
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  width = gr.Slider(minimum=256, maximum=1024, value=512, step=64, label="Width")
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  height = gr.Slider(minimum=256, maximum=1024, value=512, step=64, label="Height")
 
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  # Event handlers
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  gallery.select(update_selection, [width, height], [prompt, selected_lora, gr.State(), width, height])
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+ randomize_seed.change(lambda x: gr.update(visible=not x), randomize_seed, seed_input)
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+ generate.click(run_lora, inputs=[prompt, image_input, image_strength, cfg_scale, steps, gr.State(), randomize_seed, seed_input, width, height, lora_scale], outputs=[result, seed_output, progress_bar])
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+ cancel.click(lambda: None, None, None, cancels=[generate])
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  demo.queue().launch()