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Update app.py
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app.py
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@@ -84,24 +84,24 @@ with gr.Blocks(css=css, theme="Nymbo/Nymbo_Theme") as demo:
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with gr.Column(scale=2):
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prompt = gr.Textbox(label="Descripci贸n de im谩gen")
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basemodel_choice = gr.Dropdown(label="Modelo", choices=["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-DEV"], value="black-forest-labs/FLUX.1-schnell")
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process_lora = gr.Checkbox(label="Procesar LORA")
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process_upscale = gr.Checkbox(label="Procesar Escalador")
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upscale_factor = gr.Radio(label="Factor de Escala", choices=[2, 4, 8], value=2)
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upscale_model = gr.Radio(label="Modelo de Escalado", choices=["GPFGAN", "Finegrain"], value="GPFGAN")
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with gr.Accordion(label="Opciones Avanzadas", open=False):
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demo.launch()
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with gr.Column(scale=2):
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prompt = gr.Textbox(label="Descripci贸n de im谩gen")
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basemodel_choice = gr.Dropdown(label="Modelo", choices=["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-DEV"], value="black-forest-labs/FLUX.1-schnell")
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lora_model_choice = gr.Dropdown(label="LORA Realismo", choices=["Shakker-Labs/FLUX.1-dev-LoRA-add-details", "XLabs-AI/flux-RealismLora"], value="XLabs-AI/flux-RealismLora")
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process_lora = gr.Checkbox(label="Procesar LORA")
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process_upscale = gr.Checkbox(label="Procesar Escalador")
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upscale_factor = gr.Radio(label="Factor de Escala", choices=[2, 4, 8], value=2)
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upscale_model = gr.Radio(label="Modelo de Escalado", choices=["GPFGAN", "Finegrain"], value="GPFGAN")
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with gr.Accordion(label="Opciones Avanzadas", open=False):
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width = gr.Slider(label="Ancho", minimum=512, maximum=1280, step=8, value=512)
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height = gr.Slider(label="Alto", minimum=512, maximum=1280, step=8, value=512)
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scales = gr.Slider(label="Escalado", minimum=1, maximum=20, step=1, value=10)
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steps = gr.Slider(label="Pasos", minimum=1, maximum=100, step=1, value=20)
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seed = gr.Number(label="Semilla", value=-1)
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btn = gr.Button("Generar")
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btn.click(
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fn=gen,
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inputs=[prompt, basemodel_choice, width, height, scales, steps, seed, upscale_factor, process_upscale, lora_model_choice, process_lora, upscale_model,],
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outputs=output_res,
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)
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demo.launch()
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