Update app.py

app.py

@@ -57,7 +57,7 @@ async def gen(prompt, basemodel, width, height, scales, steps, seed, upscale_fac
             upscale_image.save("upscale_image.jpg", format="JPEG")
             return [image_path, "upscale_image.jpg"]
         else:
-            print("Error: La ruta de la imagen escalada es None")
+            print("Error: The scaled image path is None")
             return [image_path, image_path]
     else:
         return [image_path, image_path]
@@ -72,20 +72,20 @@ with gr.Blocks(css=css, theme="Nymbo/Nymbo_Theme") as demo:
             with gr.Column(scale=3):
                 output_res = ImageSlider(label="Flux / Upscaled")
             with gr.Column(scale=2):
-                prompt = gr.Textbox(label="Descripción de imágen")
-                basemodel_choice = gr.Dropdown(label="Modelo", choices=["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-DEV", "enhanceaiteam/Flux-uncensored", "Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro", "Shakker-Labs/FLUX.1-dev-LoRA-add-details", "city96/FLUX.1-dev-gguf"], value="black-forest-labs/FLUX.1-schnell")
-                lora_model_choice = gr.Dropdown(label="LORA", choices=["Shakker-Labs/FLUX.1-dev-LoRA-add-details", "XLabs-AI/flux-RealismLora", "enhanceaiteam/Flux-uncensored"], value="XLabs-AI/flux-RealismLora")
-                process_lora = gr.Checkbox(label="Procesar LORA")
-                process_upscale = gr.Checkbox(label="Procesar Escalador")
-                upscale_factor = gr.Radio(label="Factor de Escala", choices=[2, 4, 8], value=2)
+                prompt = gr.Textbox(label="Image Description")
+                basemodel_choice = gr.Dropdown(label="Model", choices=["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-DEV", "enhanceaiteam/Flux-uncensored", "Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro", "Shakker-Labs/FLUX.1-dev-LoRA-add-details", "city96/FLUX.1-dev-gguf"], value="black-forest-labs/FLUX.1-schnell")
+                lora_model_choice = gr.Dropdown(label="LoRA", choices=["Shakker-Labs/FLUX.1-dev-LoRA-add-details", "XLabs-AI/flux-RealismLora", "enhanceaiteam/Flux-uncensored"], value="XLabs-AI/flux-RealismLora")
+                process_lora = gr.Checkbox(label="LoRA Process")
+                process_upscale = gr.Checkbox(label="Scale Process")
+                upscale_factor = gr.Radio(label="Scaling Factor", choices=[2, 4, 8], value=2)
                 
-                with gr.Accordion(label="Opciones Avanzadas", open=False):
-                    width = gr.Slider(label="Ancho", minimum=512, maximum=1280, step=8, value=1280)
-                    height = gr.Slider(label="Alto", minimum=512, maximum=1280, step=8, value=768)
-                    scales = gr.Slider(label="Escalado", minimum=1, maximum=20, step=1, value=8)
-                    steps = gr.Slider(label="Pasos", minimum=1, maximum=100, step=1, value=8)
-                    seed = gr.Number(label="Semilla", value=-1)
+                with gr.Accordion(label="Advanced Options", open=False):
+                    width = gr.Slider(label="Width", minimum=512, maximum=1280, step=8, value=1280)
+                    height = gr.Slider(label="Height", minimum=512, maximum=1280, step=8, value=768)
+                    scales = gr.Slider(label="Scale", minimum=1, maximum=20, step=1, value=8)
+                    steps = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=8)
+                    seed = gr.Number(label="Seed", value=-1)
     
-                btn = gr.Button("Generar")
+                btn = gr.Button("Generate")
                 btn.click(fn=gen, inputs=[prompt, basemodel_choice, width, height, scales, steps, seed, upscale_factor, process_upscale, lora_model_choice, process_lora], outputs=output_res,)
     demo.launch()