Update app.py

app.py

@@ -89,8 +89,8 @@ def king(type ,
 
         refine = refiner(
             prompt=instruction,
-            guidance_scale=6,
-            num_inference_steps=25,
+            guidance_scale=guidance_scale,
+            num_inference_steps=steps,
             image=output_image,
             generator=generator,
         ).images[0]  
@@ -101,7 +101,7 @@ def king(type ,
         generator = torch.Generator().manual_seed(seed)
         image = pipe(
             prompt = instruction,
-            guidance_scale =7, 
+            guidance_scale = guidance_scale, 
             num_inference_steps = steps, 
             width = width, 
             height = height,
@@ -111,11 +111,9 @@ def king(type ,
 
         refine = refiner(
             prompt=instruction,
-            guidance_scale=6,
-            num_inference_steps=25,
+            guidance_scale=guidance_scale,
+            num_inference_steps=steps,
             image=image,
-            width = width, 
-            height = height,
             generator=generator,
         ).images[0]        
         return seed, refine
@@ -141,7 +139,7 @@ def response(instruction, input_image=None ):
     return output
 
 css = '''
-.gradio-container{max-width: 600px !important}
+.gradio-container{max-width: 700px !important}
 h1{text-align:center}
 footer {
     visibility: hidden
@@ -196,6 +194,7 @@ with gr.Blocks(css=css) as demo:
     with gr.Row():
         text_cfg_scale = gr.Number(value=7.3, step=0.1, label="Text CFG", interactive=True)
         image_cfg_scale = gr.Number(value=1.7, step=0.1,label="Image CFG", interactive=True)
+        guidance_scale = gr.Number(value=6.0, step=0.1, label="Image Generation Guidance Scale", interactive=True)
         steps = gr.Number(value=25, step=1, label="Steps", interactive=True)
         randomize_seed = gr.Radio(
                 ["Fix Seed", "Randomize Seed"],
@@ -239,6 +238,7 @@ with gr.Blocks(css=css) as demo:
                 image_cfg_scale,
                 width,
                 height,
+                guidance_scale,
             ],
             outputs=[seed, input_image],
         )