Update app.py

app.py

@@ -164,8 +164,8 @@ def gradio_process_image(input_image, resolution, num_inference_steps, strength,
     
     condition_image = prepare_image(input_image, resolution, hdr)
     
-    prompt = "masterpiece, best quality, highres"
-    negative_prompt = "low quality, normal quality, ugly, blurry, blur, lowres, bad anatomy, bad hands, cropped, worst quality, verybadimagenegative_v1.3, JuggernautNegative-neg"
+    prompt = "detailed eyes,masterpiece, best quality, highres"
+    negative_prompt = "pixelated, hard edges,low quality, normal quality, ugly, blurry, blur, lowres, bad anatomy, bad hands, cropped, worst quality, verybadimagenegative_v1.3, JuggernautNegative-neg"
     
     options = {
         "prompt": prompt,
@@ -206,7 +206,7 @@ with gr.Blocks() as demo:
             run_button = gr.Button("Enhance Image")
         with gr.Column():
             output_slider = ImageSlider(label="Before / After", type="numpy")
-    with gr.Accordion("Advanced Options", open=False):
+    with gr.Accordion("Advanced Options", open=True):
         resolution = gr.Slider(minimum=256, maximum=2048, value=512, step=256, label="Resolution")
         num_inference_steps = gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Number of Inference Steps")
         strength = gr.Slider(minimum=0, maximum=1, value=0.4, step=0.01, label="Strength")
@@ -227,7 +227,7 @@ with gr.Blocks() as demo:
         inputs=[input_image, resolution, num_inference_steps, strength, hdr, guidance_scale],
         outputs=output_slider,
         fn=gradio_process_image,
-        cache_examples=True,
+        cache_examples=False,
     )
 
 demo.launch(share=True)