Update app.py

app.py

@@ -191,6 +191,36 @@ DEFAULT_VALUES = {
     "color_fix_method": "adain"
 }
 
+# Create interface components
+with gr.Blocks(title="Controllable Conditional Super-Resolution") as demo:
+    gr.Markdown("## Controllable Conditional Super-Resolution")
+    gr.Markdown("Upload an image to enhance its resolution using CCSR.")
+    
+    with gr.Row():
+        with gr.Column():
+            input_image = gr.Image(label="Input Image")
+            
+            with gr.Accordion("Advanced Options", open=False):
+                prompt = gr.Textbox(label="Prompt", value=DEFAULT_VALUES["prompt"])
+                negative_prompt = gr.Textbox(label="Negative Prompt", value=DEFAULT_VALUES["negative_prompt"])
+                guidance_scale = gr.Slider(minimum=1.0, maximum=20.0, value=DEFAULT_VALUES["guidance_scale"], label="Guidance Scale")
+                conditioning_scale = gr.Slider(minimum=0.1, maximum=2.0, value=DEFAULT_VALUES["conditioning_scale"], label="Conditioning Scale")
+                num_steps = gr.Slider(minimum=1, maximum=50, value=DEFAULT_VALUES["num_steps"], step=1, label="Number of Steps")
+                seed = gr.Number(label="Seed", value=DEFAULT_VALUES["seed"])
+                upscale_factor = gr.Slider(minimum=1, maximum=8, value=DEFAULT_VALUES["upscale_factor"], step=1, label="Upscale Factor")
+                color_fix_method = gr.Dropdown(
+                    choices=["none", "wavelet", "adain"], 
+                    label="Color Fix Method", 
+                    value=DEFAULT_VALUES["color_fix_method"]
+                )
+            
+            with gr.Row():
+                clear_btn = gr.Button("Clear")
+                submit_btn = gr.Button("Submit", variant="primary")
+
+        with gr.Column():
+            output_image = gr.Image(label="Generated Image")
+
 # Define example data
 EXAMPLES = [
     [
@@ -250,51 +280,33 @@ EXAMPLES = [
     ]
 ]
 
-# Create interface components
-with gr.Blocks(title="Controllable Conditional Super-Resolution") as demo:
-    gr.Markdown("## Controllable Conditional Super-Resolution")
-    gr.Markdown("Upload an image to enhance its resolution using CCSR.")
-    
+    # Add gallery of examples
     with gr.Row():
-        with gr.Column():
-            input_image = gr.Image(label="Input Image")
-            
-            with gr.Accordion("Advanced Options", open=False):
-                prompt = gr.Textbox(label="Prompt", value=DEFAULT_VALUES["prompt"])
-                negative_prompt = gr.Textbox(label="Negative Prompt", value=DEFAULT_VALUES["negative_prompt"])
-                guidance_scale = gr.Slider(minimum=1.0, maximum=20.0, value=DEFAULT_VALUES["guidance_scale"], label="Guidance Scale")
-                conditioning_scale = gr.Slider(minimum=0.1, maximum=2.0, value=DEFAULT_VALUES["conditioning_scale"], label="Conditioning Scale")
-                num_steps = gr.Slider(minimum=1, maximum=50, value=DEFAULT_VALUES["num_steps"], step=1, label="Number of Steps")
-                seed = gr.Number(label="Seed", value=DEFAULT_VALUES["seed"])
-                upscale_factor = gr.Slider(minimum=1, maximum=8, value=DEFAULT_VALUES["upscale_factor"], step=1, label="Upscale Factor")
-                color_fix_method = gr.Dropdown(
-                    choices=["none", "wavelet", "adain"], 
-                    label="Color Fix Method", 
-                    value=DEFAULT_VALUES["color_fix_method"]
-                )
-            
-            with gr.Row():
-                clear_btn = gr.Button("Clear")
-                submit_btn = gr.Button("Submit", variant="primary")
-
-        with gr.Column():
-            output_image = gr.Image(label="Generated Image")
+        gr.Examples(
+            examples=examples,
+            inputs=[
+                input_image, prompt, negative_prompt, guidance_scale,
+                conditioning_scale, num_steps, seed, upscale_factor,
+                color_fix_method
+            ],
+            outputs=output_image,
+            fn=process_image,
+            run_on_click=True  # This makes it run inference automatically when clicked
+        )
 
-    # Add examples
-    gr.Examples(
-        examples=EXAMPLES,
+    # Define submit action
+    submit_btn.click(
+        fn=process_image,
         inputs=[
             input_image, prompt, negative_prompt, guidance_scale,
             conditioning_scale, num_steps, seed, upscale_factor,
             color_fix_method
         ],
-        outputs=output_image,
-        fn=process_image,
-        cache_examples=True  # Cache the results for faster loading
+        outputs=output_image
     )
 
-    # Define submit action
-    submit_btn.click(
+    # Add event handler for input image change
+    input_image.change(
         fn=process_image,
         inputs=[
             input_image, prompt, negative_prompt, guidance_scale,
@@ -329,4 +341,4 @@ with gr.Blocks(title="Controllable Conditional Super-Resolution") as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()