chore: Refactor app.py to improve code structure and readability

app.py

@@ -1,17 +1,50 @@
+import gradio as gr
 from gradio_client import Client, handle_file
+from gradio_imageslider import ImageSlider
+
 tile_upscaler_url = "gokaygokay/TileUpscalerV2"
 
 client_tile_upscaler = Client(tile_upscaler_url)
 
-result = client_tile_upscaler.predict(
-		param_0=handle_file('https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/bus.png'),
-		param_1=1024,
-		param_2=20,
-		param_3=0.2,
-		param_4=0,
-		param_5=6,
-		param_6=0.75,
-		param_7="DDIM",
-		api_name="/wrapper"
-)
-print(result)
+def gradio_process_image(image, resolution, num_inference_steps, strength, hdr, guidance_scale, controlnet_strength, scheduler_name):
+  result = client_tile_upscaler.predict(
+      param_0=handle_file(image),
+      param_1=resolution,
+      param_2=num_inference_steps,
+      param_3=strength,
+      param_4=hdr,
+      param_5=guidance_scale,
+      param_6=controlnet_strength,
+      param_7=scheduler_name,
+      api_name="/wrapper"
+  )
+  return result
+
+
+with gr.Blocks() as demo:
+  with gr.Row():
+    with gr.Column():
+      input_image = gr.Image(type="pil", label="Input Image")
+      run_button = gr.Button("Enhance Image")
+    with gr.Column():
+      output_slider = ImageSlider(label="Before / After", type="numpy")
+    with gr.Accordion("Advanced Options", open=False):
+      resolution = gr.Slider(minimum=128, maximum=2048, value=1024, step=128, 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=0.2, step=0.01, label="Strength")
+      hdr = gr.Slider(minimum=0, maximum=1, value=0, step=0.1, label="HDR Effect")
+      guidance_scale = gr.Slider(minimum=0, maximum=20, value=6, step=0.5, label="Guidance Scale")
+      controlnet_strength = gr.Slider(minimum=0.0, maximum=2.0, value=0.75, step=0.05, label="ControlNet Strength")
+      scheduler_name = gr.Dropdown(
+          choices=["DDIM", "DPM++ 3M SDE Karras", "DPM++ 3M Karras"],
+          value="DDIM",
+          label="Scheduler"
+      )
+
+    run_button.click(
+      fn=gradio_process_image, 
+      inputs=[input_image, resolution, num_inference_steps, strength, hdr, guidance_scale, controlnet_strength, scheduler_name],
+      outputs=output_slider
+    )
+    
+demo.launch()