feat: Refactor image refinement process in app.py

The code changes refactor the image refinement process in the `app.py` file. The `refine_image` function now uses the Hugging Face InferenceClient to handle the image-to-image transformation. This improves the efficiency and reliability of the refinement process.

app.py

@@ -1,26 +1,17 @@
 import os
 import gradio as gr
-from gradio_client import Client, handle_file
+
+from huggingface_hub import InferenceClient
+client = InferenceClient()
+
 from gradio_imageslider import ImageSlider
 
 stable_diffusion_xl_refiner_10 = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-refiner-1.0"
-refiner_client = None
 
 def refine_image(image, prompt, negative_prompt, num_inference_steps, guidance_scale, seed):
-    global refiner_client
-    if refiner_client is None:
-        refiner_client = Client(stable_diffusion_xl_refiner_10)
-    job = refiner_client.submit(
-        inputs=image,
-        parameters={
-            "prompt":prompt,
-            "negative_prompt": negative_prompt,
-            "num_inference_steps": num_inference_steps,
-            "guidance_scale": guidance_scale,
-            "seed": seed,
-        }
-    )
-    return job.result()
+
+    image = client.image_to_image(image, prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale, seed=seed, model="stabilityai/stable-diffusion-xl-refiner-1.0")
+    return image
 
 with gr.Blocks() as demo:
     image = gr.Image()