preview of UI

app.py

@@ -1,7 +1,43 @@
 import gradio as gr
+import torch
+from diffusers import StableDiffusionInpaintPipeline
 
-def greet(name):
-    return "Hello " + name + "!!"
+pipe = StableDiffusionInpaintPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-2-inpainting",
+    torch_dtype=torch.float16,
+)
+import gradio as gr
+from PIL import Image
+
+def process_image(image: Image.Image, prompt: str, slider_value: int) -> Image.Image:
+    # Placeholder function for processing
+    # Replace this with your actual processing logic
+    # For example, modifying the image based on the slider value and prompt
+    processed_image = image.copy()  # Just returning a copy for now
+    return processed_image
+
+with gr.Blocks() as demo:
+    # Title at the top center
+    gr.Markdown("<h1 style='text-align: center;'>Image Inprinting</h1>")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            # Image upload on the left
+            image_input = gr.Image(type='pil', label='Upload Image')
+            # Slider below the image upload
+            slider = gr.Slider(minimum=1, maximum=4, step=1, value=1, label='Select Zoom')
+            # Textbox for prompt
+            prompt_input = gr.Textbox(label='Enter Prompt')
+            # Submit button
+            submit_btn = gr.Button("Submit")
+        
+        with gr.Column(scale=1):
+            # Output image on the right
+            image_output = gr.Image(label='Output Image')
+
+    # Event handler to process the image when the button is clicked
+    submit_btn.click(fn=process_image, inputs=[image_input, prompt_input, slider], outputs=image_output)
+
+# Launch the Gradio app
+demo.launch(debug=True)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()