Update app.py

app.py

@@ -40,7 +40,7 @@ def process_image(input_image: Image.Image, bg_prompt: str) -> Image.Image:
     foreground = remove(input_image)
     foreground = foreground.convert("RGBA")
 
-    # Step 2: Determine new dimensions (multiples of 8) based on the foreground.
+    # Step 2: Adjust dimensions for background generation.
     orig_w, orig_h = foreground.size
     gen_w, gen_h = adjust_size(orig_w, orig_h)
     print(f"Original size: {orig_w}x{orig_h} | Adjusted size: {gen_w}x{gen_h}")
@@ -51,18 +51,18 @@ def process_image(input_image: Image.Image, bg_prompt: str) -> Image.Image:
         bg_prompt,
         height=gen_h,
         width=gen_w,
-        num_inference_steps=50,  # Adjust as needed.
-        guidance_scale=7.5       # Adjust for prompt adherence.
+        num_inference_steps=50,  # Adjust if needed.
+        guidance_scale=7.5       # Adjust for more/less prompt adherence.
     )
-    # The generated background is in RGB mode; convert to RGBA for compositing.
+    # Convert the generated background to RGBA.
     background = bg_output.images[0].convert("RGBA")
 
-    # Step 4: If necessary, resize the foreground to match the background.
+    # Step 4: Ensure the foreground matches the background dimensions.
     if foreground.size != background.size:
         print("Resizing foreground to match background dimensions...")
         foreground = foreground.resize(background.size, Image.ANTIALIAS)
 
-    # Step 5: Composite the foreground over the new background.
+    # Step 5: Composite the images.
     print("Compositing images...")
     final_image = Image.alpha_composite(background, foreground)
 
@@ -71,7 +71,7 @@ def process_image(input_image: Image.Image, bg_prompt: str) -> Image.Image:
 # -----------------------------------------------------------------------------
 # Load the Stable Diffusion pipeline from Hugging Face.
 # -----------------------------------------------------------------------------
-MODEL_ID = "stabilityai/stable-diffusion-2"  # You may change the model if desired.
+MODEL_ID = "stabilityai/stable-diffusion-2"  # Change the model if desired.
 
 # Use half precision if GPU is available.
 if torch.cuda.is_available():
@@ -86,7 +86,7 @@ if torch.cuda.is_available():
 print("Stable Diffusion pipeline loaded.")
 
 # -----------------------------------------------------------------------------
-# Create the Gradio Interface.
+# Create the Gradio Interface using the updated API.
 # -----------------------------------------------------------------------------
 title = "Background Removal & Replacement"
 description = (
@@ -98,10 +98,10 @@ description = (
 iface = gr.Interface(
     fn=process_image,
     inputs=[
-        gr.inputs.Image(type="pil", label="Upload Your Image"),
-        gr.inputs.Textbox(lines=2, placeholder="Describe the new background...", label="Background Prompt")
+        gr.Image(type="pil", label="Upload Your Image"),
+        gr.Textbox(lines=2, placeholder="Describe the new background...", label="Background Prompt")
     ],
-    outputs=gr.outputs.Image(type="pil", label="Output Image"),
+    outputs=gr.Image(label="Output Image"),
     title=title,
     description=description,
     allow_flagging="never"