Optimize application

app.py

@@ -221,7 +221,7 @@ def infer(
         (max_dimension, max_dimension),
     )
 
-    # grow_and_blur_mask
+    # Grow mask: For each kernel size apply the max filter
     grow_pixels = 10
     sigma_grow = grow_pixels / 4
     kernel_size_grow = math.ceil(sigma_grow * 1.5 + 1)
@@ -229,6 +229,7 @@ def infer(
         ImageFilter.MaxFilter(size=2 * kernel_size_grow + 1)
     )
 
+    # Blur mask: For each kernel size apply the gaussian blur filter
     blur_pixels = 33
     sigma_blur = blur_pixels / 4
     kernel_size_blur = math.ceil(sigma_blur * 1.5 + 1)
@@ -247,9 +248,6 @@ def infer(
         (max_dimension, max_dimension),
     )
 
-    room_image_padded.save("room_image_padded.png")
-    room_mask_padded.save("room_mask_padded.png")
-
     furniture_image, _ = pad(
         furniture_image_input,
         (max_dimension, max_dimension),
@@ -286,8 +284,7 @@ def infer(
     prompt = (
         furniture_prompt + ".\n" + SYSTEM_PROMPT if furniture_prompt else SYSTEM_PROMPT
     )
-    image.save("image.png")
-    mask.save("mask.png")
+
     results_images = pipe(
         prompt=prompt,
         image=image,
@@ -320,6 +317,15 @@ def infer(
             room_mask_cropped,
         )
         final_images.append(final_image)
+    final_images_gradio = [
+        gr.Image(
+            value=image,
+            label=f"Result {i + 1}",
+            show_label=False,
+            interactive=False,
+        )
+        for i, image in enumerate(final_images)
+    ]
 
     return final_images, seed