Update app.py

app.py

@@ -148,18 +148,23 @@ def extract_gaussian(state: dict, req: gr.Request) -> Tuple[str, str]:
     torch.cuda.empty_cache()
     return gaussian_path, gaussian_path
 
-def prepare_multi_example() -> List[Image.Image]:
+def prepare_multi_example() -> List[Tuple[str, str]]:
+    """
+    Prepare example images for the 'Multiple Images' gallery.
+    Returns:
+        List[Tuple[str, str]]: A list of tuples containing image paths and captions.
+    """
     multi_case = list(set([i.split('_')[0] for i in os.listdir("assets/example_multi_image")]))
-    images = []
+    examples = []
     for case in multi_case:
-        views = []
-        for i in range(1, 4):
-            img = Image.open(f'assets/example_multi_image/{case}_{i}.png')
-            W, H = img.size
-            img = img.resize((int(W / H * 512), 512))
-            views.append(img)
-        images.append(views)
-    return images
+        case_images = []
+        for i in range(1, 4):  # Assuming 3 views per case
+            img_path = f'assets/example_multi_image/{case}_{i}.png'
+            if os.path.exists(img_path):  # Ensure the image exists
+                case_images.append((img_path, f"View {i}"))
+        if case_images:  # Only add cases with valid images
+            examples.append(case_images)
+    return examples
 
 with gr.Blocks(delete_cache=(600, 600)) as demo:
     gr.Markdown("""