fix ismultiimage bug

app.py

@@ -111,7 +111,7 @@ def get_seed(randomize_seed: bool, seed: int) -> int:
 def image_to_3d(
     image: Image.Image,
     multiimages: List[Tuple[Image.Image, str]],
-    is_multiimage: bool,
+    is_multiimage: str,
     seed: int,
     ss_guidance_strength: float,
     ss_sampling_steps: int,
@@ -126,7 +126,7 @@ def image_to_3d(
     Args:
         image (Image.Image): The input image for single-image mode.
         multiimages (List[Tuple[Image.Image, str]]): List of images with captions for multi-image mode.
-        is_multiimage (bool): Whether to use multi-image generation.
+        is_multiimage (str): Whether to use multi-image generation.
         seed (int): Random seed for reproducibility.
         ss_guidance_strength (float): Sparse structure guidance strength.
         ss_sampling_steps (int): Sparse structure sampling steps.
@@ -141,6 +141,7 @@ def image_to_3d(
     """
     user_dir = os.path.join(TMP_DIR, str(req.session_hash))
     os.makedirs(user_dir, exist_ok=True)
+    is_multiimage = is_multiimage.lower() == "true"
 
     # Run pipeline depending on mode
     if not is_multiimage:
@@ -269,7 +270,7 @@ def split_image(image: Image.Image) -> List[Image.Image]:
 def quick_generate_glb(
     image: Image.Image,
     multiimages: List[Tuple[Image.Image, str]],
-    is_multiimage: bool,
+    is_multiimage: str,
     seed: int,
     ss_guidance_strength: float,
     ss_sampling_steps: int,
@@ -299,7 +300,7 @@ def quick_generate_glb(
 def quick_generate_gs(
     image: Image.Image,
     multiimages: List[Tuple[Image.Image, str]],
-    is_multiimage: bool,
+    is_multiimage: str,
     seed: int,
     ss_guidance_strength: float,
     ss_sampling_steps: int,
@@ -333,7 +334,7 @@ def test_for_api_gen(image: Image.Image) -> Image.Image:
         Image.Image: The preprocessed image no processs.
     """
     return image
-    
+
 
 
 with gr.Blocks(delete_cache=(600, 600)) as demo:
@@ -374,6 +375,12 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
                         *NOTE: this is an experimental algorithm without training a specialized model. It may not produce the best results for all images, especially those having different poses or inconsistent details.*
                     """)
             
+            is_multiimage = gr.Radio(choices=["true", "false"],value="false",label="Use multi-image mode",visible=True)
+            def update_is_multiimage(tab_index: int):
+                return "true" if tab_index == 1 else "false"
+            input_tabs.select(fn=update_is_multiimage,inputs=None,outputs=is_multiimage)
+    
+            
             with gr.Accordion(label="Generation Settings", open=False):
                 seed = gr.Slider(0, MAX_SEED, label="Seed", value=0, step=1)
                 randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)