Upload app.py with huggingface_hub

app.py

@@ -381,7 +381,7 @@ def preprocess_image(input: Image.Image) -> Image.Image:
 
 
 @spaces.GPU(duration=60)
-def preprocess_images(images: List[Tuple[Image.Image, str]]) -> List[Image.Image]:
+def preprocess_images(images):
     """
     Preprocess a list of input images for multi-image conditioning.
     """
@@ -409,7 +409,7 @@ def unpack_state(state: dict) -> Tuple[SparseTensor, SparseTensor, int]:
     return shape_slat, tex_slat, state['res']
 
 
-def get_seed(randomize_seed: bool, seed: int) -> int:
+def get_seed(randomize_seed, seed):
     """
     Get the random seed.
     """
@@ -485,26 +485,26 @@ def split_image(image: Image.Image) -> List[Image.Image]:
 
 @spaces.GPU(duration=120)
 def image_to_3d(
-    seed: int,
-    resolution: str,
-    ss_guidance_strength: float,
-    ss_guidance_rescale: float,
-    ss_sampling_steps: int,
-    ss_rescale_t: float,
-    shape_slat_guidance_strength: float,
-    shape_slat_guidance_rescale: float,
-    shape_slat_sampling_steps: int,
-    shape_slat_rescale_t: float,
-    tex_slat_guidance_strength: float,
-    tex_slat_guidance_rescale: float,
-    tex_slat_sampling_steps: int,
-    tex_slat_rescale_t: float,
-    multiimages: List[Tuple[Image.Image, str]],
-    multiimage_algo: str,
-    tex_multiimage_algo: str,
+    seed,
+    resolution,
+    ss_guidance_strength,
+    ss_guidance_rescale,
+    ss_sampling_steps,
+    ss_rescale_t,
+    shape_slat_guidance_strength,
+    shape_slat_guidance_rescale,
+    shape_slat_sampling_steps,
+    shape_slat_rescale_t,
+    tex_slat_guidance_strength,
+    tex_slat_guidance_rescale,
+    tex_slat_sampling_steps,
+    tex_slat_rescale_t,
+    multiimages,
+    multiimage_algo,
+    tex_multiimage_algo,
     req: gr.Request,
     progress=gr.Progress(track_tqdm=True),
-) -> str:
+):
     if not multiimages:
         raise gr.Error("Please upload images or select an example first.")
 
@@ -628,12 +628,12 @@ def image_to_3d(
 
 @spaces.GPU(duration=120)
 def extract_glb(
-    state: dict,
-    decimation_target: int,
-    texture_size: int,
+    state,
+    decimation_target,
+    texture_size,
     req: gr.Request,
     progress=gr.Progress(track_tqdm=True),
-) -> Tuple[str, str]:
+):
     """
     Extract a GLB file from the 3D model.