refactor image_to_3d to support numpy arrays and improve error handling

app.py

@@ -312,7 +312,7 @@ def unpack_state(state: dict) -> Tuple[Gaussian, edict, str]:
 
 @spaces.GPU
 def image_to_3d(
-    image: Image.Image,
+    image,
     seed: int,
     ss_guidance_strength: float,
     ss_sampling_steps: int,
@@ -332,8 +332,15 @@ def image_to_3d(
         # Call cuda() here in the GPU worker process
         pipeline.cuda()
         
+        # Convert image to the right format if needed
+        if isinstance(image, np.ndarray):
+            image = Image.fromarray(image.astype('uint8'))
+            
+        # Make sure we have a list of images as expected by the pipeline
+        input_image = [image]
+        
         outputs = pipeline.run(
-            image,
+            input_image,
             seed=seed,
             formats=["gaussian", "mesh"],
             preprocess_image=False,
@@ -357,6 +364,8 @@ def image_to_3d(
         return state, video_path
     except Exception as e:
         print(f"Error in image_to_3d: {str(e)}")
+        import traceback
+        traceback.print_exc()  # Print the full stack trace for debugging
         return None, f"Error generating 3D model: {str(e)}"
 
 
@@ -618,3 +627,4 @@ if __name__ == "__main__":
 
     demo = create_interface()
     demo.launch(debug=True)
+