Update app.py

app.py

@@ -4,6 +4,7 @@ import spaces
 from transformers import AutoModelForImageSegmentation
 import torch
 from torchvision import transforms
+from typing import Union, Tuple
 
 torch.set_float32_matmul_precision(["high", "highest"][0])
 
@@ -20,7 +21,7 @@ transform_image = transforms.Compose(
     ]
 )
 
-def fn(image):
+def fn(image: Union[PILImage.Image, str]) -> Tuple[PILImage.Image, PILImage.Image]:
     """
     Remove the background from an image and return both the transparent version and the original.
 
@@ -43,7 +44,7 @@ def fn(image):
     return (processed_image, origin)
 
 @spaces.GPU
-def process(image):
+def process(image: PILImage.Image) -> PILImage.Image:
     """
     Apply BiRefNet-based image segmentation to remove the background.
 
@@ -67,7 +68,7 @@ def process(image):
     image.putalpha(mask)
     return image
 
-def process_file(f):
+def process_file(f: str) -> str:
     """
     Load an image file from disk, remove the background, and save the output as a transparent PNG.