Update app.py

app.py

@@ -13,7 +13,7 @@ import matplotlib.pyplot as plt
 import numpy as np
 import torch
 from loguru import logger
-from PIL import Image
+from PIL import Image as PILImage
 from torch import Tensor
 from torchaudio.backend.common import AudioMetaData
 
@@ -247,7 +247,7 @@ class SpectrogramVisualizer:
         n_fft: int = 1024,
         hop: int = 512,
         title: Optional[str] = None,
-    ) -> Image:
+    ) -> PILImage.Image:
         """Create spectrogram image from audio tensor"""
         audio = torch.as_tensor(audio)
         
@@ -276,7 +276,7 @@ class SpectrogramVisualizer:
         )
         
         figure.canvas.draw()
-        return Image.frombytes(
+        return PILImage.frombytes(
             "RGB", 
             figure.canvas.get_width_height(), 
             figure.canvas.tostring_rgb()
@@ -360,7 +360,7 @@ def process_audio(
     noise_type: str,
     snr: int,
     mic_input: Optional[str] = None,
-) -> Tuple[str, Image, str, Image]:
+) -> Tuple[str, PILImage.Image, str, PILImage.Image]:
     """Main audio processing pipeline.
     
     Args:
@@ -604,5 +604,5 @@ if __name__ == "__main__":
     demo.queue().launch(
         server_name="0.0.0.0",
         server_port=7860,
-        share=True,
+        share=False,
     )