Update app.py

app.py

@@ -1,3 +1,4 @@
+import os
 import torch
 from PIL import Image
 from torchvision import transforms
@@ -36,7 +37,7 @@ def inference(input_image):
     # The output has unnormalized scores. To get probabilities, you can run a softmax on it.
     probabilities = torch.nn.functional.softmax(output[0], dim=0)
     # Download ImageNet labels
-    !wget https://raw.githubusercontent.com/pytorch/hub/master/imagenet_classes.txt
+    os.system("wget https://raw.githubusercontent.com/pytorch/hub/master/imagenet_classes.txt")
     # Read the categories
     with open("imagenet_classes.txt", "r") as f:
         categories = [s.strip() for s in f.readlines()]