Update app.py

app.py

@@ -29,11 +29,11 @@ def inference(input_image):
         #transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
     ])
     input_tensor = preprocess(input_image)
-    #input_batch = input_tensor.unsqueeze(0) # create a mini-batch as expected by the model
+    input_batch = input_tensor.unsqueeze(0) # create a mini-batch as expected by the model
 
     # move the input and model to GPU for speed if available
     if torch.cuda.is_available():
-        input_tensor = input_tensor.to('cuda')
+        input_batch = input_batch.to('cuda')
         model.to('cuda')
 
     with torch.no_grad():