Update app.py

app.py

@@ -10,11 +10,9 @@ utils = torch.hub.load('NVIDIA/DeepLearningExamples:torchhub', 'nvidia_convnets_
 resnet50.eval().to(device)
 
 def inference(img):
-
   img_transforms = transforms.Compose(
                 [transforms.Resize(256), transforms.CenterCrop(224), transforms.ToTensor()]
   )
-
   img = img_transforms(img)
   with torch.no_grad():
     # mean and std are not multiplied by 255 as they are in training script
@@ -29,7 +27,7 @@ def inference(img):
     [img]
   ).to(device)
  
- with torch.no_grad():
+  with torch.no_grad():
     output = torch.nn.functional.softmax(resnet50(batch), dim=1)      
     
   results = utils.pick_n_best(predictions=output, n=5)