Update app.py

app.py

@@ -25,10 +25,10 @@ model.load_state_dict(torch.load('model_weights_mobilenet_v2_valp1trainp2.pth',m
 
 def inference(input_image):
     preprocess = transforms.Compose([
-        transforms.Resize(256),
+        transforms.Resize(260),
         transforms.CenterCrop(224),
         transforms.ToTensor(),
-        transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
+        #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