Update app.py

app.py

@@ -48,8 +48,8 @@ def predict(path):
     scores = mx.ndarray.softmax(mod.get_outputs()[0]).asnumpy()
     # print the top-5 inferences class
     scores = np.squeeze(scores)
-    scores = reversed(scores)
     a = np.argsort(scores)[::-1]
+    a = reversed(a)
     results = {}
     for i in a[0:5]:
         results[labels[i]] = float(scores[i])