Update app.py

app.py

@@ -48,7 +48,7 @@ def predict(path):
     scores = mx.ndarray.softmax(mod.get_outputs()[0]).asnumpy()
     # print the top-5 inferences class
     scores = np.squeeze(scores)
-    a = np.argsort(scores)[::1]
+    a = np.argsort(scores)
     results = {}
     for i in a[0:5]:
         results[labels[i]] = float(scores[i])