How to use decode_predictions() for non-Imagenet models..?
In Deep learning when you are performing prediction you will get prediction in your case it is an array with 9 probabilities in them. So first perform following operation on them.

import numpy as np

prediction = model.prediction(test_data) 
# prediction will contain [[0.6, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05]]

prediction = np.argmax(prediction[0])
# Now predition hold the index of the (0.6) i.e max probability value


Now after that you should have a dictionary which contains key as 0, 1, 2, .. 8 and values as classname1, classname2, ...classname9

This is the way you will get the class name as output