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tflite_interpreter = tf.lite.Interpreter(model_path=TFLITE_MODEL)
input_details = tflite_interpreter.get_input_details()
output_details = tflite_interpreter.get_output_details()
print("== Input details ==")
print("shape:", input_details[0]['shape'])
print("type:", input_details[0]['dtype'])
print("\n== Output details ==")
print("shape:", output_details[0]['shape'])
print("type:", output_details[0]['dtype'])
# >> == Input details ==
# >> shape: [ 1 224 224 3]
# >> type: <class 'numpy.float32'>
# >> == Output details ==
# >> shape: [1 5]
# >> type: <class 'numpy.float32'>
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