def transcribe(audio):
    text = trans(audio)["text"]
    return text

def clasificacion(text):
    return clasificador(text)[0]["label"]


def clasifica_imagen(inp):
    inp = inp.reshape((-1224,224,3))
    inp = tf.keras.applications.mobilenet_v2.preprocess_input(inp)
    prediction = inception_net.predict(inp).flatten()
    confidences = {etiquetas[i]:float(prediction[i]) for i in range(1000)}
    return confidences