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def clasifica_imagen(inp):
inp = inp.reshape((-1,224,224,3))
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
def audio_a_text(audio):
text = trans(audio)['text']
return text
def texto_a_sentimiento(text):
return clasificador(text)[0]['label']
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