| def audio_a_text(audio): | |
| text = trans(audio)["text"] | |
| return text | |
| def texto_a_sentimiento(text): | |
| return clasificador(text)[0]["label"] | |
| 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 | |