def emotion(): task_id = request.args['task_id'] if task_id is None: task_id = uuid.uuid4().hex url = request.args.get("url") if url is None: print("URL not provided") task_url = misc.get_task_url(task_id) else: task_url = url global loaded_model if loaded_model is None: loaded_model = emotion_api.getModel() loaded_model._make_predict_function() emotion_blocks = analysis_api.emotion(task_url, task_id, loaded_model) return jsonpickle.encode(emotion_blocks)
def transcibe_emotion(): task_id = request.args['task_id'] if task_id is None: task_id = uuid.uuid4().hex task_url = misc.get_task_url(task_id) url = request.args.get("url") if url is None: print("URL not provided") else: task_url = url language = request.args['language'] model = (request.args['model'] == 'True') engine = request.args['engine'] if engine is None: engine = 'google' conversation_blocks = analysis_api.transcribe_emotion(engine, task_id, language, model, loaded_model, pool, task_url) return jsonpickle.encode(conversation_blocks)
def downloadTaskAudio(taskId): downloadResult = misc.download_file(misc.get_task_url(taskId), TASK_PATH) return downloadResult