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