# from funasr import AutoModel
# import time

# def vocal_text(input_video_path):
#     model = AutoModel(model="./Voice_translation", model_revision="v2.0.4",
#                     vad_model="./Endpoint_detection", vad_model_revision="v2.0.4",
#                     punc_model="./Ct_punc", punc_model_revision="v2.0.4",
#                     use_cuda=True,use_fast = True,
#                     )
#     res = model.generate(input_video_path,
#                 batch_size_s=30,
#                 hotword='test')


#     texts = [item['text'] for item in res]


#     result = ' '.join(texts)
#     return result


# if  __name__ == "__main__":
#     start_time = time.time()


#     model = AutoModel(model="./Voice_translation", model_revision="v2.0.4",
#                     vad_model="./Endpoint_detection", vad_model_revision="v2.0.4",
#                     punc_model="./Ct_punc", punc_model_revision="v2.0.4",
#                     )
#     res = model.generate(input="./data/audio/5bf77846-0193-4f35-92f7-09ce51ee3793.mp3",
#                 batch_size_s=30,
#                 hotword='test')

#     print(res)
#     texts = [item['text'] for item in res]

#     print(texts)
#     result = ' '.join(texts)
#     print(result)


# # def save(input,savepath):
# #     outputs = open(savepath, 'w', encoding='utf-8')
# #     outputs.write(input+'\n')
# #     outputs.close()
# # save(input=result,savepath=r"F:\work\voice_translation\datasets\1.txt")

#     end_time = time.time()
#     # 计算时间差
#     elapsed_time = end_time - start_time

#     print(f"耗时: {elapsed_time} 秒")