如何加载多个.onnx模型,对同一个音频处理

[viviliuwqhduhnwqihwqwudceygysjiwuwnn]

from funasr_onnx import Fsmn_vad from pathlib import Path

model_dir = "damo/speech_fsmn_vad_zh-cn-16k-common-pytorch" wav_path = '{}/.cache/modelscope/hub/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/example/vad_example.wav'.format(Path.home())

model = Fsmn_vad(model_dir)

result = model(wav_path) print(result)和 from funasr_onnx import Paraformer from pathlib import Path

model_dir = r"C:.cache\modelscope\hub\damo\speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online-onnx" model = Paraformer(model_dir, batch_size=1, quantize=True)

wav_path = ['{}/.cache/modelscope/hub/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav'.format(Path.home())]

result = model(wav_path) print(result) 这两个怎么放到一起使用作用于同一个音频,输出既识别出文字又有端点检测, 类似model = AutoModel( model="iic/SenseVoiceSmall", vad_model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch", vad_kwargs={"max_single_segment_time": 60000},这种效果