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