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If the wrong type is passed to a pipeline you get this error message:
ValueError:
Audio files can be provided to the Audio class using different types:
- a "str" or "Path" instance: "audio.wav" or Path("audio.wav")
- a "IOBase" instance with "read" and "seek" support: open("audio.wav", "rb")
- a "Mapping" with any of the above as "audio" key: {"audio": ...}
- a "Mapping" with both "waveform" and "sample_rate" key:
{"waveform": (channel, time) numpy.ndarray or torch.Tensor, "sample_rate": 44100}
timecodes = pipeline(audio_data)
File "D:\Programs\Python64\lib\site-packages\pyannote\audio\core\pipeline.py", line 325, in __call__
return self.apply(file, **kwargs)
File "D:\Programs\Python64\lib\site-packages\pyannote\audio\pipelines\voice_activity_detection.py", line 211, in apply
segmentations: SlidingWindowFeature = self._segmentation(
File "D:\Programs\Python64\lib\site-packages\pyannote\audio\core\inference.py", line 425, in __call__
return self.slide(waveform, sample_rate, hook=hook)
File "D:\Programs\Python64\lib\site-packages\pyannote\audio\core\inference.py", line 281, in slide
waveform.unfold(1, window_size, step_size),
AttributeError: 'numpy.ndarray' object has no attribute 'unfold'
The text was updated successfully, but these errors were encountered:
Tested versions
pyannote.audio==3.1.1
System information
Windows / CPU
Issue description
If the wrong type is passed to a pipeline you get this error message:
It says above that it supports numpy.ndarray,
Test:
Error:
The text was updated successfully, but these errors were encountered: