mindspore.dataset.audio.AmplitudeToDB
- class mindspore.dataset.audio.AmplitudeToDB(stype=ScaleType.POWER, ref_value=1.0, amin=1e-10, top_db=80.0)[source]
Turn the input audio waveform from the amplitude/power scale to decibel scale.
Note
The shape of the audio waveform to be processed needs to be <…, freq, time>.
- Parameters
stype (ScaleType, optional) – Scale of the input waveform, which can be
ScaleType.POWER
orScaleType.MAGNITUDE
. Default:ScaleType.POWER
.ref_value (float, optional) –
Multiplier reference value for generating db_multiplier . Default:
1.0
. The formula is .amin (float, optional) – Lower bound to clamp the input waveform, which must be greater than zero. Default:
1e-10
.top_db (float, optional) – Minimum cut-off decibels, which must be non-negative. Default:
80.0
.
- Raises
TypeError – If stype is not of type
mindspore.dataset.audio.ScaleType
.TypeError – If ref_value is not of type float.
ValueError – If ref_value is not a positive number.
TypeError – If amin is not of type float.
ValueError – If amin is not a positive number.
TypeError – If top_db is not of type float.
ValueError – If top_db is not a positive number.
RuntimeError – If input tensor is not in shape of <…, freq, time>.
- Supported Platforms:
CPU
Examples
>>> import numpy as np >>> import mindspore.dataset as ds >>> import mindspore.dataset.audio as audio >>> >>> # Use the transform in dataset pipeline mode >>> waveform = np.random.random([5, 400 // 2 + 1, 30]) # 5 samples >>> numpy_slices_dataset = ds.NumpySlicesDataset(data=waveform, column_names=["audio"]) >>> transforms = [audio.AmplitudeToDB(stype=audio.ScaleType.POWER)] >>> numpy_slices_dataset = numpy_slices_dataset.map(operations=transforms, input_columns=["audio"]) >>> for item in numpy_slices_dataset.create_dict_iterator(num_epochs=1, output_numpy=True): ... print(item["audio"].shape, item["audio"].dtype) ... break (201, 30) float64 >>> >>> # Use the transform in eager mode >>> waveform = np.random.random([400 // 2 + 1, 30]) # 1 sample >>> output = audio.AmplitudeToDB(stype=audio.ScaleType.POWER)(waveform) >>> print(output.shape, output.dtype) (201, 30) float64
- Tutorial Examples: