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139 lines
3.6 KiB
139 lines
3.6 KiB
#!/usr/bin/env python
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# coding: utf8
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""" This module provides audio data convertion functions. """
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# pyright: reportMissingImports=false
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# pylint: disable=import-error
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import numpy as np
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import tensorflow as tf
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from ..utils.tensor import from_float32_to_uint8, from_uint8_to_float32
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# pylint: enable=import-error
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__email__ = "spleeter@deezer.com"
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__author__ = "Deezer Research"
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__license__ = "MIT License"
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def to_n_channels(waveform: tf.Tensor, n_channels: int) -> tf.Tensor:
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"""
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Convert a waveform to n_channels by removing or duplicating channels if
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needed (in tensorflow).
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Parameters:
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waveform (tensorflow.Tensor):
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Waveform to transform.
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n_channels (int):
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Number of channel to reshape waveform in.
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Returns:
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tensorflow.Tensor:
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Reshaped waveform.
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"""
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return tf.cond(
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tf.shape(waveform)[1] >= n_channels,
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true_fn=lambda: waveform[:, :n_channels],
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false_fn=lambda: tf.tile(waveform, [1, n_channels])[:, :n_channels],
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)
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def to_stereo(waveform: np.ndarray) -> np.ndarray:
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"""
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Convert a waveform to stereo by duplicating if mono, or truncating
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if too many channels.
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Parameters:
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waveform (numpy.ndarray):
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a `(N, d)` numpy array.
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Returns:
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numpy.ndarray:
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A stereo waveform as a `(N, 1)` numpy array.
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"""
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if waveform.shape[1] == 1:
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return np.repeat(waveform, 2, axis=-1)
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if waveform.shape[1] > 2:
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return waveform[:, :2]
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return waveform
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def gain_to_db(tensor: tf.Tensor, espilon: float = 10e-10) -> tf.Tensor:
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"""
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Convert from gain to decibel in tensorflow.
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Parameters:
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tensor (tensorflow.Tensor):
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Tensor to convert
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epsilon (float):
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Operation constant.
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Returns:
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tensorflow.Tensor:
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Converted tensor.
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"""
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return 20.0 / np.log(10) * tf.math.log(tf.maximum(tensor, espilon))
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def db_to_gain(tensor: tf.Tensor) -> tf.Tensor:
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"""
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Convert from decibel to gain in tensorflow.
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Parameters:
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tensor (tensorflow.Tensor):
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Tensor to convert
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Returns:
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tensorflow.Tensor:
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Converted tensor.
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"""
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return tf.pow(10.0, (tensor / 20.0))
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def spectrogram_to_db_uint(
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spectrogram: tf.Tensor, db_range: float = 100.0, **kwargs
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) -> tf.Tensor:
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"""
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Encodes given spectrogram into uint8 using decibel scale.
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Parameters:
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spectrogram (tensorflow.Tensor):
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Spectrogram to be encoded as TF float tensor.
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db_range (float):
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Range in decibel for encoding.
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Returns:
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tensorflow.Tensor:
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Encoded decibel spectrogram as `uint8` tensor.
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"""
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db_spectrogram: tf.Tensor = gain_to_db(spectrogram)
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max_db_spectrogram: tf.Tensor = tf.reduce_max(db_spectrogram)
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db_spectrogram: tf.Tensor = tf.maximum(
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db_spectrogram, max_db_spectrogram - db_range
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)
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return from_float32_to_uint8(db_spectrogram, **kwargs)
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def db_uint_spectrogram_to_gain(
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db_uint_spectrogram: tf.Tensor, min_db: tf.Tensor, max_db: tf.Tensor
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) -> tf.Tensor:
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"""
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Decode spectrogram from uint8 decibel scale.
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Paramters:
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db_uint_spectrogram (tensorflow.Tensor):
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Decibel spectrogram to decode.
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min_db (tensorflow.Tensor):
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Lower bound limit for decoding.
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max_db (tensorflow.Tensor):
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Upper bound limit for decoding.
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Returns:
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tensorflow.Tensor:
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Decoded spectrogram as `float32` tensor.
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"""
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db_spectrogram: tf.Tensor = from_uint8_to_float32(
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db_uint_spectrogram, min_db, max_db
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)
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return db_to_gain(db_spectrogram)
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