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henryruhs
2024-04-02 13:30:19 +02:00
parent bc57669da0
commit 7b9ccdcf3a
2 changed files with 4 additions and 4 deletions
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facefusion/audio.py
+3 -4
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@@ -5,7 +5,7 @@ import scipy
from facefusion.filesystem import is_audio from facefusion.filesystem import is_audio
from facefusion.ffmpeg import read_audio_buffer from facefusion.ffmpeg import read_audio_buffer
from facefusion.typing import Fps, Audio, Spectrogram, AudioFrame from facefusion.typing import Fps, Audio, AudioFrame, Spectrogram, MelFilter
from facefusion.voice_extractor import batch_extract_voice from facefusion.voice_extractor import batch_extract_voice
@@ -65,7 +65,7 @@ def normalize_audio(audio : numpy.ndarray[Any, Any]) -> Audio:
def filter_audio(audio : Audio, filter_coefficient : float) -> Audio: def filter_audio(audio : Audio, filter_coefficient : float) -> Audio:
audio = scipy.signal.lfilter([ 1.0, filter_coefficient ], [1.0], audio) audio = scipy.signal.lfilter([ 1.0, filter_coefficient ], [ 1.0 ], audio)
return audio return audio
@@ -78,8 +78,7 @@ def convert_mel_to_hertz(mel : numpy.ndarray[Any, Any]) -> numpy.ndarray[Any, An
@lru_cache(maxsize = None) @lru_cache(maxsize = None)
def create_static_mel_filter(sample_rate : int, filter_total : int, filter_size : int, frequency_minimum : float, frequency_maximum : float) -> numpy.ndarray[Any, Any]: def create_static_mel_filter(sample_rate : int, filter_total : int, filter_size : int, frequency_minimum : float, frequency_maximum : float) -> MelFilter:
frequency_maximum = min(sample_rate / 2, frequency_maximum)
mel_filter = numpy.zeros((filter_total, filter_size // 2 + 1)) mel_filter = numpy.zeros((filter_total, filter_size // 2 + 1))
mel_bins = numpy.linspace(convert_hertz_to_mel(frequency_minimum), convert_hertz_to_mel(frequency_maximum), filter_total + 2) mel_bins = numpy.linspace(convert_hertz_to_mel(frequency_minimum), convert_hertz_to_mel(frequency_maximum), filter_total + 2)
indices = numpy.floor((filter_size + 1) * convert_mel_to_hertz(mel_bins) / sample_rate).astype(numpy.int16) indices = numpy.floor((filter_size + 1) * convert_mel_to_hertz(mel_bins) / sample_rate).astype(numpy.int16)
facefusion/typing.py
+1
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@@ -46,6 +46,7 @@ Audio = numpy.ndarray[Any, Any]
AudioChunk = numpy.ndarray[Any, Any] AudioChunk = numpy.ndarray[Any, Any]
AudioFrame = numpy.ndarray[Any, Any] AudioFrame = numpy.ndarray[Any, Any]
Spectrogram = numpy.ndarray[Any, Any] Spectrogram = numpy.ndarray[Any, Any]
MelFilter = numpy.ndarray[Any, Any]
Fps = float Fps = float
Padding = Tuple[int, int, int, int] Padding = Tuple[int, int, int, int]