mirror of
https://github.com/w-okada/voice-changer.git
synced 2025-01-24 22:15:02 +03:00
68 lines
2.2 KiB
Python
68 lines
2.2 KiB
Python
import numpy as np
|
|
from const import PitchExtractorType
|
|
from voice_changer.DiffusionSVC.pitchExtractor.PitchExtractor import PitchExtractor
|
|
from voice_changer.RVC.deviceManager.DeviceManager import DeviceManager
|
|
import onnxruntime
|
|
|
|
from voice_changer.RVC.pitchExtractor import onnxcrepe
|
|
from voice_changer.utils.VoiceChangerModel import AudioInOut
|
|
|
|
|
|
class CrepeOnnxPitchExtractor(PitchExtractor):
|
|
|
|
def __init__(self, pitchExtractorType: PitchExtractorType, file: str, gpu: int):
|
|
self.pitchExtractorType = pitchExtractorType
|
|
super().__init__()
|
|
(
|
|
onnxProviders,
|
|
onnxProviderOptions,
|
|
) = DeviceManager.get_instance().getOnnxExecutionProvider(gpu)
|
|
|
|
self.onnx_session = onnxruntime.InferenceSession(
|
|
file, providers=onnxProviders, provider_options=onnxProviderOptions
|
|
)
|
|
self.f0_min = 50
|
|
self.f0_max = 1100
|
|
self.sapmle_rate = 16000
|
|
self.uv_interp = True
|
|
|
|
def extract(self, audio: AudioInOut, sr: int, block_size: int, model_sr: int, pitch, f0_up_key, silence_front=0):
|
|
hop_size = block_size * sr / model_sr
|
|
|
|
offset_frame_number = silence_front * sr
|
|
start_frame = int(offset_frame_number / hop_size) # frame
|
|
real_silence_front = start_frame * hop_size / sr # 秒
|
|
audio = audio[int(np.round(real_silence_front * sr)):].astype(np.float32)
|
|
|
|
precision = (1000 * hop_size / sr)
|
|
|
|
onnx_f0, onnx_pd = onnxcrepe.predict(
|
|
self.onnx_session,
|
|
audio,
|
|
sr,
|
|
precision=precision,
|
|
fmin=self.f0_min,
|
|
fmax=self.f0_max,
|
|
batch_size=256,
|
|
return_periodicity=True,
|
|
decoder=onnxcrepe.decode.weighted_argmax,
|
|
)
|
|
|
|
f0 = onnxcrepe.filter.median(onnx_f0, 3)
|
|
pd = onnxcrepe.filter.median(onnx_pd, 3)
|
|
|
|
f0[pd < 0.1] = 0
|
|
f0 = f0.squeeze()
|
|
pitch[-f0.shape[0]:] = f0[:pitch.shape[0]]
|
|
f0 = pitch
|
|
|
|
if self.uv_interp:
|
|
uv = f0 == 0
|
|
if len(f0[~uv]) > 0:
|
|
f0[uv] = np.interp(np.where(uv)[0], np.where(~uv)[0], f0[~uv])
|
|
f0[f0 < self.f0_min] = self.f0_min
|
|
|
|
f0 = f0 * 2 ** (float(f0_up_key) / 12)
|
|
|
|
return f0
|