voice-changer/server/voice_changer/RVC/pitchExtractor/CrepeOnnxPitchExtractor.py
2023-10-09 12:15:03 +09:00

66 lines
2.1 KiB
Python

import numpy as np
from const import PitchExtractorType
from voice_changer.RVC.deviceManager.DeviceManager import DeviceManager
from voice_changer.RVC.pitchExtractor.PitchExtractor import PitchExtractor
import onnxruntime
from voice_changer.RVC.pitchExtractor import onnxcrepe
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
)
def extract(self, audio, pitchf, f0_up_key, sr, window, silence_front=0):
start_frame = int(silence_front * sr / window)
real_silence_front = start_frame * window / sr
silence_front_offset = int(np.round(real_silence_front * sr))
audio = audio[silence_front_offset:]
f0_min = 50
f0_max = 1100
f0_mel_min = 1127 * np.log(1 + f0_min / 700)
f0_mel_max = 1127 * np.log(1 + f0_max / 700)
precision = 10.0
audio_num = audio.cpu()
onnx_f0, onnx_pd = onnxcrepe.predict(
self.onnx_session,
audio_num,
sr,
precision=precision,
fmin=f0_min,
fmax=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()
f0 *= pow(2, f0_up_key / 12)
pitchf[-f0.shape[0]:] = f0[:pitchf.shape[0]]
f0bak = pitchf.copy()
f0_mel = 1127.0 * np.log(1.0 + f0bak / 700.0)
f0_mel = np.clip(
(f0_mel - f0_mel_min) * 254.0 / (f0_mel_max - f0_mel_min) + 1.0, 1.0, 255.0
)
pitch_coarse = f0_mel.astype(int)
return pitch_coarse, pitchf