OPENGIT/Retrieval-based-Voice-Conversion-WebUI
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fix

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yxlllc 2024-04-22 02:52:34 +08:00
parent cc6f1fee3a
commit a84c7de758
1 changed files with 6 additions and 5 deletions
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11
infer/lib/rtrvc.py
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@ -206,7 +206,7 @@ class RVC:
if not torch.is_tensor(f0): if not torch.is_tensor(f0):
f0 = torch.from_numpy(f0) f0 = torch.from_numpy(f0)
f0 = f0.float().to(self.device).squeeze() f0 = f0.float().to(self.device).squeeze()
f0_mel = 1127 * torch.log(1 + f0 * pow(2, -self.formant_shift / 12) / 700) f0_mel = 1127 * torch.log(1 + f0 / 700)
f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * 254 / ( f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * 254 / (
self.f0_mel_max - self.f0_mel_min self.f0_mel_max - self.f0_mel_min
) + 1 ) + 1
@ -398,12 +398,14 @@ class RVC:
printt("Index search FAILED") printt("Index search FAILED")
t3 = ttime() t3 = ttime()
p_len = input_wav.shape[0] // 160 p_len = input_wav.shape[0] // 160
factor = pow(2, self.formant_shift / 12)
return_length2 = int(np.ceil(return_length * factor))
if self.if_f0 == 1: if self.if_f0 == 1:
f0_extractor_frame = block_frame_16k + 800 f0_extractor_frame = block_frame_16k + 800
if f0method == "rmvpe": if f0method == "rmvpe":
f0_extractor_frame = 5120 * ((f0_extractor_frame - 1) // 5120 + 1) - 160 f0_extractor_frame = 5120 * ((f0_extractor_frame - 1) // 5120 + 1) - 160
pitch, pitchf = self.get_f0( pitch, pitchf = self.get_f0(
input_wav[-f0_extractor_frame:], self.f0_up_key, self.n_cpu, f0method input_wav[-f0_extractor_frame:], self.f0_up_key - self.formant_shift, self.n_cpu, f0method
) )
shift = block_frame_16k // 160 shift = block_frame_16k // 160
self.cache_pitch[:-shift] = self.cache_pitch[shift:].clone() self.cache_pitch[:-shift] = self.cache_pitch[shift:].clone()
@ -411,15 +413,14 @@ class RVC:
self.cache_pitch[4 - pitch.shape[0] :] = pitch[3:-1] self.cache_pitch[4 - pitch.shape[0] :] = pitch[3:-1]
self.cache_pitchf[4 - pitch.shape[0] :] = pitchf[3:-1] self.cache_pitchf[4 - pitch.shape[0] :] = pitchf[3:-1]
cache_pitch = self.cache_pitch[None, -p_len:] cache_pitch = self.cache_pitch[None, -p_len:]
cache_pitchf = self.cache_pitchf[None, -p_len:] cache_pitchf = self.cache_pitchf[None, -p_len:] * return_length2 / return_length
t4 = ttime() t4 = ttime()
feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1) feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
feats = feats[:, :p_len, :] feats = feats[:, :p_len, :]
p_len = torch.LongTensor([p_len]).to(self.device) p_len = torch.LongTensor([p_len]).to(self.device)
sid = torch.LongTensor([0]).to(self.device) sid = torch.LongTensor([0]).to(self.device)
skip_head = torch.LongTensor([skip_head]) skip_head = torch.LongTensor([skip_head])
factor = pow(2, self.formant_shift / 12) return_length2 = torch.LongTensor([return_length2])
return_length2 = torch.LongTensor([int(np.ceil(return_length * factor))])
return_length = torch.LongTensor([return_length]) return_length = torch.LongTensor([return_length])
with torch.no_grad(): with torch.no_grad():
if self.if_f0 == 1: if self.if_f0 == 1: