|
|
import numpy as np |
|
|
import torch |
|
|
import torch.nn.functional as F |
|
|
from torchaudio.transforms import Resample |
|
|
from .constants import * |
|
|
from .model import E2E0, E2E |
|
|
from .spec import MelSpectrogram |
|
|
from .utils import to_local_average_f0, to_viterbi_f0 |
|
|
|
|
|
class RMVPE: |
|
|
def __init__(self, model_path, hop_length=160): |
|
|
self.resample_kernel = {} |
|
|
model = E2E0(4, 1, (2, 2)) |
|
|
ckpt = torch.load(model_path) |
|
|
model.load_state_dict(ckpt['model'], strict=False) |
|
|
model.eval() |
|
|
self.model = model |
|
|
self.mel_extractor = MelSpectrogram(N_MELS, SAMPLE_RATE, WINDOW_LENGTH, hop_length, None, MEL_FMIN, MEL_FMAX) |
|
|
self.resample_kernel = {} |
|
|
|
|
|
def mel2hidden(self, mel): |
|
|
with torch.no_grad(): |
|
|
n_frames = mel.shape[-1] |
|
|
mel = F.pad(mel, (0, 32 * ((n_frames - 1) // 32 + 1) - n_frames), mode='constant') |
|
|
hidden = self.model(mel) |
|
|
return hidden[:, :n_frames] |
|
|
|
|
|
def decode(self, hidden, thred=0.03, use_viterbi=False): |
|
|
if use_viterbi: |
|
|
f0 = to_viterbi_f0(hidden, thred=thred) |
|
|
else: |
|
|
f0 = to_local_average_f0(hidden, thred=thred) |
|
|
return f0 |
|
|
|
|
|
def infer_from_audio(self, audio, sample_rate=16000, device=None, thred=0.03, use_viterbi=False): |
|
|
if device is None: |
|
|
device = 'cuda' if torch.cuda.is_available() else 'cpu' |
|
|
try: |
|
|
audio = audio.float().unsqueeze(0).to(device) |
|
|
except: |
|
|
audio = torch.from_numpy(audio).float().unsqueeze(0).to(device) |
|
|
if sample_rate == 16000: |
|
|
audio_res = audio |
|
|
else: |
|
|
key_str = str(sample_rate) |
|
|
if key_str not in self.resample_kernel: |
|
|
self.resample_kernel[key_str] = Resample(sample_rate, 16000, lowpass_filter_width=128) |
|
|
self.resample_kernel[key_str] = self.resample_kernel[key_str].to(device) |
|
|
audio_res = self.resample_kernel[key_str](audio) |
|
|
mel_extractor = self.mel_extractor.to(device) |
|
|
self.model = self.model.to(device) |
|
|
mel = mel_extractor(audio_res, center=True) |
|
|
hidden = self.mel2hidden(mel) |
|
|
f0 = self.decode(hidden, thred=thred, use_viterbi=use_viterbi) |
|
|
return f0 |
