Update src/vc_infer_pipeline.py

src/vc_infer_pipeline.py

@@ -77,7 +77,9 @@ class VC(object):
 
  def get_optimal_torch_device(self, index: int = 0) -> torch.device:
  if torch.cuda.is_available():
- return torch.device(f"cuda:{index % torch.cuda.device_count()}")
+ return torch.device(
+ f"cuda:{index % torch.cuda.device_count()}"
+ )
  elif torch.backends.mps.is_available():
  return torch.device("mps")
  return torch.device("cpu")
@@ -91,7 +93,9 @@ class VC(object):
  hop_length=160,
  model="full",
  ):
- x = x.astype(np.float32)
+ x = x.astype(
+ np.float32
+ )
  x /= np.quantile(np.abs(x), 0.999)
  torch_device = self.get_optimal_torch_device()
  audio = torch.from_numpy(x).to(torch_device, copy=True)
@@ -147,6 +151,12 @@ class VC(object):
  f0 = f0[0].cpu().numpy()
  return f0
 
+ def get_f0_pyin_computation(self, x, f0_min, f0_max):
+ y, sr = librosa.load("saudio/Sidney.wav", self.sr, mono=True)
+ f0, _, _ = librosa.pyin(y, sr=self.sr, fmin=f0_min, fmax=f0_max)
+ f0 = f0[1:]
+ return f0
+ 
  def get_f0_hybrid_computation(
  self,
  methods_str,
@@ -168,7 +178,10 @@ class VC(object):
  x /= np.quantile(np.abs(x), 0.999)
  for method in methods:
  f0 = None
- if method == "mangio-crepe":
+ if method == "crepe":
+ f0 = self.get_f0_official_crepe_computation(x, f0_min, f0_max)
+ f0 = f0[1:]
+ elif method == "mangio-crepe":
  f0 = self.get_f0_crepe_computation(
  x, f0_min, f0_max, p_len, crepe_hop_length
  )
@@ -234,7 +247,9 @@ class VC(object):
  )
  pad_size = (p_len - len(f0) + 1) // 2
  if pad_size > 0 or p_len - len(f0) - pad_size > 0:
- f0 = np.pad(f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant")
+ f0 = np.pad(
+ f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant"
+ )
  
  elif f0_method == "harvest":
  input_audio_path2wav[input_audio_path] = x.astype(np.double)