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fixed audio

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SayanoAI
2024-10-06 21:39:08 -04:00
parent 1f05cf1fff
commit 69e8d01634
6 changed files with 43 additions and 41 deletions
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pitch_extraction.py
+14 -16
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@@ -6,7 +6,7 @@ from scipy import signal
import torch
from .lib.rmvpe import RMVPE
from .lib.audio import autotune_f0, pad_audio
from .lib.audio import autotune_f0, pad_audio, hz_to_mel
from .lib import BASE_MODELS_DIR
from .lib.utils import gc_collect, get_merge_func, get_optimal_threads, get_optimal_torch_device
@@ -20,14 +20,15 @@ class FeatureExtractor:
config.is_half,
)
self.sr = 16000 # hubert输入采样率
self.window = 160 # 每帧点数
self.t_pad = self.sr * self.x_pad # 每条前后pad时间
self.sr = 16000 # hubert sr
self.window = 160
self.f0_bins = 256
self.t_pad = self.sr * self.x_pad
self.t_pad_tgt = tgt_sr * self.x_pad
self.t_pad2 = self.t_pad * 2
self.t_query = self.sr * self.x_query # 查询切点前后查询时间
self.t_center = self.sr * self.x_center # 查询切点位置
self.t_max = self.sr * self.x_max # 免查询时长阈值
self.t_query = self.sr * self.x_query
self.t_center = self.sr * self.x_center
self.t_max = self.sr * self.x_max
self.device = config.device
self.onnx = onnx
self.f0_method_dict = {
@@ -193,7 +194,7 @@ class FeatureExtractor:
return self.model_rmvpe.infer_from_audio(x, thred=0.03)
def get_pitch_dependant_rmvpe(self, x, f0_min=1, f0_max=40000, *args, **kwargs):
def get_pitch_dependant_rmvpe(self, x, f0_min=0, f0_max=40000, *args, **kwargs):
if not hasattr(self,"model_rmvpe"):
self.model_rmvpe = RMVPE(os.path.join(BASE_MODELS_DIR,f"rmvpe.{'onnx' if self.onnx else 'pt'}"), is_half=self.is_half, device=self.device, onnx=self.onnx)
@@ -262,8 +263,8 @@ class FeatureExtractor:
**kwargs
):
time_step = self.window / self.sr * 1000
f0_mel_min = 1127 * np.log(1 + f0_min / 700)
f0_mel_max = 1127 * np.log(1 + f0_max / 700)
f0_mel_min = hz_to_mel(f0_min)
f0_mel_max = hz_to_mel(f0_max)
params = {'x': x, 'f0_up_key': f0_up_key, 'f0_min': f0_min,
'f0_max': f0_max, 'time_step': time_step, 'filter_radius': filter_radius,
'crepe_hop_length': crepe_hop_length, 'model': "full", 'onnx': rmvpe_onnx
@@ -295,12 +296,9 @@ class FeatureExtractor:
]
# f0bak = f0.copy()
f0_mel = 1127 * np.log(1 + f0 / 700)
f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
f0_mel_max - f0_mel_min
) + 1
f0_mel[f0_mel <= 1] = 1
f0_mel[f0_mel > 255] = 255
f0_mel = hz_to_mel(f0)
f0_mel = (f0_mel - f0_mel_min)*(self.f0_bins-2)/(f0_mel_max - f0_mel_min) + 1
f0_mel = np.clip(f0_mel, a_min=1, a_max=self.f0_bins-1)
f0_coarse = np.rint(f0_mel).astype(np.int16)
return f0_coarse, f0 # 1-0