RVC/Retrieval-based-Voice-Conversion-WebUI
1
0
Fork 0
mirror of https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git synced 2026-01-20 02:51:09 +00:00
Code Issues Packages Projects Releases Wiki Activity

Format code (#384)

Browse Source 
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
This commit is contained in:
github-actions[bot]
2023-05-30 15:22:53 +08:00
committed by GitHub
parent 5284e38c3d
commit 89afd017ba
7 changed files with 181 additions and 133 deletions
Download Patch File Download Diff File Expand all files Collapse all files

43
infer_pack/modules/F0Predictor/DioF0Predictor.py
View File

@@ -2,26 +2,27 @@ from infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
import pyworld
import numpy as np
class DioF0Predictor(F0Predictor):
def __init__(self,hop_length=512,f0_min=50,f0_max=1100,sampling_rate=44100):
def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
self.hop_length = hop_length
self.f0_min = f0_min
self.f0_max = f0_max
self.sampling_rate = sampling_rate
def interpolate_f0(self,f0):
'''
def interpolate_f0(self, f0):
"""
对F0进行插值处理
'''
"""
data = np.reshape(f0, (f0.size, 1))
vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
vuv_vector[data > 0.0] = 1.0
vuv_vector[data <= 0.0] = 0.0
ip_data = data
frame_number = data.size
last_value = 0.0
for i in range(frame_number):
@@ -42,21 +43,25 @@ class DioF0Predictor(F0Predictor):
for k in range(i, frame_number):
ip_data[k] = last_value
else:
ip_data[i] = data[i] #这里可能存在一个没有必要的拷贝
ip_data[i] = data[i] # 这里可能存在一个没有必要的拷贝
last_value = data[i]
return ip_data[:,0], vuv_vector[:,0]
def resize_f0(self,x, target_len):
return ip_data[:, 0], vuv_vector[:, 0]
def resize_f0(self, x, target_len):
source = np.array(x)
source[source<0.001] = np.nan
target = np.interp(np.arange(0, len(source)*target_len, len(source))/ target_len, np.arange(0, len(source)), source)
source[source < 0.001] = np.nan
target = np.interp(
np.arange(0, len(source) * target_len, len(source)) / target_len,
np.arange(0, len(source)),
source,
)
res = np.nan_to_num(target)
return res
def compute_f0(self,wav,p_len=None):
def compute_f0(self, wav, p_len=None):
if p_len is None:
p_len = wav.shape[0]//self.hop_length
p_len = wav.shape[0] // self.hop_length
f0, t = pyworld.dio(
wav.astype(np.double),
fs=self.sampling_rate,
@@ -69,9 +74,9 @@ class DioF0Predictor(F0Predictor):
f0[index] = round(pitch, 1)
return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
def compute_f0_uv(self,wav,p_len=None):
def compute_f0_uv(self, wav, p_len=None):
if p_len is None:
p_len = wav.shape[0]//self.hop_length
p_len = wav.shape[0] // self.hop_length
f0, t = pyworld.dio(
wav.astype(np.double),
fs=self.sampling_rate,

14
infer_pack/modules/F0Predictor/F0Predictor.py
View File

@@ -1,16 +1,16 @@
class F0Predictor(object):
def compute_f0(self,wav,p_len):
'''
def compute_f0(self, wav, p_len):
"""
input: wav:[signal_length]
p_len:int
output: f0:[signal_length//hop_length]
'''
"""
pass
def compute_f0_uv(self,wav,p_len):
'''
def compute_f0_uv(self, wav, p_len):
"""
input: wav:[signal_length]
p_len:int
output: f0:[signal_length//hop_length],uv:[signal_length//hop_length]
'''
pass
"""
pass

55
infer_pack/modules/F0Predictor/HarvestF0Predictor.py
View File

@@ -2,26 +2,27 @@ from infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
import pyworld
import numpy as np
class HarvestF0Predictor(F0Predictor):
def __init__(self,hop_length=512,f0_min=50,f0_max=1100,sampling_rate=44100):
def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
self.hop_length = hop_length
self.f0_min = f0_min
self.f0_max = f0_max
self.sampling_rate = sampling_rate
def interpolate_f0(self,f0):
'''
def interpolate_f0(self, f0):
"""
对F0进行插值处理
'''
"""
data = np.reshape(f0, (f0.size, 1))
vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
vuv_vector[data > 0.0] = 1.0
vuv_vector[data <= 0.0] = 0.0
ip_data = data
frame_number = data.size
last_value = 0.0
for i in range(frame_number):
@@ -42,34 +43,38 @@ class HarvestF0Predictor(F0Predictor):
for k in range(i, frame_number):
ip_data[k] = last_value
else:
ip_data[i] = data[i] #这里可能存在一个没有必要的拷贝
ip_data[i] = data[i] # 这里可能存在一个没有必要的拷贝
last_value = data[i]
return ip_data[:,0], vuv_vector[:,0]
def resize_f0(self,x, target_len):
return ip_data[:, 0], vuv_vector[:, 0]
def resize_f0(self, x, target_len):
source = np.array(x)
source[source<0.001] = np.nan
target = np.interp(np.arange(0, len(source)*target_len, len(source))/ target_len, np.arange(0, len(source)), source)
source[source < 0.001] = np.nan
target = np.interp(
np.arange(0, len(source) * target_len, len(source)) / target_len,
np.arange(0, len(source)),
source,
)
res = np.nan_to_num(target)
return res
def compute_f0(self,wav,p_len=None):
def compute_f0(self, wav, p_len=None):
if p_len is None:
p_len = wav.shape[0]//self.hop_length
p_len = wav.shape[0] // self.hop_length
f0, t = pyworld.harvest(
wav.astype(np.double),
fs=self.hop_length,
f0_ceil=self.f0_max,
f0_floor=self.f0_min,
frame_period=1000 * self.hop_length / self.sampling_rate,
)
wav.astype(np.double),
fs=self.hop_length,
f0_ceil=self.f0_max,
f0_floor=self.f0_min,
frame_period=1000 * self.hop_length / self.sampling_rate,
)
f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.fs)
return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
def compute_f0_uv(self,wav,p_len=None):
def compute_f0_uv(self, wav, p_len=None):
if p_len is None:
p_len = wav.shape[0]//self.hop_length
p_len = wav.shape[0] // self.hop_length
f0, t = pyworld.harvest(
wav.astype(np.double),
fs=self.sampling_rate,

80
infer_pack/modules/F0Predictor/PMF0Predictor.py
View File

@@ -2,27 +2,27 @@ from infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
import parselmouth
import numpy as np
class PMF0Predictor(F0Predictor):
def __init__(self,hop_length=512,f0_min=50,f0_max=1100,sampling_rate=44100):
def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
self.hop_length = hop_length
self.f0_min = f0_min
self.f0_max = f0_max
self.sampling_rate = sampling_rate
def interpolate_f0(self,f0):
'''
def interpolate_f0(self, f0):
"""
对F0进行插值处理
'''
"""
data = np.reshape(f0, (f0.size, 1))
vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
vuv_vector[data > 0.0] = 1.0
vuv_vector[data <= 0.0] = 0.0
ip_data = data
frame_number = data.size
last_value = 0.0
for i in range(frame_number):
@@ -43,41 +43,55 @@ class PMF0Predictor(F0Predictor):
for k in range(i, frame_number):
ip_data[k] = last_value
else:
ip_data[i] = data[i] #这里可能存在一个没有必要的拷贝
ip_data[i] = data[i] # 这里可能存在一个没有必要的拷贝
last_value = data[i]
return ip_data[:,0], vuv_vector[:,0]
def compute_f0(self,wav,p_len=None):
return ip_data[:, 0], vuv_vector[:, 0]
def compute_f0(self, wav, p_len=None):
x = wav
if p_len is None:
p_len = x.shape[0]//self.hop_length
p_len = x.shape[0] // self.hop_length
else:
assert abs(p_len-x.shape[0]//self.hop_length) < 4, "pad length error"
assert abs(p_len - x.shape[0] // self.hop_length) < 4, "pad length error"
time_step = self.hop_length / self.sampling_rate * 1000
f0 = parselmouth.Sound(x, self.sampling_rate).to_pitch_ac(
time_step=time_step / 1000, voicing_threshold=0.6,
pitch_floor=self.f0_min, pitch_ceiling=self.f0_max).selected_array['frequency']
f0 = (
parselmouth.Sound(x, self.sampling_rate)
.to_pitch_ac(
time_step=time_step / 1000,
voicing_threshold=0.6,
pitch_floor=self.f0_min,
pitch_ceiling=self.f0_max,
)
.selected_array["frequency"]
)
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,uv = self.interpolate_f0(f0)
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, uv = self.interpolate_f0(f0)
return f0
def compute_f0_uv(self,wav,p_len=None):
def compute_f0_uv(self, wav, p_len=None):
x = wav
if p_len is None:
p_len = x.shape[0]//self.hop_length
p_len = x.shape[0] // self.hop_length
else:
assert abs(p_len-x.shape[0]//self.hop_length) < 4, "pad length error"
assert abs(p_len - x.shape[0] // self.hop_length) < 4, "pad length error"
time_step = self.hop_length / self.sampling_rate * 1000
f0 = parselmouth.Sound(x, self.sampling_rate).to_pitch_ac(
time_step=time_step / 1000, voicing_threshold=0.6,
pitch_floor=self.f0_min, pitch_ceiling=self.f0_max).selected_array['frequency']
f0 = (
parselmouth.Sound(x, self.sampling_rate)
.to_pitch_ac(
time_step=time_step / 1000,
voicing_threshold=0.6,
pitch_floor=self.f0_min,
pitch_ceiling=self.f0_max,
)
.selected_array["frequency"]
)
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,uv = self.interpolate_f0(f0)
return f0,uv
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, uv = self.interpolate_f0(f0)
return f0, uv