-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathextract_f0_print.py
120 lines (109 loc) · 4.37 KB
/
extract_f0_print.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
import os,traceback,sys,parselmouth
import librosa
import pyworld
from scipy.io import wavfile
import numpy as np,logging
logging.getLogger('numba').setLevel(logging.WARNING)
from multiprocessing import Process
exp_dir = sys.argv[1]
f = open("%s/extract_f0_feature.log"%exp_dir, "a+")
def printt(strr):
print(strr)
f.write("%s\n" % strr)
f.flush()
n_p = int(sys.argv[2])
f0method = sys.argv[3]
class FeatureInput(object):
def __init__(self, samplerate=16000, hop_size=160):
self.fs = samplerate
self.hop = hop_size
self.f0_bin = 256
self.f0_max = 1100.0
self.f0_min = 50.0
self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
def compute_f0(self, path,f0_method):
x, sr = librosa.load(path, self.fs)
p_len=x.shape[0]//self.hop
assert sr == self.fs
if(f0_method=="pm"):
time_step = 160 / 16000 * 1000
f0_min = 50
f0_max = 1100
f0 = parselmouth.Sound(x, sr).to_pitch_ac(
time_step=time_step / 1000, voicing_threshold=0.6,
pitch_floor=f0_min, pitch_ceiling=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')
elif(f0_method=="harvest"):
f0, t = pyworld.harvest(
x.astype(np.double),
fs=sr,
f0_ceil=1100,
frame_period=1000 * self.hop / sr,
)
f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.fs)
elif(f0_method=="dio"):
f0, t = pyworld.dio(
x.astype(np.double),
fs=sr,
f0_ceil=1100,
frame_period=1000 * self.hop / sr,
)
f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.fs)
return f0
def coarse_f0(self, f0):
f0_mel = 1127 * np.log(1 + f0 / 700)
f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * (
self.f0_bin - 2
) / (self.f0_mel_max - self.f0_mel_min) + 1
# use 0 or 1
f0_mel[f0_mel <= 1] = 1
f0_mel[f0_mel > self.f0_bin - 1] = self.f0_bin - 1
f0_coarse = np.rint(f0_mel).astype(np.int)
assert f0_coarse.max() <= 255 and f0_coarse.min() >= 1, (
f0_coarse.max(),
f0_coarse.min(),
)
return f0_coarse
def go(self,paths,f0_method):
if (len(paths) == 0): printt("no-f0-todo")
else:
printt("todo-f0-%s"%len(paths))
n=max(len(paths)//5,1)#每个进程最多打印5条
for idx,(inp_path,opt_path1,opt_path2) in enumerate(paths):
try:
if(idx%n==0):printt("f0ing,now-%s,all-%s,-%s"%(idx,len(paths),inp_path))
if(os.path.exists(opt_path1+".npy")==True and os.path.exists(opt_path2+".npy")==True):continue
featur_pit = self.compute_f0(inp_path,f0_method)
np.save(opt_path2,featur_pit,allow_pickle=False,)#nsf
coarse_pit = self.coarse_f0(featur_pit)
np.save(opt_path1,coarse_pit,allow_pickle=False,)#ori
except:
printt("f0fail-%s-%s-%s" % (idx, inp_path,traceback.format_exc()))
if __name__=='__main__':
# exp_dir=r"E:\codes\py39\dataset\mi-test"
# n_p=16
# f = open("%s/log_extract_f0.log"%exp_dir, "w")
printt(sys.argv)
featureInput = FeatureInput()
paths=[]
inp_root= "%s/1_16k_wavs"%(exp_dir)
opt_root1="%s/2a_f0"%(exp_dir)
opt_root2="%s/2b-f0nsf"%(exp_dir)
os.makedirs(opt_root1,exist_ok=True)
os.makedirs(opt_root2,exist_ok=True)
for name in sorted(list(os.listdir(inp_root))):
inp_path="%s/%s"%(inp_root,name)
if ("spec" in inp_path): continue
opt_path1="%s/%s"%(opt_root1,name)
opt_path2="%s/%s"%(opt_root2,name)
paths.append([inp_path,opt_path1,opt_path2])
ps=[]
for i in range(n_p):
p=Process(target=featureInput.go,args=(paths[i::n_p],f0method,))
p.start()
ps.append(p)
for p in ps:
p.join()