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extract_f0_print.py
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extract_f0_print.py
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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()