Spaces:
Running
Running
File size: 4,486 Bytes
7bc29af |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 |
import multiprocessing
import os
import sys
from scipy import signal
now_dir = os.getcwd()
sys.path.append(now_dir)
print(sys.argv)
inp_root = sys.argv[1]
sr = int(sys.argv[2])
n_p = int(sys.argv[3])
exp_dir = sys.argv[4]
noparallel = sys.argv[5] == "True"
per = float(sys.argv[6])
import multiprocessing
import os
import traceback
import librosa
import numpy as np
from scipy.io import wavfile
from infer.lib.audio import load_audio
from infer.lib.slicer2 import Slicer
mutex = multiprocessing.Lock()
f = open("%s/preprocess.log" % exp_dir, "a+")
def println(strr):
mutex.acquire()
print(strr)
f.write("%s\n" % strr)
f.flush()
mutex.release()
class PreProcess:
def __init__(self, sr, exp_dir, per=3.7):
self.slicer = Slicer(
sr=sr,
threshold=-42,
min_length=1500,
min_interval=400,
hop_size=15,
max_sil_kept=500,
)
self.sr = sr
self.bh, self.ah = signal.butter(N=5, Wn=48, btype="high", fs=self.sr)
self.per = per
self.overlap = 0.3
self.tail = self.per + self.overlap
self.max = 0.9
self.alpha = 0.75
self.exp_dir = exp_dir
self.gt_wavs_dir = "%s/0_gt_wavs" % exp_dir
self.wavs16k_dir = "%s/1_16k_wavs" % exp_dir
os.makedirs(self.exp_dir, exist_ok=True)
os.makedirs(self.gt_wavs_dir, exist_ok=True)
os.makedirs(self.wavs16k_dir, exist_ok=True)
def norm_write(self, tmp_audio, idx0, idx1):
tmp_max = np.abs(tmp_audio).max()
if tmp_max > 2.5:
print("%s-%s-%s-filtered" % (idx0, idx1, tmp_max))
return
tmp_audio = (tmp_audio / tmp_max * (self.max * self.alpha)) + (
1 - self.alpha
) * tmp_audio
wavfile.write(
"%s/%s_%s.wav" % (self.gt_wavs_dir, idx0, idx1),
self.sr,
tmp_audio.astype(np.float32),
)
tmp_audio = librosa.resample(
tmp_audio, orig_sr=self.sr, target_sr=16000
) # , res_type="soxr_vhq"
wavfile.write(
"%s/%s_%s.wav" % (self.wavs16k_dir, idx0, idx1),
16000,
tmp_audio.astype(np.float32),
)
def pipeline(self, path, idx0):
try:
audio = load_audio(path, self.sr)
# zero phased digital filter cause pre-ringing noise...
# audio = signal.filtfilt(self.bh, self.ah, audio)
audio = signal.lfilter(self.bh, self.ah, audio)
idx1 = 0
for audio in self.slicer.slice(audio):
i = 0
while 1:
start = int(self.sr * (self.per - self.overlap) * i)
i += 1
if len(audio[start:]) > self.tail * self.sr:
tmp_audio = audio[start : start + int(self.per * self.sr)]
self.norm_write(tmp_audio, idx0, idx1)
idx1 += 1
else:
tmp_audio = audio[start:]
idx1 += 1
break
self.norm_write(tmp_audio, idx0, idx1)
println("%s->Suc." % path)
except:
println("%s->%s" % (path, traceback.format_exc()))
def pipeline_mp(self, infos):
for path, idx0 in infos:
self.pipeline(path, idx0)
def pipeline_mp_inp_dir(self, inp_root, n_p):
try:
infos = [
("%s/%s" % (inp_root, name), idx)
for idx, name in enumerate(sorted(list(os.listdir(inp_root))))
]
if noparallel:
for i in range(n_p):
self.pipeline_mp(infos[i::n_p])
else:
ps = []
for i in range(n_p):
p = multiprocessing.Process(
target=self.pipeline_mp, args=(infos[i::n_p],)
)
ps.append(p)
p.start()
for i in range(n_p):
ps[i].join()
except:
println("Fail. %s" % traceback.format_exc())
def preprocess_trainset(inp_root, sr, n_p, exp_dir, per):
pp = PreProcess(sr, exp_dir, per)
println("start preprocess")
println(sys.argv)
pp.pipeline_mp_inp_dir(inp_root, n_p)
println("end preprocess")
if __name__ == "__main__":
preprocess_trainset(inp_root, sr, n_p, exp_dir, per)
|