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 11:00:23 +00:00
Code Issues Packages Projects Releases Wiki Activity

Reformat and rewrite _get_name_params (#57)

Browse Source 
* Reformat

* rewrite _get_name_params

* Add workflow for automatic formatting

* Revert "Add workflow for automatic formatting"

This reverts commit 9111c5dbc1.

* revert Retrieval_based_Voice_Conversion_WebUI.ipynb

---------

Co-authored-by: 源文雨 <41315874+fumiama@users.noreply.github.com>
This commit is contained in:
Ftps
2023-04-15 20:44:24 +09:00
committed by GitHub
parent aaa893c4b1
commit c8261b2ccc
45 changed files with 4878 additions and 2456 deletions
Download Patch File Download Diff File Expand all files Collapse all files

117
trainset_preprocess_pipeline_print.py
View File

@@ -1,5 +1,6 @@
import sys,os,multiprocessing
now_dir=os.getcwd()
import sys, os, multiprocessing
now_dir = os.getcwd()
sys.path.append(now_dir)
inp_root = sys.argv[1]
@@ -7,15 +8,17 @@ sr = int(sys.argv[2])
n_p = int(sys.argv[3])
exp_dir = sys.argv[4]
noparallel = sys.argv[5] == "True"
import numpy as np,os,traceback
import numpy as np, os, traceback
from slicer2 import Slicer
import librosa,traceback
from scipy.io import wavfile
import librosa, traceback
from scipy.io import wavfile
import multiprocessing
from my_utils import load_audio
mutex = multiprocessing.Lock()
f = open("%s/preprocess.log"%exp_dir, "a+")
f = open("%s/preprocess.log" % exp_dir, "a+")
def println(strr):
mutex.acquire()
print(strr)
@@ -23,81 +26,101 @@ def println(strr):
f.flush()
mutex.release()
class PreProcess():
def __init__(self,sr,exp_dir):
class PreProcess:
def __init__(self, sr, exp_dir):
self.slicer = Slicer(
sr=sr,
threshold=-32,
min_length=800,
min_interval=400,
hop_size=15,
max_sil_kept=150
max_sil_kept=150,
)
self.sr=sr
self.per=3.7
self.overlap=0.3
self.tail=self.per+self.overlap
self.max=0.95
self.alpha=0.8
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)
self.sr = sr
self.per = 3.7
self.overlap = 0.3
self.tail = self.per + self.overlap
self.max = 0.95
self.alpha = 0.8
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_audio = (tmp_audio / np.abs(tmp_audio).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*32768).astype(np.int16))
def norm_write(self, tmp_audio, idx0, idx1):
tmp_audio = (tmp_audio / np.abs(tmp_audio).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 * 32768).astype(np.int16),
)
tmp_audio = librosa.resample(tmp_audio, orig_sr=self.sr, target_sr=16000)
wavfile.write("%s/%s_%s.wav" % (self.wavs16k_dir, idx0, idx1), 16000, (tmp_audio*32768).astype(np.int16))
wavfile.write(
"%s/%s_%s.wav" % (self.wavs16k_dir, idx0, idx1),
16000,
(tmp_audio * 32768).astype(np.int16),
)
def pipeline(self,path, idx0):
def pipeline(self, path, idx0):
try:
audio = load_audio(path,self.sr)
idx1=0
audio = load_audio(path, self.sr)
idx1 = 0
for audio in self.slicer.slice(audio):
i = 0
while (1):
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)
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:]
break
self.norm_write(tmp_audio, idx0, idx1)
println("%s->Suc."%path)
println("%s->Suc." % path)
except:
println("%s->%s"%(path,traceback.format_exc()))
println("%s->%s" % (path, traceback.format_exc()))
def pipeline_mp(self,infos):
def pipeline_mp(self, infos):
for path, idx0 in infos:
self.pipeline(path,idx0)
self.pipeline(path, idx0)
def pipeline_mp_inp_dir(self,inp_root,n_p):
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))))]
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],))
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],)
)
p.start()
ps.append(p)
for p in ps:p.join()
for p in ps:
p.join()
except:
println("Fail. %s"%traceback.format_exc())
println("Fail. %s" % traceback.format_exc())
def preprocess_trainset(inp_root, sr, n_p, exp_dir):
pp=PreProcess(sr,exp_dir)
pp = PreProcess(sr, exp_dir)
println("start preprocess")
println(sys.argv)
pp.pipeline_mp_inp_dir(inp_root,n_p)
pp.pipeline_mp_inp_dir(inp_root, n_p)
println("end preprocess")
if __name__=='__main__':
if __name__ == "__main__":
preprocess_trainset(inp_root, sr, n_p, exp_dir)