File size: 11,672 Bytes
404fa56 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 |
import traceback
import logging
import tempfile
logger = logging.getLogger(__name__)
import numpy as np
import soundfile as sf
import torch
from io import BytesIO
import hashlib
from infer.lib.audio import load_audio, wav2
from infer.lib.infer_pack.models import (
SynthesizerTrnMs256NSFsid,
SynthesizerTrnMs256NSFsid_nono,
SynthesizerTrnMs768NSFsid,
SynthesizerTrnMs768NSFsid_nono,
)
from infer.modules.vc.pipeline import Pipeline
from infer.modules.vc.utils import *
class VC:
def __init__(self, config):
self.n_spk = None
self.tgt_sr = None
self.net_g = None
self.pipeline = None
self.cpt = None
self.version = None
self.if_f0 = None
self.version = None
self.hubert_model = None
self.config = config
def get_vc(self, sid, *to_return_protect):
logger.info("Get sid: " + sid)
to_return_protect0 = {
"visible": self.if_f0 != 0,
"value": to_return_protect[0]
if self.if_f0 != 0 and to_return_protect
else 0.5,
"__type__": "update",
}
to_return_protect1 = {
"visible": self.if_f0 != 0,
"value": to_return_protect[1]
if self.if_f0 != 0 and to_return_protect
else 0.33,
"__type__": "update",
}
if sid == "" or sid == []:
if self.hubert_model is not None: # 考虑到轮询, 需要加个判断看是否 sid 是由有模型切换到无模型的
logger.info("Clean model cache")
del (self.net_g, self.n_spk, self.hubert_model, self.tgt_sr) # ,cpt
self.hubert_model = (
self.net_g
) = self.n_spk = self.hubert_model = self.tgt_sr = None
if torch.cuda.is_available():
torch.cuda.empty_cache()
###楼下不这么折腾清理不干净
self.if_f0 = self.cpt.get("f0", 1)
self.version = self.cpt.get("version", "v1")
if self.version == "v1":
if self.if_f0 == 1:
self.net_g = SynthesizerTrnMs256NSFsid(
*self.cpt["config"], is_half=self.config.is_half
)
else:
self.net_g = SynthesizerTrnMs256NSFsid_nono(*self.cpt["config"])
elif self.version == "v2":
if self.if_f0 == 1:
self.net_g = SynthesizerTrnMs768NSFsid(
*self.cpt["config"], is_half=self.config.is_half
)
else:
self.net_g = SynthesizerTrnMs768NSFsid_nono(*self.cpt["config"])
del self.net_g, self.cpt
if torch.cuda.is_available():
torch.cuda.empty_cache()
return (
{"visible": False, "__type__": "update"},
{
"visible": True,
"value": to_return_protect0,
"__type__": "update",
},
{
"visible": True,
"value": to_return_protect1,
"__type__": "update",
},
"",
"",
)
person = f'{os.getenv("weight_root")}/{sid}'
logger.info(f"Loading: {person}")
self.cpt = torch.load(person, map_location="cpu")
self.tgt_sr = self.cpt["config"][-1]
self.cpt["config"][-3] = self.cpt["weight"]["emb_g.weight"].shape[0] # n_spk
self.if_f0 = self.cpt.get("f0", 1)
self.version = self.cpt.get("version", "v1")
self.eps = self.cpt["info"]
if(self.eps==""):
self.eps="N/A"
synthesizer_class = {
("v1", 1): SynthesizerTrnMs256NSFsid,
("v1", 0): SynthesizerTrnMs256NSFsid_nono,
("v2", 1): SynthesizerTrnMs768NSFsid,
("v2", 0): SynthesizerTrnMs768NSFsid_nono,
}
self.net_g = synthesizer_class.get(
(self.version, self.if_f0), SynthesizerTrnMs256NSFsid
)(*self.cpt["config"], is_half=self.config.is_half)
del self.net_g.enc_q
self.net_g.load_state_dict(self.cpt["weight"], strict=False)
self.net_g.eval().to(self.config.device)
if self.config.is_half:
self.net_g = self.net_g.half()
else:
self.net_g = self.net_g.float()
model_hash = hashlib.md5(open(person, "rb").read()).hexdigest()
self.pipeline = Pipeline(self.tgt_sr, self.config)
n_spk = self.cpt["config"][-3]
index = {"value": get_index_path_from_model(sid), "__type__": "update"}
logger.info("Select index: " + index["value"])
if self.eps == 'N/A':
epoch_str = "This is a v1 model, on some older models epochs were not used."
else:
epoch_str = self.eps[:-5] if self.eps.endswith('epoch') else self.eps
fstr = f"Epochs: {epoch_str}\nSample Rate: {self.tgt_sr}\nVersion: {self.version}\nHash: {model_hash}"
logger.info(fstr)
return (
(
{"visible": True, "maximum": n_spk, "__type__": "update"},
to_return_protect0,
to_return_protect1,
index,
index,
fstr,
)
if to_return_protect
else {"visible": True, "maximum": n_spk, "__type__": "update"}
)
def vc_single(
self,
sid,
input_audio_path_uploaded,
input_audio_path_select,
f0_up_key,
f0_file,
f0_method,
file_index,
file_index2,
index_rate,
filter_radius,
resample_sr,
rms_mix_rate,
protect,
):
# if the type of input_audio_path is temporaryFileWrapper, it means the user has used a voice recording, so use the filepath of the temporary file
if (input_audio_path_uploaded is None) and (input_audio_path_select is None):
return "You need to upload an audio or select from audios", None
f0_up_key = int(f0_up_key)
if (isinstance(input_audio_path_uploaded, str) and os.path.isfile(input_audio_path_uploaded)) and (isinstance(input_audio_path_select, str) and os.path.isfile(input_audio_path_select)):
print("Dual input!!! Using uploaded instead of selected.")
input_audio_path = open(input_audio_path_uploaded, 'rb')
if (not (isinstance(input_audio_path_uploaded, str) and os.path.isfile(input_audio_path_uploaded))) and (isinstance(input_audio_path_select, str) and os.path.isfile(input_audio_path_select)):
print("Using Selected file")
input_audio_path = open(input_audio_path_select, 'rb')
try:
audio = load_audio(input_audio_path.name, 16000)
audio_max = np.abs(audio).max() / 0.95
if audio_max > 1:
audio /= audio_max
times = [0, 0, 0]
if self.hubert_model is None:
self.hubert_model = load_hubert(self.config)
file_index = (
(
file_index.strip(" ")
.strip('"')
.strip("\n")
.strip('"')
.strip(" ")
.replace("trained", "added")
)
if file_index != ""
else file_index2
) # 防止小白写错，自动帮他替换掉
audio_opt = self.pipeline.pipeline(
self.hubert_model,
self.net_g,
sid,
audio,
input_audio_path,
times,
f0_up_key,
f0_method,
file_index,
index_rate,
self.if_f0,
filter_radius,
self.tgt_sr,
resample_sr,
rms_mix_rate,
self.version,
protect,
f0_file,
)
if self.tgt_sr != resample_sr >= 16000:
tgt_sr = resample_sr
else:
tgt_sr = self.tgt_sr
index_info = (
"Index:\n%s." % file_index
if os.path.exists(file_index)
else "Index not used."
)
return (
"Success.\n%s\nTime:\nnpy: %.2fs, f0: %.2fs, infer: %.2fs."
% (index_info, *times),
(tgt_sr, audio_opt),
)
except:
info = traceback.format_exc()
logger.warning(info)
return info, (None, None)
def vc_multi(
self,
sid,
dir_path,
opt_root,
paths,
f0_up_key,
f0_method,
file_index,
file_index2,
index_rate,
filter_radius,
resample_sr,
rms_mix_rate,
protect,
format1,
):
try:
dir_path = (
dir_path.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
) # 防止小白拷路径头尾带了空格和"和回车
opt_root = opt_root.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
os.makedirs(opt_root, exist_ok=True)
try:
if dir_path != "":
paths = [
os.path.join(dir_path, name) for name in os.listdir(dir_path)
]
else:
paths = [path.name for path in paths]
except:
traceback.print_exc()
paths = [path.name for path in paths]
infos = []
for path in paths:
info, opt = self.vc_single(
sid,
path,
f0_up_key,
None,
f0_method,
file_index,
file_index2,
# file_big_npy,
index_rate,
filter_radius,
resample_sr,
rms_mix_rate,
protect,
)
if "Success" in info:
try:
tgt_sr, audio_opt = opt
if format1 in ["wav", "flac"]:
sf.write(
"%s/%s.%s"
% (opt_root, os.path.basename(path), format1),
audio_opt,
tgt_sr,
)
else:
path = "%s/%s.%s" % (
opt_root,
os.path.basename(path),
format1,
)
with BytesIO() as wavf:
sf.write(wavf, audio_opt, tgt_sr, format="wav")
wavf.seek(0, 0)
with open(path, "wb") as outf:
wav2(wavf, outf, format1)
except:
info += traceback.format_exc()
infos.append("%s->%s" % (os.path.basename(path), info))
yield "\n".join(infos)
yield "\n".join(infos)
except:
yield traceback.format_exc()
|