RVC/Retrieval-based-Voice-Conversion-WebUI
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Format code (#366)

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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
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2023-05-28 16:06:11 +00:00
committed by GitHub
parent e569477457
commit e435b3bb8a
6 changed files with 262 additions and 170 deletions
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40
infer_uvr5.py
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@@ -1,7 +1,9 @@
import os, sys, torch, warnings, pdb
now_dir = os.getcwd()
sys.path.append(now_dir)
from json import load as ll
warnings.filterwarnings("ignore")
import librosa
import importlib
@@ -15,6 +17,7 @@ import soundfile as sf
from uvr5_pack.lib_v5.nets_new import CascadedNet
from uvr5_pack.lib_v5 import nets_61968KB as nets
class _audio_pre_:
def __init__(self, agg, model_path, device, is_half):
self.model_path = model_path
@@ -41,7 +44,7 @@ class _audio_pre_:
self.mp = mp
self.model = model
def _path_audio_(self, music_file, ins_root=None, vocal_root=None,format="flac"):
def _path_audio_(self, music_file, ins_root=None, vocal_root=None, format="flac"):
if ins_root is None and vocal_root is None:
return "No save root."
name = os.path.basename(music_file)
@@ -122,9 +125,11 @@ class _audio_pre_:
print("%s instruments done" % name)
sf.write(
os.path.join(
ins_root, "instrument_{}_{}.{}".format(name, self.data["agg"],format)
ins_root,
"instrument_{}_{}.{}".format(name, self.data["agg"], format),
),
(np.array(wav_instrument) * 32768).astype("int16"), self.mp.param["sr"],
(np.array(wav_instrument) * 32768).astype("int16"),
self.mp.param["sr"],
) #
if vocal_root is not None:
if self.data["high_end_process"].startswith("mirroring"):
@@ -139,11 +144,13 @@ class _audio_pre_:
print("%s vocals done" % name)
sf.write(
os.path.join(
vocal_root, "vocal_{}_{}.{}".format(name, self.data["agg"],format)
vocal_root, "vocal_{}_{}.{}".format(name, self.data["agg"], format)
),
(np.array(wav_vocals) * 32768).astype("int16"), self.mp.param["sr"],
(np.array(wav_vocals) * 32768).astype("int16"),
self.mp.param["sr"],
)
class _audio_pre_new:
def __init__(self, agg, model_path, device, is_half):
self.model_path = model_path
@@ -157,9 +164,9 @@ class _audio_pre_new:
"agg": agg,
"high_end_process": "mirroring",
}
mp=ModelParameters("uvr5_pack/lib_v5/modelparams/4band_v3.json")
nout=64 if "DeReverb"in model_path else 48
model = CascadedNet(mp.param["bins"] * 2,nout)
mp = ModelParameters("uvr5_pack/lib_v5/modelparams/4band_v3.json")
nout = 64 if "DeReverb" in model_path else 48
model = CascadedNet(mp.param["bins"] * 2, nout)
cpk = torch.load(model_path, map_location="cpu")
model.load_state_dict(cpk)
model.eval()
@@ -171,7 +178,9 @@ class _audio_pre_new:
self.mp = mp
self.model = model
def _path_audio_(self, music_file, vocal_root=None, ins_root=None,format="flac"):#3个VR模型vocal和ins是反的
def _path_audio_(
self, music_file, vocal_root=None, ins_root=None, format="flac"
): # 3个VR模型vocal和ins是反的
if ins_root is None and vocal_root is None:
return "No save root."
name = os.path.basename(music_file)
@@ -252,9 +261,11 @@ class _audio_pre_new:
print("%s instruments done" % name)
sf.write(
os.path.join(
ins_root, "main_vocal_{}_{}.{}".format(name, self.data["agg"],format)
ins_root,
"main_vocal_{}_{}.{}".format(name, self.data["agg"], format),
),
(np.array(wav_instrument) * 32768).astype("int16"),self.mp.param["sr"],
(np.array(wav_instrument) * 32768).astype("int16"),
self.mp.param["sr"],
) #
if vocal_root is not None:
if self.data["high_end_process"].startswith("mirroring"):
@@ -269,9 +280,10 @@ class _audio_pre_new:
print("%s vocals done" % name)
sf.write(
os.path.join(
vocal_root, "others_{}_{}.{}".format(name, self.data["agg"],format)
vocal_root, "others_{}_{}.{}".format(name, self.data["agg"], format)
),
(np.array(wav_vocals) * 32768).astype("int16"),self.mp.param["sr"],
(np.array(wav_vocals) * 32768).astype("int16"),
self.mp.param["sr"],
)
@@ -283,7 +295,7 @@ if __name__ == "__main__":
# model_path = "uvr5_weights/VR-DeEchoNormal.pth"
model_path = "uvr5_weights/DeEchoNormal.pth"
# pre_fun = _audio_pre_(model_path=model_path, device=device, is_half=True,agg=10)
pre_fun = _audio_pre_new(model_path=model_path, device=device, is_half=True,agg=10)
pre_fun = _audio_pre_new(model_path=model_path, device=device, is_half=True, agg=10)
audio_path = "雪雪伴奏对消HP5.wav"
save_path = "opt"
pre_fun._path_audio_(audio_path, save_path, save_path)