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webui.py
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import json, yaml, warnings, torch
import platform
warnings.filterwarnings("ignore")
torch.manual_seed(233333)
import os, sys
now_dir = os.getcwd()
tmp = os.path.join(now_dir, "TEMP")
os.makedirs(tmp, exist_ok=True)
os.environ["TEMP"] = tmp
import site
site_packages_root = "%s/runtime/Lib/site-packages" % now_dir
for path in site.getsitepackages():
if "site-packages" in path:
site_packages_root = path
os.environ["OPENBLAS_NUM_THREADS"] = "4"
os.environ["no_proxy"] = "localhost, 127.0.0.1, ::1"
with open("%s/users.pth" % (site_packages_root), "w") as f:
f.write(
"%s\n%s/tools\n%s/tools/damo_asr\n%s/GPT_SoVITS\n%s/tools/uvr5"
% (now_dir, now_dir, now_dir, now_dir, now_dir)
)
import traceback
sys.path.append(now_dir)
import gradio as gr
from subprocess import Popen
from config import (
python_exec,
infer_device,
is_half,
exp_root,
webui_port_main,
webui_port_infer_tts,
webui_port_uvr5,
webui_port_subfix,
)
from tools.i18n.i18n import I18nAuto
i18n = I18nAuto()
from multiprocessing import cpu_count
n_cpu = cpu_count()
# 判断是否有能用来训练和加速推理的N卡
ngpu = torch.cuda.device_count()
gpu_infos = []
mem = []
if_gpu_ok = False
if torch.cuda.is_available() or ngpu != 0:
for i in range(ngpu):
gpu_name = torch.cuda.get_device_name(i)
if any(
value in gpu_name.upper()
for value in [
"10",
"16",
"20",
"30",
"40",
"A2",
"A3",
"A4",
"P4",
"A50",
"500",
"A60",
"70",
"80",
"90",
"M4",
"T4",
"TITAN",
"L",
]
):
# A10#A100#V100#A40#P40#M40#K80#A4500
if_gpu_ok = True # 至少有一张能用的N卡
gpu_infos.append("%s\t%s" % (i, gpu_name))
mem.append(
int(
torch.cuda.get_device_properties(i).total_memory
/ 1024
/ 1024
/ 1024
+ 0.4
)
)
if if_gpu_ok and len(gpu_infos) > 0:
gpu_info = "\n".join(gpu_infos)
default_batch_size = min(mem) // 2
else:
gpu_info = i18n("很遗憾您这没有能用的显卡来支持您训练")
default_batch_size = 1
gpus = "-".join([i[0] for i in gpu_infos])
pretrained_sovits_name = "GPT_SoVITS/pretrained_models/s2G488k.pth"
pretrained_gpt_name = (
"GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"
)
def get_weights_names():
SoVITS_names = [pretrained_sovits_name]
for name in os.listdir(SoVITS_weight_root):
if name.endswith(".pth"):
SoVITS_names.append(name)
GPT_names = [pretrained_gpt_name]
for name in os.listdir(GPT_weight_root):
if name.endswith(".ckpt"):
GPT_names.append(name)
return SoVITS_names, GPT_names
SoVITS_weight_root = "SoVITS_weights"
GPT_weight_root = "GPT_weights"
os.makedirs(SoVITS_weight_root, exist_ok=True)
os.makedirs(GPT_weight_root, exist_ok=True)
SoVITS_names, GPT_names = get_weights_names()
def change_choices():
SoVITS_names, GPT_names = get_weights_names()
return {"choices": sorted(SoVITS_names), "__type__": "update"}, {
"choices": sorted(GPT_names),
"__type__": "update",
}
p_label = None
p_uvr5 = None
p_asr = None
p_tts_inference = None
system = platform.system()
def kill_process(pid):
if system == "Windows":
cmd = "taskkill /t /f /pid %s" % pid
else:
cmd = "kill -9 %s" % pid
print(cmd)
os.system(cmd) ###linux上杀了webui，可能还会没杀干净。。。
# os.kill(p_label.pid,19)#主进程#控制台进程#python子进程###不好使，连主进程的webui一起关了，辣鸡
def change_label(if_label, path_list):
global p_label
if if_label == True and p_label == None:
cmd = '"%s" tools/subfix_webui.py --load_list "%s" --webui_port %s' % (
python_exec,
path_list,
webui_port_subfix,
)
yield "打标工具WebUI已开启"
print(cmd)
p_label = Popen(cmd, shell=True)
elif if_label == False and p_label != None:
kill_process(p_label.pid)
p_label = None
yield "打标工具WebUI已关闭"
def change_uvr5(if_uvr5):
global p_uvr5
if if_uvr5 == True and p_uvr5 == None:
cmd = '"%s" tools/uvr5/webui.py "%s" %s %s' % (
python_exec,
infer_device,
is_half,
webui_port_uvr5,
)
yield "UVR5已开启"
print(cmd)
p_uvr5 = Popen(cmd, shell=True)
elif if_uvr5 == False and p_uvr5 != None:
kill_process(p_uvr5.pid)
p_uvr5 = None
yield "UVR5已关闭"
def change_tts_inference(
if_tts, bert_path, cnhubert_base_path, gpu_number, gpt_path, sovits_path
):
global p_tts_inference
if if_tts == True and p_tts_inference == None:
os.environ["gpt_path"] = (
gpt_path if "/" in gpt_path else "%s/%s" % (GPT_weight_root, gpt_path)
)
os.environ["sovits_path"] = (
sovits_path
if "/" in sovits_path
else "%s/%s" % (SoVITS_weight_root, sovits_path)
)
os.environ["cnhubert_base_path"] = cnhubert_base_path
os.environ["bert_path"] = bert_path
os.environ["_CUDA_VISIBLE_DEVICES"] = gpu_number
os.environ["is_half"] = str(is_half)
os.environ["infer_ttswebui"] = str(webui_port_infer_tts)
cmd = '"%s" GPT_SoVITS/inference_webui.py' % (python_exec)
yield "TTS推理进程已开启"
print(cmd)
p_tts_inference = Popen(cmd, shell=True)
elif if_tts == False and p_tts_inference != None:
kill_process(p_tts_inference.pid)
p_tts_inference = None
yield "TTS推理进程已关闭"
def open_asr(asr_inp_dir):
global p_asr
if p_asr == None:
cmd = '"%s" tools/damo_asr/cmd-asr.py "%s"' % (python_exec, asr_inp_dir)
yield "ASR任务开启：%s" % cmd, {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
print(cmd)
p_asr = Popen(cmd, shell=True)
p_asr.wait()
p_asr = None
yield "ASR任务完成", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
else:
yield "已有正在进行的ASR任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
def close_asr():
global p_asr
if p_asr != None:
kill_process(p_asr.pid)
p_asr = None
return (
"已终止ASR进程",
{"__type__": "update", "visible": True},
{"__type__": "update", "visible": False},
)
"""
button1Ba_open.click(open1Ba, [batch_size,total_epoch,exp_name,text_low_lr_rate,if_save_latest,if_save_every_weights,gpu_numbers1Ba,pretrained_s2G,pretrained_s2D], [info1Bb,button1Ba_open,button1Ba_close])
button1Ba_close.click(close1Ba, [], [info1Bb,button1Ba_open,button1Ba_close])
"""
p_train_SoVITS = None
def open1Ba(
batch_size,
total_epoch,
exp_name,
text_low_lr_rate,
if_save_latest,
if_save_every_weights,
save_every_epoch,
gpu_numbers1Ba,
pretrained_s2G,
pretrained_s2D,
):
global p_train_SoVITS
if p_train_SoVITS == None:
with open("GPT_SoVITS/configs/s2.json") as f:
data = f.read()
data = json.loads(data)
s2_dir = "%s/%s" % (exp_root, exp_name)
os.makedirs("%s/logs_s2" % (s2_dir), exist_ok=True)
data["train"]["batch_size"] = batch_size
data["train"]["epochs"] = total_epoch
data["train"]["text_low_lr_rate"] = text_low_lr_rate
data["train"]["pretrained_s2G"] = pretrained_s2G
data["train"]["pretrained_s2D"] = pretrained_s2D
data["train"]["if_save_latest"] = if_save_latest
data["train"]["if_save_every_weights"] = if_save_every_weights
data["train"]["save_every_epoch"] = save_every_epoch
data["train"]["gpu_numbers"] = gpu_numbers1Ba
data["data"]["exp_dir"] = data["s2_ckpt_dir"] = s2_dir
data["save_weight_dir"] = SoVITS_weight_root
data["name"] = exp_name
tmp_config_path = "TEMP/tmp_s2.json"
with open(tmp_config_path, "w") as f:
f.write(json.dumps(data))
cmd = '"%s" GPT_SoVITS/s2_train.py --config "%s"' % (
python_exec,
tmp_config_path,
)
yield "SoVITS训练开始：%s" % cmd, {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
print(cmd)
p_train_SoVITS = Popen(cmd, shell=True)
p_train_SoVITS.wait()
p_train_SoVITS = None
yield "SoVITS训练完成", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
else:
yield "已有正在进行的SoVITS训练任务，需先终止才能开启下一次任务", {
"__type__": "update",
"visible": False,
}, {"__type__": "update", "visible": True}
def close1Ba():
global p_train_SoVITS
if p_train_SoVITS != None:
kill_process(p_train_SoVITS.pid)
p_train_SoVITS = None
return (
"已终止SoVITS训练",
{"__type__": "update", "visible": True},
{"__type__": "update", "visible": False},
)
p_train_GPT = None
def open1Bb(
batch_size,
total_epoch,
exp_name,
if_save_latest,
if_save_every_weights,
save_every_epoch,
gpu_numbers,
pretrained_s1,
):
global p_train_GPT
if p_train_GPT == None:
with open("GPT_SoVITS/configs/s1longer.yaml") as f:
data = f.read()
data = yaml.load(data, Loader=yaml.FullLoader)
s1_dir = "%s/%s" % (exp_root, exp_name)
os.makedirs("%s/logs_s1" % (s1_dir), exist_ok=True)
data["train"]["batch_size"] = batch_size
data["train"]["epochs"] = total_epoch
data["pretrained_s1"] = pretrained_s1
data["train"]["save_every_n_epoch"] = save_every_epoch
data["train"]["if_save_every_weights"] = if_save_every_weights
data["train"]["if_save_latest"] = if_save_latest
data["train"]["half_weights_save_dir"] = GPT_weight_root
data["train"]["exp_name"] = exp_name
data["train_semantic_path"] = "%s/6-name2semantic.tsv" % s1_dir
data["train_phoneme_path"] = "%s/2-name2text.txt" % s1_dir
data["output_dir"] = "%s/logs_s1" % s1_dir
os.environ["_CUDA_VISIBLE_DEVICES"] = gpu_numbers.replace("-", ",")
os.environ["hz"] = "25hz"
tmp_config_path = "TEMP/tmp_s1.yaml"
with open(tmp_config_path, "w") as f:
f.write(yaml.dump(data, default_flow_style=False))
# cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" --train_semantic_path "%s/6-name2semantic.tsv" --train_phoneme_path "%s/2-name2text.txt" --output_dir "%s/logs_s1"'%(python_exec,tmp_config_path,s1_dir,s1_dir,s1_dir)
cmd = '"%s" GPT_SoVITS/s1_train.py --config_file "%s" ' % (
python_exec,
tmp_config_path,
)
yield "GPT训练开始：%s" % cmd, {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
print(cmd)
p_train_GPT = Popen(cmd, shell=True)
p_train_GPT.wait()
p_train_GPT = None
yield "GPT训练完成", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
else:
yield "已有正在进行的GPT训练任务，需先终止才能开启下一次任务", {
"__type__": "update",
"visible": False,
}, {"__type__": "update", "visible": True}
def close1Bb():
global p_train_GPT
if p_train_GPT != None:
kill_process(p_train_GPT.pid)
p_train_GPT = None
return (
"已终止GPT训练",
{"__type__": "update", "visible": True},
{"__type__": "update", "visible": False},
)
ps_slice = []
def open_slice(
inp,
opt_root,
threshold,
min_length,
min_interval,
hop_size,
max_sil_kept,
_max,
alpha,
n_parts,
):
global ps_slice
if os.path.exists(inp) == False:
yield "输入路径不存在", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
return
if os.path.isfile(inp):
n_parts = 1
elif os.path.isdir(inp):
pass
else:
yield "输入路径存在但既不是文件也不是文件夹", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
return
if ps_slice == []:
for i_part in range(n_parts):
cmd = (
'"%s" tools/slice_audio.py "%s" "%s" %s %s %s %s %s %s %s %s %s'
""
% (
python_exec,
inp,
opt_root,
threshold,
min_length,
min_interval,
hop_size,
max_sil_kept,
_max,
alpha,
i_part,
n_parts,
)
)
print(cmd)
p = Popen(cmd, shell=True)
ps_slice.append(p)
yield "切割执行中", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
for p in ps_slice:
p.wait()
ps_slice = []
yield "切割结束", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
else:
yield "已有正在进行的切割任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
def close_slice():
global ps_slice
if ps_slice != []:
for p_slice in ps_slice:
try:
kill_process(p_slice.pid)
except:
traceback.print_exc()
ps_slice = []
return (
"已终止所有切割进程",
{"__type__": "update", "visible": True},
{"__type__": "update", "visible": False},
)
"""
inp_text= os.environ.get("inp_text")
inp_wav_dir= os.environ.get("inp_wav_dir")
exp_name= os.environ.get("exp_name")
i_part= os.environ.get("i_part")
all_parts= os.environ.get("all_parts")
os.environ["CUDA_VISIBLE_DEVICES"]= os.environ.get("_CUDA_VISIBLE_DEVICES")
opt_dir= os.environ.get("opt_dir")#"/data/docker/liujing04/gpt-vits/fine_tune_dataset/%s"%exp_name
bert_pretrained_dir= os.environ.get("bert_pretrained_dir")#"/data/docker/liujing04/bert-vits2/Bert-VITS2-master20231106/bert/chinese-roberta-wwm-ext-large"
"""
ps1a = []
def open1a(inp_text, inp_wav_dir, exp_name, gpu_numbers, bert_pretrained_dir):
global ps1a
if ps1a == []:
config = {
"inp_text": inp_text,
"inp_wav_dir": inp_wav_dir,
"exp_name": exp_name,
"opt_dir": "%s/%s" % (exp_root, exp_name),
"bert_pretrained_dir": bert_pretrained_dir,
}
gpu_names = gpu_numbers.split("-")
all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
"i_part": str(i_part),
"all_parts": str(all_parts),
"_CUDA_VISIBLE_DEVICES": gpu_names[i_part],
"is_half": str(is_half),
}
)
os.environ.update(config)
cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py' % python_exec
print(cmd)
p = Popen(cmd, shell=True)
ps1a.append(p)
yield "文本进程执行中", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
for p in ps1a:
p.wait()
ps1a = []
yield "文本进程结束", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
else:
yield "已有正在进行的文本任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
def close1a():
global ps1a
if ps1a != []:
for p1a in ps1a:
try:
kill_process(p1a.pid)
except:
traceback.print_exc()
ps1a = []
return (
"已终止所有1a进程",
{"__type__": "update", "visible": True},
{"__type__": "update", "visible": False},
)
"""
inp_text= os.environ.get("inp_text")
inp_wav_dir= os.environ.get("inp_wav_dir")
exp_name= os.environ.get("exp_name")
i_part= os.environ.get("i_part")
all_parts= os.environ.get("all_parts")
os.environ["CUDA_VISIBLE_DEVICES"]= os.environ.get("_CUDA_VISIBLE_DEVICES")
opt_dir= os.environ.get("opt_dir")
cnhubert.cnhubert_base_path= os.environ.get("cnhubert_base_dir")
"""
ps1b = []
def open1b(inp_text, inp_wav_dir, exp_name, gpu_numbers, ssl_pretrained_dir):
global ps1b
if ps1b == []:
config = {
"inp_text": inp_text,
"inp_wav_dir": inp_wav_dir,
"exp_name": exp_name,
"opt_dir": "%s/%s" % (exp_root, exp_name),
"cnhubert_base_dir": ssl_pretrained_dir,
"is_half": str(is_half),
}
gpu_names = gpu_numbers.split("-")
all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
"i_part": str(i_part),
"all_parts": str(all_parts),
"_CUDA_VISIBLE_DEVICES": gpu_names[i_part],
}
)
os.environ.update(config)
cmd = (
'"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py' % python_exec
)
print(cmd)
p = Popen(cmd, shell=True)
ps1b.append(p)
yield "SSL提取进程执行中", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
for p in ps1b:
p.wait()
ps1b = []
yield "SSL提取进程结束", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
else:
yield "已有正在进行的SSL提取任务，需先终止才能开启下一次任务", {
"__type__": "update",
"visible": False,
}, {"__type__": "update", "visible": True}
def close1b():
global ps1b
if ps1b != []:
for p1b in ps1b:
try:
kill_process(p1b.pid)
except:
traceback.print_exc()
ps1b = []
return (
"已终止所有1b进程",
{"__type__": "update", "visible": True},
{"__type__": "update", "visible": False},
)
"""
inp_text= os.environ.get("inp_text")
exp_name= os.environ.get("exp_name")
i_part= os.environ.get("i_part")
all_parts= os.environ.get("all_parts")
os.environ["CUDA_VISIBLE_DEVICES"]= os.environ.get("_CUDA_VISIBLE_DEVICES")
opt_dir= os.environ.get("opt_dir")
pretrained_s2G= os.environ.get("pretrained_s2G")
"""
ps1c = []
def open1c(inp_text, exp_name, gpu_numbers, pretrained_s2G_path):
global ps1c
if ps1c == []:
config = {
"inp_text": inp_text,
"exp_name": exp_name,
"opt_dir": "%s/%s" % (exp_root, exp_name),
"pretrained_s2G": pretrained_s2G_path,
"s2config_path": "GPT_SoVITS/configs/s2.json",
"is_half": str(is_half),
}
gpu_names = gpu_numbers.split("-")
all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
"i_part": str(i_part),
"all_parts": str(all_parts),
"_CUDA_VISIBLE_DEVICES": gpu_names[i_part],
}
)
os.environ.update(config)
cmd = '"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py' % python_exec
print(cmd)
p = Popen(cmd, shell=True)
ps1c.append(p)
yield "语义token提取进程执行中", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
for p in ps1c:
p.wait()
ps1c = []
yield "语义token提取进程结束", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
else:
yield "已有正在进行的语义token提取任务，需先终止才能开启下一次任务", {
"__type__": "update",
"visible": False,
}, {"__type__": "update", "visible": True}
def close1c():
global ps1c
if ps1c != []:
for p1c in ps1c:
try:
kill_process(p1c.pid)
except:
traceback.print_exc()
ps1c = []
return (
"已终止所有语义token进程",
{"__type__": "update", "visible": True},
{"__type__": "update", "visible": False},
)
#####inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,cnhubert_base_dir,pretrained_s2G
ps1abc = []
def open1abc(
inp_text,
inp_wav_dir,
exp_name,
gpu_numbers1a,
gpu_numbers1Ba,
gpu_numbers1c,
bert_pretrained_dir,
ssl_pretrained_dir,
pretrained_s2G_path,
):
global ps1abc
if ps1abc == []:
opt_dir = "%s/%s" % (exp_root, exp_name)
try:
#############################1a
path_text = "%s/2-name2text.txt" % opt_dir
if os.path.exists(path_text) == False:
config = {
"inp_text": inp_text,
"inp_wav_dir": inp_wav_dir,
"exp_name": exp_name,
"opt_dir": opt_dir,
"bert_pretrained_dir": bert_pretrained_dir,
"is_half": str(is_half),
}
gpu_names = gpu_numbers1a.split("-")
all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
"i_part": str(i_part),
"all_parts": str(all_parts),
"_CUDA_VISIBLE_DEVICES": gpu_names[i_part],
}
)
os.environ.update(config)
cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py' % python_exec
print(cmd)
p = Popen(cmd, shell=True)
ps1abc.append(p)
yield "进度：1a-ing", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
for p in ps1abc:
p.wait()
opt = []
for i_part in range(
all_parts
): # txt_path="%s/2-name2text-%s.txt"%(opt_dir,i_part)
txt_path = "%s/2-name2text-%s.txt" % (opt_dir, i_part)
with open(txt_path, "r", encoding="utf8") as f:
opt += f.read().strip("\n").split("\n")
os.remove(txt_path)
with open(path_text, "w", encoding="utf8") as f:
f.write("\n".join(opt) + "\n")
yield "进度：1a-done", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
ps1abc = []
#############################1b
config = {
"inp_text": inp_text,
"inp_wav_dir": inp_wav_dir,
"exp_name": exp_name,
"opt_dir": opt_dir,
"cnhubert_base_dir": ssl_pretrained_dir,
}
gpu_names = gpu_numbers1Ba.split("-")
all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
"i_part": str(i_part),
"all_parts": str(all_parts),
"_CUDA_VISIBLE_DEVICES": gpu_names[i_part],
}
)
os.environ.update(config)
cmd = (
'"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py'
% python_exec
)
print(cmd)
p = Popen(cmd, shell=True)
ps1abc.append(p)
yield "进度：1a-done, 1b-ing", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
for p in ps1abc:
p.wait()
yield "进度：1a1b-done", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
ps1abc = []
#############################1c
path_semantic = "%s/6-name2semantic.tsv" % opt_dir
if os.path.exists(path_semantic) == False:
config = {
"inp_text": inp_text,
"exp_name": exp_name,
"opt_dir": opt_dir,
"pretrained_s2G": pretrained_s2G_path,
"s2config_path": "GPT_SoVITS/configs/s2.json",
}
gpu_names = gpu_numbers1c.split("-")
all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
"i_part": str(i_part),
"all_parts": str(all_parts),
"_CUDA_VISIBLE_DEVICES": gpu_names[i_part],
}
)
os.environ.update(config)
cmd = (
'"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py'
% python_exec
)
print(cmd)
p = Popen(cmd, shell=True)
ps1abc.append(p)
yield "进度：1a1b-done, 1cing", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
for p in ps1abc:
p.wait()
opt = ["item_name semantic_audio"]
for i_part in range(all_parts):
semantic_path = "%s/6-name2semantic-%s.tsv" % (opt_dir, i_part)
with open(semantic_path, "r", encoding="utf8") as f:
opt += f.read().strip("\n").split("\n")
os.remove(semantic_path)
with open(path_semantic, "w", encoding="utf8") as f:
f.write("\n".join(opt) + "\n")
yield "进度：all-done", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
ps1abc = []
yield "一键三连进程结束", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
except:
traceback.print_exc()
close1abc()
yield "一键三连中途报错", {"__type__": "update", "visible": True}, {
"__type__": "update",
"visible": False,
}
else:
yield "已有正在进行的一键三连任务，需先终止才能开启下一次任务", {"__type__": "update", "visible": False}, {
"__type__": "update",
"visible": True,
}
def close1abc():
global ps1abc
if ps1abc != []:
for p1abc in ps1abc:
try:
kill_process(p1abc.pid)
except:
traceback.print_exc()
ps1abc = []
return (
"已终止所有一键三连进程",
{"__type__": "update", "visible": True},
{"__type__": "update", "visible": False},
)
with gr.Blocks(title="GPT-SoVITS WebUI") as app:
gr.Markdown(
value="本软件以MIT协议开源, 作者不对软件具备任何控制力, 使用软件者、传播软件导出的声音者自负全责. <br>如不认可该条款, 则不能使用或引用软件包内任何代码和文件. 详见根目录<b>LICENSE</b>."
)
with gr.Tabs():
with gr.TabItem("0-前置数据集获取工具"): # 提前随机切片防止uvr5爆内存->uvr5->slicer->asr->打标
gr.Markdown(value="0a-UVR5人声伴奏分离&去混响去延迟工具")
with gr.Row():
if_uvr5 = gr.Checkbox(label="是否开启UVR5-WebUI", show_label=True)
uvr5_info = gr.Textbox(label="UVR5进程输出信息")
gr.Markdown(value="0b-语音切分工具")
with gr.Row():
with gr.Row():
slice_inp_path = gr.Textbox(label="音频自动切分输入路径，可文件可文件夹", value="")
slice_opt_root = gr.Textbox(
label="切分后的子音频的输出根目录", value="output/slicer_opt"
)
threshold = gr.Textbox(
label="threshold:音量小于这个值视作静音的备选切割点", value="-34"
)
min_length = gr.Textbox(
label="min_length:每段最小多长，如果第一段太短一直和后面段连起来直到超过这个值", value="4000"
)
min_interval = gr.Textbox(label="min_interval:最短切割间隔", value="300")
hop_size = gr.Textbox(
label="hop_size:怎么算音量曲线，越小精度越大计算量越高（不是精度越大效果越好）", value="10"
)
max_sil_kept = gr.Textbox(
label="max_sil_kept:切完后静音最多留多长", value="500"
)
with gr.Row():
open_slicer_button = gr.Button(
"开启语音切割", variant="primary", visible=True
)
close_slicer_button = gr.Button(
"终止语音切割", variant="primary", visible=False
)
_max = gr.Slider(
minimum=0,
maximum=1,
step=0.05,
label="max:归一化后最大值多少",
value=0.9,
interactive=True,
)
alpha = gr.Slider(
minimum=0,
maximum=1,
step=0.05,
label="alpha_mix:混多少比例归一化后音频进来",
value=0.25,
interactive=True,
)
n_process = gr.Slider(
minimum=1,
maximum=n_cpu,
step=1,
label="切割使用的进程数",
value=4,
interactive=True,
)
slicer_info = gr.Textbox(label="语音切割进程输出信息")
gr.Markdown(value="0c-中文批量离线ASR工具")
with gr.Row():
open_asr_button = gr.Button(
"开启离线批量ASR", variant="primary", visible=True
)
close_asr_button = gr.Button(
"终止ASR进程", variant="primary", visible=False
)
asr_inp_dir = gr.Textbox(
label="批量ASR(中文only)输入文件夹路径",
value="D:\\RVC1006\\GPT-SoVITS\\raw\\xxx",
interactive=True,
)
asr_info = gr.Textbox(label="ASR进程输出信息")
gr.Markdown(value="0d-语音文本校对标注工具")
with gr.Row():
if_label = gr.Checkbox(label="是否开启打标WebUI", show_label=True)
path_list = gr.Textbox(
label="打标数据标注文件路径",
value="D:\\RVC1006\\GPT-SoVITS\\raw\\xxx.list",
interactive=True,
)
label_info = gr.Textbox(label="打标工具进程输出信息")
if_label.change(change_label, [if_label, path_list], [label_info])
if_uvr5.change(change_uvr5, [if_uvr5], [uvr5_info])
open_asr_button.click(
open_asr, [asr_inp_dir], [asr_info, open_asr_button, close_asr_button]
)
close_asr_button.click(
close_asr, [], [asr_info, open_asr_button, close_asr_button]
)
open_slicer_button.click(
open_slice,
[
slice_inp_path,
slice_opt_root,
threshold,
min_length,
min_interval,
hop_size,
max_sil_kept,
_max,
alpha,
n_process,