From b28194ea7612215f4cca8976fe13311edc26d4f6 Mon Sep 17 00:00:00 2001
From: Blaise <133521603+blaise-tk@users.noreply.github.com>
Date: Tue, 16 Jan 2024 17:01:03 +0100
Subject: [PATCH] Code refactor
---
webui.py | 1319 +++++++++++++++++++++++++++++++++++++++---------------
1 file changed, 964 insertions(+), 355 deletions(-)
diff --git a/webui.py b/webui.py
index dbccba7..703c597 100644
--- a/webui.py
+++ b/webui.py
@@ -1,35 +1,48 @@
-import json,yaml,warnings,torch
+import json, yaml, warnings, torch
import platform
warnings.filterwarnings("ignore")
torch.manual_seed(233333)
-import os,pdb,sys
+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
+
+site_packages_root = "%s/runtime/Lib/site-packages" % now_dir
for path in site.getsitepackages():
- if("site-packages"in path):site_packages_root=path
+ 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))
+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 shutil
-import pdb
import gradio as gr
from subprocess import Popen
-import signal
-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 config import (
+ python_exec,
+ infer_device,
+ is_half,
+ exp_root,
+ webui_port_main,
+ webui_port_infer_tts,
+ webui_port_uvr5,
+ webui_port_subfix,
+)
from i18n.i18n import I18nAuto
+
i18n = I18nAuto()
-from scipy.io import wavfile
-from tools.my_utils import load_audio
from multiprocessing import cpu_count
-n_cpu=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()
@@ -40,11 +53,42 @@ 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"]):
+ 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))
+ 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
@@ -53,230 +97,395 @@ else:
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"
+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)
+ 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()
+ 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"}
+ 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()
-p_label=None
-p_uvr5=None
-p_asr=None
-p_tts_inference=None
-system=platform.system()
def kill_process(pid):
- if(system=="Windows"):
+ if system == "Windows":
cmd = "taskkill /t /f /pid %s" % pid
else:
- cmd = "kill -9 %s"%pid
+ cmd = "kill -9 %s" % pid
print(cmd)
- os.system(cmd)###linux上杀了webui，可能还会没杀干净。。。
+ 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):
+
+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)
+ 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):
+ elif if_label == False and p_label != None:
kill_process(p_label.pid)
- p_label=None
+ 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)
+ 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):
+ elif if_uvr5 == False and p_uvr5 != None:
kill_process(p_uvr5.pid)
- p_uvr5=None
+ 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):
+
+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)
+ 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):
+ elif if_tts == False and p_tts_inference != None:
kill_process(p_tts_inference.pid)
- p_tts_inference=None
+ 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}
+ 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}
+ 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}
+ 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):
+ 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}
+ 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):
+"""
+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}
+ 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}
+ 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}
+ 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):
+ 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_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):
+
+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))
+ 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}
+ 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}
+ 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}
+ 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):
+ 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}
+ p_train_GPT = None
+ return (
+ "已终止GPT训练",
+ {"__type__": "update", "visible": True},
+ {"__type__": "update", "visible": False},
+ )
+
+
+ps_slice = []
-ps_slice=[]
-def open_slice(inp,opt_root,threshold,min_length,min_interval,hop_size,max_sil_kept,_max,alpha,n_parts):
+
+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}
+ 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
+ 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}
+ 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 == []):
+ 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)
+ 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}
+ 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}
+ 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}
+ 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 != []):
+ 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}
+ 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")
@@ -285,53 +494,71 @@ 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):
+"""
+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,
+ 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)
+ 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)
+ "is_half": str(is_half),
}
)
os.environ.update(config)
- cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py'%python_exec
+ 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}
+ 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}
+ 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}
+ 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 != []):
+ 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}
-'''
+ 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")
@@ -340,21 +567,23 @@ 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):
+"""
+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)
+ 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)
+ gpu_names = gpu_numbers.split("-")
+ all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
@@ -364,29 +593,47 @@ def open1b(inp_text,inp_wav_dir,exp_name,gpu_numbers,ssl_pretrained_dir):
}
)
os.environ.update(config)
- cmd = '"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py'%python_exec
+ 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}
+ 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}
+ 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}
+ 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 != []):
+ 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}
-'''
+ 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")
@@ -394,21 +641,23 @@ 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):
+"""
+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)
+ 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)
+ gpu_names = gpu_numbers.split("-")
+ all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
@@ -418,48 +667,76 @@ def open1c(inp_text,exp_name,gpu_numbers,pretrained_s2G_path):
}
)
os.environ.update(config)
- cmd = '"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py'%python_exec
+ 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}
+ 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}
+ 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}
+ 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 != []):
+ 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}
+ 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):
+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)
+ 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)
+ 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)
+ gpu_names = gpu_numbers1a.split("-")
+ all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
@@ -469,34 +746,43 @@ def open1abc(inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numb
}
)
os.environ.update(config)
- cmd = '"%s" GPT_SoVITS/prepare_datasets/1-get-text.py'%python_exec
+ 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()
+ 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)
+ 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:
+ 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:
+ 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=[]
+ 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,
+ 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)
+ gpu_names = gpu_numbers1Ba.split("-")
+ all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
@@ -506,26 +792,36 @@ def open1abc(inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numb
}
)
os.environ.update(config)
- cmd = '"%s" GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py'%python_exec
+ 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=[]
+ 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",
+ 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)
+ gpu_names = gpu_numbers1c.split("-")
+ all_parts = len(gpu_names)
for i_part in range(all_parts):
config.update(
{
@@ -535,74 +831,137 @@ def open1abc(inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numb
}
)
os.environ.update(config)
- cmd = '"%s" GPT_SoVITS/prepare_datasets/3-get-semantic.py'%python_exec
+ 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()
+ 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:
+ 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:
+ 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}
+ 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}
+ 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}
+ 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}
+ 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 != []):
+ 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}
+ 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.
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LICENSE."
+ 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.
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LICENSE."
)
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
+ 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)
+ 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")
+ 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)
+ 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)
+ 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",
@@ -611,115 +970,365 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
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)
+ 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_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], [slicer_info,open_slicer_button,close_slicer_button])
- close_slicer_button.click(close_slice, [], [slicer_info,open_slicer_button,close_slicer_button])
+ 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,
+ ],
+ [slicer_info, open_slicer_button, close_slicer_button],
+ )
+ close_slicer_button.click(
+ close_slice, [], [slicer_info, open_slicer_button, close_slicer_button]
+ )
with gr.TabItem("1-GPT-SoVITS-TTS"):
with gr.Row():
exp_name = gr.Textbox(label="*实验/模型名", value="xxx", interactive=True)
- gpu_info = gr.Textbox(label="显卡信息", value=gpu_info, visible=True, interactive=False)
- pretrained_s2G = gr.Textbox(label="预训练的SoVITS-G模型路径", value="GPT_SoVITS/pretrained_models/s2G488k.pth", interactive=True)
- pretrained_s2D = gr.Textbox(label="预训练的SoVITS-D模型路径", value="GPT_SoVITS/pretrained_models/s2D488k.pth", interactive=True)
- pretrained_s1 = gr.Textbox(label="预训练的GPT模型路径", value="GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt", interactive=True)
+ gpu_info = gr.Textbox(
+ label="显卡信息", value=gpu_info, visible=True, interactive=False
+ )
+ pretrained_s2G = gr.Textbox(
+ label="预训练的SoVITS-G模型路径",
+ value="GPT_SoVITS/pretrained_models/s2G488k.pth",
+ interactive=True,
+ )
+ pretrained_s2D = gr.Textbox(
+ label="预训练的SoVITS-D模型路径",
+ value="GPT_SoVITS/pretrained_models/s2D488k.pth",
+ interactive=True,
+ )
+ pretrained_s1 = gr.Textbox(
+ label="预训练的GPT模型路径",
+ value="GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt",
+ interactive=True,
+ )
with gr.TabItem("1A-训练集格式化工具"):
gr.Markdown(value="输出logs/实验名目录下应有23456开头的文件和文件夹")
with gr.Row():
- inp_text = gr.Textbox(label="*文本标注文件",value=r"D:\RVC1006\GPT-SoVITS\raw\xxx.list",interactive=True)
- inp_wav_dir = gr.Textbox(label="*训练集音频文件目录",value=r"D:\RVC1006\GPT-SoVITS\raw\xxx",interactive=True)
+ inp_text = gr.Textbox(
+ label="*文本标注文件",
+ value=r"D:\RVC1006\GPT-SoVITS\raw\xxx.list",
+ interactive=True,
+ )
+ inp_wav_dir = gr.Textbox(
+ label="*训练集音频文件目录",
+ value=r"D:\RVC1006\GPT-SoVITS\raw\xxx",
+ interactive=True,
+ )
gr.Markdown(value="1Aa-文本内容")
with gr.Row():
- gpu_numbers1a = gr.Textbox(label="GPU卡号以-分割，每个卡号一个进程",value="%s-%s"%(gpus,gpus),interactive=True)
- bert_pretrained_dir = gr.Textbox(label="预训练的中文BERT模型路径",value="GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large",interactive=False)
- button1a_open = gr.Button("开启文本获取", variant="primary",visible=True)
- button1a_close = gr.Button("终止文本获取进程", variant="primary",visible=False)
- info1a=gr.Textbox(label="文本进程输出信息")
+ gpu_numbers1a = gr.Textbox(
+ label="GPU卡号以-分割，每个卡号一个进程",
+ value="%s-%s" % (gpus, gpus),
+ interactive=True,
+ )
+ bert_pretrained_dir = gr.Textbox(
+ label="预训练的中文BERT模型路径",
+ value="GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large",
+ interactive=False,
+ )
+ button1a_open = gr.Button("开启文本获取", variant="primary", visible=True)
+ button1a_close = gr.Button(
+ "终止文本获取进程", variant="primary", visible=False
+ )
+ info1a = gr.Textbox(label="文本进程输出信息")
gr.Markdown(value="1Ab-SSL自监督特征提取")
with gr.Row():
- gpu_numbers1Ba = gr.Textbox(label="GPU卡号以-分割，每个卡号一个进程",value="%s-%s"%(gpus,gpus),interactive=True)
- cnhubert_base_dir = gr.Textbox(label="预训练的SSL模型路径",value="GPT_SoVITS/pretrained_models/chinese-hubert-base",interactive=False)
- button1b_open = gr.Button("开启SSL提取", variant="primary",visible=True)
- button1b_close = gr.Button("终止SSL提取进程", variant="primary",visible=False)
- info1b=gr.Textbox(label="SSL进程输出信息")
+ gpu_numbers1Ba = gr.Textbox(
+ label="GPU卡号以-分割，每个卡号一个进程",
+ value="%s-%s" % (gpus, gpus),
+ interactive=True,
+ )
+ cnhubert_base_dir = gr.Textbox(
+ label="预训练的SSL模型路径",
+ value="GPT_SoVITS/pretrained_models/chinese-hubert-base",
+ interactive=False,
+ )
+ button1b_open = gr.Button(
+ "开启SSL提取", variant="primary", visible=True
+ )
+ button1b_close = gr.Button(
+ "终止SSL提取进程", variant="primary", visible=False
+ )
+ info1b = gr.Textbox(label="SSL进程输出信息")
gr.Markdown(value="1Ac-语义token提取")
with gr.Row():
- gpu_numbers1c = gr.Textbox(label="GPU卡号以-分割，每个卡号一个进程",value="%s-%s"%(gpus,gpus),interactive=True)
- button1c_open = gr.Button("开启语义token提取", variant="primary",visible=True)
- button1c_close = gr.Button("终止语义token提取进程", variant="primary",visible=False)
- info1c=gr.Textbox(label="语义token提取进程输出信息")
+ gpu_numbers1c = gr.Textbox(
+ label="GPU卡号以-分割，每个卡号一个进程",
+ value="%s-%s" % (gpus, gpus),
+ interactive=True,
+ )
+ button1c_open = gr.Button(
+ "开启语义token提取", variant="primary", visible=True
+ )
+ button1c_close = gr.Button(
+ "终止语义token提取进程", variant="primary", visible=False
+ )
+ info1c = gr.Textbox(label="语义token提取进程输出信息")
gr.Markdown(value="1Aabc-训练集格式化一键三连")
with gr.Row():
- button1abc_open = gr.Button("开启一键三连", variant="primary",visible=True)
- button1abc_close = gr.Button("终止一键三连", variant="primary",visible=False)
- info1abc=gr.Textbox(label="一键三连进程输出信息")
- button1a_open.click(open1a, [inp_text,inp_wav_dir,exp_name,gpu_numbers1a,bert_pretrained_dir], [info1a,button1a_open,button1a_close])
- button1a_close.click(close1a, [], [info1a,button1a_open,button1a_close])
- button1b_open.click(open1b, [inp_text,inp_wav_dir,exp_name,gpu_numbers1Ba,cnhubert_base_dir], [info1b,button1b_open,button1b_close])
- button1b_close.click(close1b, [], [info1b,button1b_open,button1b_close])
- button1c_open.click(open1c, [inp_text,exp_name,gpu_numbers1c,pretrained_s2G], [info1c,button1c_open,button1c_close])
- button1c_close.click(close1c, [], [info1c,button1c_open,button1c_close])
- button1abc_open.click(open1abc, [inp_text,inp_wav_dir,exp_name,gpu_numbers1a,gpu_numbers1Ba,gpu_numbers1c,bert_pretrained_dir,cnhubert_base_dir,pretrained_s2G], [info1abc,button1abc_open,button1abc_close])
- button1abc_close.click(close1abc, [], [info1abc,button1abc_open,button1abc_close])
+ button1abc_open = gr.Button(
+ "开启一键三连", variant="primary", visible=True
+ )
+ button1abc_close = gr.Button(
+ "终止一键三连", variant="primary", visible=False
+ )
+ info1abc = gr.Textbox(label="一键三连进程输出信息")
+ button1a_open.click(
+ open1a,
+ [inp_text, inp_wav_dir, exp_name, gpu_numbers1a, bert_pretrained_dir],
+ [info1a, button1a_open, button1a_close],
+ )
+ button1a_close.click(close1a, [], [info1a, button1a_open, button1a_close])
+ button1b_open.click(
+ open1b,
+ [inp_text, inp_wav_dir, exp_name, gpu_numbers1Ba, cnhubert_base_dir],
+ [info1b, button1b_open, button1b_close],
+ )
+ button1b_close.click(close1b, [], [info1b, button1b_open, button1b_close])
+ button1c_open.click(
+ open1c,
+ [inp_text, exp_name, gpu_numbers1c, pretrained_s2G],
+ [info1c, button1c_open, button1c_close],
+ )
+ button1c_close.click(close1c, [], [info1c, button1c_open, button1c_close])
+ button1abc_open.click(
+ open1abc,
+ [
+ inp_text,
+ inp_wav_dir,
+ exp_name,
+ gpu_numbers1a,
+ gpu_numbers1Ba,
+ gpu_numbers1c,
+ bert_pretrained_dir,
+ cnhubert_base_dir,
+ pretrained_s2G,
+ ],
+ [info1abc, button1abc_open, button1abc_close],
+ )
+ button1abc_close.click(
+ close1abc, [], [info1abc, button1abc_open, button1abc_close]
+ )
with gr.TabItem("1B-微调训练"):
gr.Markdown(value="1Ba-SoVITS训练。用于分享的模型文件输出在SoVITS_weights下。")
with gr.Row():
- batch_size = gr.Slider(minimum=1,maximum=40,step=1,label=i18n("每张显卡的batch_size"),value=default_batch_size,interactive=True)
- total_epoch = gr.Slider(minimum=1,maximum=20,step=1,label=i18n("总训练轮数total_epoch，不建议太高"),value=8,interactive=True)
- text_low_lr_rate = gr.Slider(minimum=0.2,maximum=0.6,step=0.05,label="文本模块学习率权重",value=0.4,interactive=True)
- save_every_epoch = gr.Slider(minimum=1,maximum=50,step=1,label=i18n("保存频率save_every_epoch"),value=4,interactive=True)
- if_save_latest = gr.Checkbox(label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"), value=True, interactive=True, show_label=True)
- if_save_every_weights = gr.Checkbox(label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"), value=True, interactive=True, show_label=True)
- gpu_numbers1Ba = gr.Textbox(label="GPU卡号以-分割，每个卡号一个进程", value="%s" % (gpus), interactive=True)
+ batch_size = gr.Slider(
+ minimum=1,
+ maximum=40,
+ step=1,
+ label=i18n("每张显卡的batch_size"),
+ value=default_batch_size,
+ interactive=True,
+ )
+ total_epoch = gr.Slider(
+ minimum=1,
+ maximum=20,
+ step=1,
+ label=i18n("总训练轮数total_epoch，不建议太高"),
+ value=8,
+ interactive=True,
+ )
+ text_low_lr_rate = gr.Slider(
+ minimum=0.2,
+ maximum=0.6,
+ step=0.05,
+ label="文本模块学习率权重",
+ value=0.4,
+ interactive=True,
+ )
+ save_every_epoch = gr.Slider(
+ minimum=1,
+ maximum=50,
+ step=1,
+ label=i18n("保存频率save_every_epoch"),
+ value=4,
+ interactive=True,
+ )
+ if_save_latest = gr.Checkbox(
+ label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"),
+ value=True,
+ interactive=True,
+ show_label=True,
+ )
+ if_save_every_weights = gr.Checkbox(
+ label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"),
+ value=True,
+ interactive=True,
+ show_label=True,
+ )
+ gpu_numbers1Ba = gr.Textbox(
+ label="GPU卡号以-分割，每个卡号一个进程",
+ value="%s" % (gpus),
+ interactive=True,
+ )
with gr.Row():
- button1Ba_open = gr.Button("开启SoVITS训练", variant="primary",visible=True)
- button1Ba_close = gr.Button("终止SoVITS训练", variant="primary",visible=False)
- info1Ba=gr.Textbox(label="SoVITS训练进程输出信息")
+ button1Ba_open = gr.Button(
+ "开启SoVITS训练", variant="primary", visible=True
+ )
+ button1Ba_close = gr.Button(
+ "终止SoVITS训练", variant="primary", visible=False
+ )
+ info1Ba = gr.Textbox(label="SoVITS训练进程输出信息")
gr.Markdown(value="1Bb-GPT训练。用于分享的模型文件输出在GPT_weights下。")
with gr.Row():
- batch_size1Bb = gr.Slider(minimum=1,maximum=40,step=1,label=i18n("每张显卡的batch_size"),value=default_batch_size,interactive=True)
- total_epoch1Bb = gr.Slider(minimum=2,maximum=100,step=1,label=i18n("总训练轮数total_epoch"),value=15,interactive=True)
- if_save_latest1Bb = gr.Checkbox(label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"), value=True, interactive=True, show_label=True)
- if_save_every_weights1Bb = gr.Checkbox(label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"), value=True, interactive=True, show_label=True)
- save_every_epoch1Bb = gr.Slider(minimum=1,maximum=50,step=1,label=i18n("保存频率save_every_epoch"),value=5,interactive=True)
- gpu_numbers1Bb = gr.Textbox(label="GPU卡号以-分割，每个卡号一个进程", value="%s" % (gpus), interactive=True)
+ batch_size1Bb = gr.Slider(
+ minimum=1,
+ maximum=40,
+ step=1,
+ label=i18n("每张显卡的batch_size"),
+ value=default_batch_size,
+ interactive=True,
+ )
+ total_epoch1Bb = gr.Slider(
+ minimum=2,
+ maximum=100,
+ step=1,
+ label=i18n("总训练轮数total_epoch"),
+ value=15,
+ interactive=True,
+ )
+ if_save_latest1Bb = gr.Checkbox(
+ label=i18n("是否仅保存最新的ckpt文件以节省硬盘空间"),
+ value=True,
+ interactive=True,
+ show_label=True,
+ )
+ if_save_every_weights1Bb = gr.Checkbox(
+ label=i18n("是否在每次保存时间点将最终小模型保存至weights文件夹"),
+ value=True,
+ interactive=True,
+ show_label=True,
+ )
+ save_every_epoch1Bb = gr.Slider(
+ minimum=1,
+ maximum=50,
+ step=1,
+ label=i18n("保存频率save_every_epoch"),
+ value=5,
+ interactive=True,
+ )
+ gpu_numbers1Bb = gr.Textbox(
+ label="GPU卡号以-分割，每个卡号一个进程",
+ value="%s" % (gpus),
+ interactive=True,
+ )
with gr.Row():
- button1Bb_open = gr.Button("开启GPT训练", variant="primary",visible=True)
- button1Bb_close = gr.Button("终止GPT训练", variant="primary",visible=False)
- info1Bb=gr.Textbox(label="GPT训练进程输出信息")
- button1Ba_open.click(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], [info1Ba,button1Ba_open,button1Ba_close])
- button1Ba_close.click(close1Ba, [], [info1Ba,button1Ba_open,button1Ba_close])
- button1Bb_open.click(open1Bb, [batch_size1Bb,total_epoch1Bb,exp_name,if_save_latest1Bb,if_save_every_weights1Bb,save_every_epoch1Bb,gpu_numbers1Bb,pretrained_s1], [info1Bb,button1Bb_open,button1Bb_close])
- button1Bb_close.click(close1Bb, [], [info1Bb,button1Bb_open,button1Bb_close])
+ button1Bb_open = gr.Button(
+ "开启GPT训练", variant="primary", visible=True
+ )
+ button1Bb_close = gr.Button(
+ "终止GPT训练", variant="primary", visible=False
+ )
+ info1Bb = gr.Textbox(label="GPT训练进程输出信息")
+ button1Ba_open.click(
+ 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,
+ ],
+ [info1Ba, button1Ba_open, button1Ba_close],
+ )
+ button1Ba_close.click(
+ close1Ba, [], [info1Ba, button1Ba_open, button1Ba_close]
+ )
+ button1Bb_open.click(
+ open1Bb,
+ [
+ batch_size1Bb,
+ total_epoch1Bb,
+ exp_name,
+ if_save_latest1Bb,
+ if_save_every_weights1Bb,
+ save_every_epoch1Bb,
+ gpu_numbers1Bb,
+ pretrained_s1,
+ ],
+ [info1Bb, button1Bb_open, button1Bb_close],
+ )
+ button1Bb_close.click(
+ close1Bb, [], [info1Bb, button1Bb_open, button1Bb_close]
+ )
with gr.TabItem("1C-推理"):
- gr.Markdown(value="选择训练完存放在SoVITS_weights和GPT_weights下的模型。默认的一个是底模，体验5秒Zero Shot TTS用。")
+ gr.Markdown(
+ value="选择训练完存放在SoVITS_weights和GPT_weights下的模型。默认的一个是底模，体验5秒Zero Shot TTS用。"
+ )
with gr.Row():
- GPT_dropdown = gr.Dropdown(label="*GPT模型列表", choices=sorted(GPT_names),value=pretrained_gpt_name)
- SoVITS_dropdown = gr.Dropdown(label="*SoVITS模型列表", choices=sorted(SoVITS_names),value=pretrained_sovits_name)
- gpu_number_1C=gr.Textbox(label="GPU卡号,只能填1个整数", value=gpus, interactive=True)
+ GPT_dropdown = gr.Dropdown(
+ label="*GPT模型列表",
+ choices=sorted(GPT_names),
+ value=pretrained_gpt_name,
+ )
+ SoVITS_dropdown = gr.Dropdown(
+ label="*SoVITS模型列表",
+ choices=sorted(SoVITS_names),
+ value=pretrained_sovits_name,
+ )
+ gpu_number_1C = gr.Textbox(
+ label="GPU卡号,只能填1个整数", value=gpus, interactive=True
+ )
refresh_button = gr.Button("刷新模型路径", variant="primary")
- refresh_button.click(fn=change_choices,inputs=[],outputs=[SoVITS_dropdown,GPT_dropdown])
+ refresh_button.click(
+ fn=change_choices,
+ inputs=[],
+ outputs=[SoVITS_dropdown, GPT_dropdown],
+ )
with gr.Row():
if_tts = gr.Checkbox(label="是否开启TTS推理WebUI", show_label=True)
tts_info = gr.Textbox(label="TTS推理WebUI进程输出信息")
- if_tts.change(change_tts_inference, [if_tts,bert_pretrained_dir,cnhubert_base_dir,gpu_number_1C,GPT_dropdown,SoVITS_dropdown], [tts_info])
- with gr.TabItem("2-GPT-SoVITS-变声"):gr.Markdown(value="施工中，请静候佳音")
+ if_tts.change(
+ change_tts_inference,
+ [
+ if_tts,
+ bert_pretrained_dir,
+ cnhubert_base_dir,
+ gpu_number_1C,
+ GPT_dropdown,
+ SoVITS_dropdown,
+ ],
+ [tts_info],
+ )
+ with gr.TabItem("2-GPT-SoVITS-变声"):
+ gr.Markdown(value="施工中，请静候佳音")
- '''
+ """
os.environ["gpt_path"]=gpt_path
os.environ["sovits_path"]=sovits_path#bert_pretrained_dir
os.environ["cnhubert_base_path"]=cnhubert_base_path#cnhubert_base_dir
os.environ["bert_path"]=bert_path
os.environ["_CUDA_VISIBLE_DEVICES"]=gpu_number
- '''
+ """
app.queue(concurrency_count=511, max_size=1022).launch(
server_name="0.0.0.0",