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| import os,sys | |
| if len(sys.argv)==1:sys.argv.append('v2') | |
| version="v1"if sys.argv[1]=="v1" else"v2" | |
| os.environ["version"]=version | |
| now_dir = os.getcwd() | |
| sys.path.insert(0, now_dir) | |
| import warnings | |
| warnings.filterwarnings("ignore") | |
| import json,yaml,torch,pdb,re,shutil | |
| import platform | |
| import psutil | |
| import signal | |
| torch.manual_seed(233333) | |
| tmp = os.path.join(now_dir, "TEMP") | |
| os.makedirs(tmp, exist_ok=True) | |
| os.environ["TEMP"] = tmp | |
| if(os.path.exists(tmp)): | |
| for name in os.listdir(tmp): | |
| if(name=="jieba.cache"):continue | |
| path="%s/%s"%(tmp,name) | |
| delete=os.remove if os.path.isfile(path) else shutil.rmtree | |
| try: | |
| delete(path) | |
| except Exception as e: | |
| print(str(e)) | |
| pass | |
| import site | |
| site_packages_roots = [] | |
| for path in site.getsitepackages(): | |
| if "packages" in path: | |
| site_packages_roots.append(path) | |
| if(site_packages_roots==[]):site_packages_roots=["%s/runtime/Lib/site-packages" % now_dir] | |
| #os.environ["OPENBLAS_NUM_THREADS"] = "4" | |
| os.environ["no_proxy"] = "localhost, 127.0.0.1, ::1" | |
| os.environ["all_proxy"] = "" | |
| for site_packages_root in site_packages_roots: | |
| if os.path.exists(site_packages_root): | |
| try: | |
| 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) | |
| ) | |
| break | |
| except PermissionError: | |
| pass | |
| from tools import my_utils | |
| import traceback | |
| import shutil | |
| import pdb | |
| 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,is_share | |
| from tools.i18n.i18n import I18nAuto, scan_language_list | |
| language=sys.argv[-1] if sys.argv[-1] in scan_language_list() else "Auto" | |
| os.environ["language"]=language | |
| i18n = I18nAuto(language=language) | |
| from scipy.io import wavfile | |
| from tools.my_utils import load_audio | |
| from multiprocessing import cpu_count | |
| # os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1' # 当遇到mps不支持的步骤时使用cpu | |
| import gradio.analytics as analytics | |
| analytics.version_check = lambda:None | |
| import gradio as gr | |
| n_cpu=cpu_count() | |
| ngpu = torch.cuda.device_count() | |
| gpu_infos = [] | |
| mem = [] | |
| if_gpu_ok = False | |
| # 判断是否有能用来训练和加速推理的N卡 | |
| ok_gpu_keywords={"10","16","20","30","40","A2","A3","A4","P4","A50","500","A60","70","80","90","M4","T4","TITAN","L4","4060","H"} | |
| set_gpu_numbers=set() | |
| 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 ok_gpu_keywords): | |
| # 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)) | |
| set_gpu_numbers.add(i) | |
| mem.append(int(torch.cuda.get_device_properties(i).total_memory/ 1024/ 1024/ 1024+ 0.4)) | |
| # # 判断是否支持mps加速 | |
| # if torch.backends.mps.is_available(): | |
| # if_gpu_ok = True | |
| # gpu_infos.append("%s\t%s" % ("0", "Apple GPU")) | |
| # mem.append(psutil.virtual_memory().total/ 1024 / 1024 / 1024) # 实测使用系统内存作为显存不会爆显存 | |
| if if_gpu_ok and len(gpu_infos) > 0: | |
| gpu_info = "\n".join(gpu_infos) | |
| default_batch_size = min(mem) // 2 | |
| else: | |
| gpu_info = ("%s\t%s" % ("0", "CPU")) | |
| gpu_infos.append("%s\t%s" % ("0", "CPU")) | |
| set_gpu_numbers.add(0) | |
| default_batch_size = int(psutil.virtual_memory().total/ 1024 / 1024 / 1024 / 2) | |
| gpus = "-".join([i[0] for i in gpu_infos]) | |
| default_gpu_numbers=str(sorted(list(set_gpu_numbers))[0]) | |
| def fix_gpu_number(input):#将越界的number强制改到界内 | |
| try: | |
| if(int(input)not in set_gpu_numbers):return default_gpu_numbers | |
| except:return input | |
| return input | |
| def fix_gpu_numbers(inputs): | |
| output=[] | |
| try: | |
| for input in inputs.split(","):output.append(str(fix_gpu_number(input))) | |
| return ",".join(output) | |
| except: | |
| return inputs | |
| pretrained_sovits_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth", "GPT_SoVITS/pretrained_models/s2G488k.pth"] | |
| pretrained_gpt_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt", "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"] | |
| pretrained_model_list = (pretrained_sovits_name[-int(version[-1])+2],pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D"),pretrained_gpt_name[-int(version[-1])+2],"GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large","GPT_SoVITS/pretrained_models/chinese-hubert-base") | |
| _='' | |
| for i in pretrained_model_list: | |
| if os.path.exists(i):... | |
| else:_+=f'\n {i}' | |
| if _: | |
| print("warning:",i18n('以下模型不存在:')+_) | |
| _ =[[],[]] | |
| for i in range(2): | |
| if os.path.exists(pretrained_gpt_name[i]):_[0].append(pretrained_gpt_name[i]) | |
| else:_[0].append("")##没有下pretrained模型的，说不定他们是想自己从零训底模呢 | |
| if os.path.exists(pretrained_sovits_name[i]):_[-1].append(pretrained_sovits_name[i]) | |
| else:_[-1].append("") | |
| pretrained_gpt_name,pretrained_sovits_name = _ | |
| SoVITS_weight_root=["SoVITS_weights_v2","SoVITS_weights"] | |
| GPT_weight_root=["GPT_weights_v2","GPT_weights"] | |
| for root in SoVITS_weight_root+GPT_weight_root: | |
| os.makedirs(root,exist_ok=True) | |
| def get_weights_names(): | |
| SoVITS_names = [name for name in pretrained_sovits_name if name!=""] | |
| for path in SoVITS_weight_root: | |
| for name in os.listdir(path): | |
| if name.endswith(".pth"): SoVITS_names.append("%s/%s" % (path, name)) | |
| GPT_names = [name for name in pretrained_gpt_name if name!=""] | |
| for path in GPT_weight_root: | |
| for name in os.listdir(path): | |
| if name.endswith(".ckpt"): GPT_names.append("%s/%s" % (path, name)) | |
| return SoVITS_names, GPT_names | |
| SoVITS_names,GPT_names = get_weights_names() | |
| for path in SoVITS_weight_root+GPT_weight_root: | |
| os.makedirs(path,exist_ok=True) | |
| def custom_sort_key(s): | |
| # 使用正则表达式提取字符串中的数字部分和非数字部分 | |
| parts = re.split('(\d+)', s) | |
| # 将数字部分转换为整数，非数字部分保持不变 | |
| parts = [int(part) if part.isdigit() else part for part in parts] | |
| return parts | |
| def change_choices(): | |
| SoVITS_names, GPT_names = get_weights_names() | |
| return {"choices": sorted(SoVITS_names,key=custom_sort_key), "__type__": "update"}, {"choices": sorted(GPT_names,key=custom_sort_key), "__type__": "update"} | |
| p_label=None | |
| p_uvr5=None | |
| p_asr=None | |
| p_denoise=None | |
| p_tts_inference=None | |
| def kill_proc_tree(pid, including_parent=True): | |
| try: | |
| parent = psutil.Process(pid) | |
| except psutil.NoSuchProcess: | |
| # Process already terminated | |
| return | |
| children = parent.children(recursive=True) | |
| for child in children: | |
| try: | |
| os.kill(child.pid, signal.SIGTERM) # or signal.SIGKILL | |
| except OSError: | |
| pass | |
| if including_parent: | |
| try: | |
| os.kill(parent.pid, signal.SIGTERM) # or signal.SIGKILL | |
| except OSError: | |
| pass | |
| system=platform.system() | |
| def kill_process(pid): | |
| if(system=="Windows"): | |
| cmd = "taskkill /t /f /pid %s" % pid | |
| os.system(cmd) | |
| else: | |
| kill_proc_tree(pid) | |
| def change_label(if_label,path_list): | |
| global p_label | |
| if(if_label==True and p_label==None): | |
| path_list=my_utils.clean_path(path_list) | |
| cmd = '"%s" tools/subfix_webui.py --load_list "%s" --webui_port %s --is_share %s'%(python_exec,path_list,webui_port_subfix,is_share) | |
| yield i18n("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 i18n("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 %s'%(python_exec,infer_device,is_half,webui_port_uvr5,is_share) | |
| yield i18n("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 i18n("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"]=fix_gpu_number(gpu_number) | |
| os.environ["is_half"]=str(is_half) | |
| os.environ["infer_ttswebui"]=str(webui_port_infer_tts) | |
| os.environ["is_share"]=str(is_share) | |
| cmd = '"%s" GPT_SoVITS/inference_webui.py "%s"'%(python_exec, language) | |
| yield i18n("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 i18n("TTS推理进程已关闭") | |
| from tools.asr.config import asr_dict | |
| def open_asr(asr_inp_dir, asr_opt_dir, asr_model, asr_model_size, asr_lang, asr_precision): | |
| global p_asr | |
| if(p_asr==None): | |
| asr_inp_dir=my_utils.clean_path(asr_inp_dir) | |
| asr_opt_dir=my_utils.clean_path(asr_opt_dir) | |
| check_for_exists([asr_inp_dir]) | |
| cmd = f'"{python_exec}" tools/asr/{asr_dict[asr_model]["path"]}' | |
| cmd += f' -i "{asr_inp_dir}"' | |
| cmd += f' -o "{asr_opt_dir}"' | |
| cmd += f' -s {asr_model_size}' | |
| cmd += f' -l {asr_lang}' | |
| cmd += f" -p {asr_precision}" | |
| output_file_name = os.path.basename(asr_inp_dir) | |
| output_folder = asr_opt_dir or "output/asr_opt" | |
| output_file_path = os.path.abspath(f'{output_folder}/{output_file_name}.list') | |
| yield "ASR任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"}, {"__type__":"update"} | |
| print(cmd) | |
| p_asr = Popen(cmd, shell=True) | |
| p_asr.wait() | |
| p_asr=None | |
| yield f"ASR任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":output_file_path}, {"__type__":"update","value":output_file_path}, {"__type__":"update","value":asr_inp_dir} | |
| 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}, {"__type__":"update"}, {"__type__":"update"}, {"__type__":"update"} | |
| # return None | |
| 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} | |
| def open_denoise(denoise_inp_dir, denoise_opt_dir): | |
| global p_denoise | |
| if(p_denoise==None): | |
| denoise_inp_dir=my_utils.clean_path(denoise_inp_dir) | |
| denoise_opt_dir=my_utils.clean_path(denoise_opt_dir) | |
| check_for_exists([denoise_inp_dir]) | |
| cmd = '"%s" tools/cmd-denoise.py -i "%s" -o "%s" -p %s'%(python_exec,denoise_inp_dir,denoise_opt_dir,"float16"if is_half==True else "float32") | |
| yield "语音降噪任务开启：%s"%cmd, {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"} | |
| print(cmd) | |
| p_denoise = Popen(cmd, shell=True) | |
| p_denoise.wait() | |
| p_denoise=None | |
| yield f"语音降噪任务完成, 查看终端进行下一步", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__":"update","value":denoise_opt_dir}, {"__type__":"update","value":denoise_opt_dir} | |
| else: | |
| yield "已有正在进行的语音降噪任务，需先终止才能开启下一次任务", {"__type__":"update","visible":False}, {"__type__":"update","visible":True}, {"__type__":"update"}, {"__type__":"update"} | |
| # return None | |
| def close_denoise(): | |
| global p_denoise | |
| if(p_denoise!=None): | |
| kill_process(p_denoise.pid) | |
| p_denoise=None | |
| return "已终止语音降噪进程", {"__type__":"update","visible":True}, {"__type__":"update","visible":False} | |
| 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) | |
| check_for_exists([s2_dir],is_train=True) | |
| if(is_half==False): | |
| data["train"]["fp16_run"]=False | |
| batch_size=max(1,batch_size//2) | |
| 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["model"]["version"]=version | |
| data["data"]["exp_dir"]=data["s2_ckpt_dir"]=s2_dir | |
| data["save_weight_dir"]=SoVITS_weight_root[-int(version[-1])+2] | |
| data["name"]=exp_name | |
| data["version"]=version | |
| tmp_config_path="%s/tmp_s2.json"%tmp | |
| 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_dpo,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"if version=="v1"else "GPT_SoVITS/configs/s1longer-v2.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) | |
| check_for_exists([s1_dir],is_train=True) | |
| if(is_half==False): | |
| data["train"]["precision"]="32" | |
| batch_size = max(1, batch_size // 2) | |
| 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"]["if_dpo"]=if_dpo | |
| data["train"]["half_weights_save_dir"]=GPT_weight_root[-int(version[-1])+2] | |
| 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 | |
| # data["version"]=version | |
| os.environ["_CUDA_VISIBLE_DEVICES"]=fix_gpu_numbers(gpu_numbers.replace("-",",")) | |
| os.environ["hz"]="25hz" | |
| tmp_config_path="%s/tmp_s1.yaml"%tmp | |
| 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 | |
| inp = my_utils.clean_path(inp) | |
| opt_root = my_utils.clean_path(opt_root) | |
| check_for_exists([inp]) | |
| if(os.path.exists(inp)==False): | |
| yield "输入路径不存在", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} | |
| 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}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} | |
| 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}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} | |
| for p in ps_slice: | |
| p.wait() | |
| ps_slice=[] | |
| yield "切割结束", {"__type__":"update","visible":True}, {"__type__":"update","visible":False}, {"__type__": "update", "value":opt_root}, {"__type__": "update", "value":opt_root}, {"__type__": "update", "value":opt_root} | |
| 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}, {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"} | |
| 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} | |
| ps1a=[] | |
| def open1a(inp_text,inp_wav_dir,exp_name,gpu_numbers,bert_pretrained_dir): | |
| global ps1a | |
| inp_text = my_utils.clean_path(inp_text) | |
| inp_wav_dir = my_utils.clean_path(inp_wav_dir) | |
| check_for_exists([inp_text,inp_wav_dir], is_dataset_processing=True) | |
| if (ps1a == []): | |
| opt_dir="%s/%s"%(exp_root,exp_name) | |
| 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, | |
| } | |
| 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": fix_gpu_number(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() | |
| opt = [] | |
| for i_part in range(all_parts): | |
| 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) | |
| path_text = "%s/2-name2text.txt" % opt_dir | |
| with open(path_text, "w", encoding="utf8") as f: | |
| f.write("\n".join(opt) + "\n") | |
| ps1a=[] | |
| if len("".join(opt)) > 0: | |
| yield "文本进程成功", {"__type__": "update", "visible": True}, {"__type__": "update", "visible": False} | |
| else: | |
| yield "文本进程失败", {"__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} | |
| ps1b=[] | |
| def open1b(inp_text,inp_wav_dir,exp_name,gpu_numbers,ssl_pretrained_dir): | |
| global ps1b | |
| inp_text = my_utils.clean_path(inp_text) | |
| inp_wav_dir = my_utils.clean_path(inp_wav_dir) | |
| check_for_exists([inp_text,inp_wav_dir], is_dataset_processing=True) | |
| 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": fix_gpu_number(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} | |
| ps1c=[] | |
| def open1c(inp_text,exp_name,gpu_numbers,pretrained_s2G_path): | |
| global ps1c | |
| inp_text = my_utils.clean_path(inp_text) | |
| check_for_exists([inp_text,''], is_dataset_processing=True) | |
| if (ps1c == []): | |
| opt_dir="%s/%s"%(exp_root,exp_name) | |
| 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", | |
| "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": fix_gpu_number(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() | |
| opt = ["item_name\tsemantic_audio"] | |
| path_semantic = "%s/6-name2semantic.tsv" % opt_dir | |
| 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") | |
| 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 | |
| inp_text = my_utils.clean_path(inp_text) | |
| inp_wav_dir = my_utils.clean_path(inp_wav_dir) | |
| check_for_exists([inp_text,inp_wav_dir]) | |
| 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 or (os.path.exists(path_text)==True and len(open(path_text,"r",encoding="utf8").read().strip("\n").split("\n"))<2)): | |
| 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": fix_gpu_number(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") | |
| assert len("".join(opt)) > 0, "1Aa-文本获取进程失败" | |
| 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": fix_gpu_number(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 or (os.path.exists(path_semantic)==True and os.path.getsize(path_semantic)<31)): | |
| 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": fix_gpu_number(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\tsemantic_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} | |
| def switch_version(version_): | |
| os.environ['version']=version_ | |
| global version | |
| version = version_ | |
| if pretrained_sovits_name[-int(version[-1])+2] !='' and pretrained_gpt_name[-int(version[-1])+2] !='':... | |
| else: | |
| gr.Warning(i18n(f'未下载{version.upper()}模型')) | |
| return {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D")}, {'__type__':'update', 'value':pretrained_gpt_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_gpt_name[-int(version[-1])+2]}, {'__type__':'update', 'value':pretrained_sovits_name[-int(version[-1])+2]} | |
| def check_for_exists(file_list=None,is_train=False,is_dataset_processing=False): | |
| missing_files=[] | |
| if is_train == True and file_list: | |
| file_list.append(os.path.join(file_list[0],'2-name2text.txt')) | |
| file_list.append(os.path.join(file_list[0],'3-bert')) | |
| file_list.append(os.path.join(file_list[0],'4-cnhubert')) | |
| file_list.append(os.path.join(file_list[0],'5-wav32k')) | |
| file_list.append(os.path.join(file_list[0],'6-name2semantic.tsv')) | |
| for file in file_list: | |
| if os.path.exists(file):pass | |
| else:missing_files.append(file) | |
| if missing_files: | |
| if is_train: | |
| for missing_file in missing_files: | |
| if missing_file != '': | |
| gr.Warning(missing_file) | |
| gr.Warning(i18n('以下文件或文件夹不存在:')) | |
| else: | |
| for missing_file in missing_files: | |
| if missing_file != '': | |
| gr.Warning(missing_file) | |
| if file_list[-1]==[''] and is_dataset_processing: | |
| pass | |
| else: | |
| gr.Warning(i18n('以下文件或文件夹不存在:')) | |
| if os.path.exists('GPT_SoVITS/text/G2PWModel'):... | |
| else: | |
| cmd = '"%s" GPT_SoVITS/download.py'%python_exec | |
| p = Popen(cmd, shell=True) | |
| p.wait() | |
| with gr.Blocks(title="GPT-SoVITS WebUI") as app: | |
| gr.Markdown( | |
| value= | |
| i18n("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>.") | |
| ) | |
| gr.Markdown( | |
| value= | |
| i18n("中文教程文档：https://www.yuque.com/baicaigongchang1145haoyuangong/ib3g1e") | |
| ) | |
| with gr.Tabs(): | |
| with gr.TabItem(i18n("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=i18n("0a-UVR5人声伴奏分离&去混响去延迟工具")) | |
| with gr.Row(): | |
| if_uvr5 = gr.Checkbox(label=i18n("是否开启UVR5-WebUI"),show_label=True) | |
| uvr5_info = gr.Textbox(label=i18n("UVR5进程输出信息")) | |
| gr.Markdown(value=i18n("0b-语音切分工具")) | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| with gr.Row(): | |
| slice_inp_path=gr.Textbox(label=i18n("音频自动切分输入路径，可文件可文件夹"),value="") | |
| slice_opt_root=gr.Textbox(label=i18n("切分后的子音频的输出根目录"),value="output/slicer_opt") | |
| with gr.Row(): | |
| threshold=gr.Textbox(label=i18n("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=i18n("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=i18n("min_interval:最短切割间隔"),value="300") | |
| hop_size=gr.Textbox(label=i18n("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=i18n("max_sil_kept:切完后静音最多留多长"),value="500") | |
| with gr.Row(): | |
| _max=gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("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=i18n("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=i18n("切割使用的进程数"),value=4,interactive=True) | |
| with gr.Row(): | |
| slicer_info = gr.Textbox(label=i18n("语音切割进程输出信息")) | |
| open_slicer_button=gr.Button(i18n("开启语音切割"), variant="primary",visible=True) | |
| close_slicer_button=gr.Button(i18n("终止语音切割"), variant="primary",visible=False) | |
| gr.Markdown(value=i18n("0bb-语音降噪工具")) | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| with gr.Row(): | |
| denoise_input_dir=gr.Textbox(label=i18n("降噪音频文件输入文件夹"),value="") | |
| denoise_output_dir=gr.Textbox(label=i18n("降噪结果输出文件夹"),value="output/denoise_opt") | |
| with gr.Row(): | |
| denoise_info = gr.Textbox(label=i18n("语音降噪进程输出信息")) | |
| open_denoise_button = gr.Button(i18n("开启语音降噪"), variant="primary",visible=True) | |
| close_denoise_button = gr.Button(i18n("终止语音降噪进程"), variant="primary",visible=False) | |
| gr.Markdown(value=i18n("0c-中文批量离线ASR工具")) | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| with gr.Row(): | |
| asr_inp_dir = gr.Textbox( | |
| label=i18n("输入文件夹路径"), | |
| value="D:\\GPT-SoVITS\\raw\\xxx", | |
| interactive=True, | |
| ) | |
| asr_opt_dir = gr.Textbox( | |
| label = i18n("输出文件夹路径"), | |
| value = "output/asr_opt", | |
| interactive = True, | |
| ) | |
| with gr.Row(): | |
| asr_model = gr.Dropdown( | |
| label = i18n("ASR 模型"), | |
| choices = list(asr_dict.keys()), | |
| interactive = True, | |
| value="达摩 ASR (中文)" | |
| ) | |
| asr_size = gr.Dropdown( | |
| label = i18n("ASR 模型尺寸"), | |
| choices = ["large"], | |
| interactive = True, | |
| value="large" | |
| ) | |
| asr_lang = gr.Dropdown( | |
| label = i18n("ASR 语言设置"), | |
| choices = ["zh","yue"], | |
| interactive = True, | |
| value="zh" | |
| ) | |
| asr_precision = gr.Dropdown( | |
| label = i18n("数据类型精度"), | |
| choices = ["float32"], | |
| interactive = True, | |
| value="float32" | |
| ) | |
| with gr.Row(): | |
| asr_info = gr.Textbox(label=i18n("ASR进程输出信息")) | |
| open_asr_button = gr.Button(i18n("开启离线批量ASR"), variant="primary",visible=True) | |
| close_asr_button = gr.Button(i18n("终止ASR进程"), variant="primary",visible=False) | |
| def change_lang_choices(key): #根据选择的模型修改可选的语言 | |
| # return gr.Dropdown(choices=asr_dict[key]['lang']) | |
| return {"__type__": "update", "choices": asr_dict[key]['lang'],"value":asr_dict[key]['lang'][0]} | |
| def change_size_choices(key): # 根据选择的模型修改可选的模型尺寸 | |
| # return gr.Dropdown(choices=asr_dict[key]['size']) | |
| return {"__type__": "update", "choices": asr_dict[key]['size'],"value":asr_dict[key]['size'][-1]} | |
| def change_precision_choices(key): #根据选择的模型修改可选的语言 | |
| if key =="Faster Whisper (多语种)": | |
| if default_batch_size <= 4: | |
| precision = 'int8' | |
| elif is_half: | |
| precision = 'float16' | |
| else: | |
| precision = 'float32' | |
| else: | |
| precision = 'float32' | |
| # return gr.Dropdown(choices=asr_dict[key]['precision']) | |
| return {"__type__": "update", "choices": asr_dict[key]['precision'],"value":precision} | |
| asr_model.change(change_lang_choices, [asr_model], [asr_lang]) | |
| asr_model.change(change_size_choices, [asr_model], [asr_size]) | |
| asr_model.change(change_precision_choices, [asr_model], [asr_precision]) | |
| gr.Markdown(value=i18n("0d-语音文本校对标注工具")) | |
| with gr.Row(): | |
| if_label = gr.Checkbox(label=i18n("是否开启打标WebUI"),show_label=True) | |
| path_list = gr.Textbox( | |
| label=i18n(".list标注文件的路径"), | |
| value="D:\\RVC1006\\GPT-SoVITS\\raw\\xxx.list", | |
| interactive=True, | |
| ) | |
| label_info = gr.Textbox(label=i18n("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]) | |
| with gr.TabItem(i18n("1-GPT-SoVITS-TTS")): | |
| with gr.Row(): | |
| exp_name = gr.Textbox(label=i18n("*实验/模型名"), value="xxx", interactive=True) | |
| gpu_info = gr.Textbox(label=i18n("显卡信息"), value=gpu_info, visible=True, interactive=False) | |
| version_checkbox = gr.Radio(label=i18n("版本"),value=version,choices=['v1','v2']) | |
| pretrained_s2G = gr.Textbox(label=i18n("预训练的SoVITS-G模型路径"), value=pretrained_sovits_name[-int(version[-1])+2], interactive=True) | |
| pretrained_s2D = gr.Textbox(label=i18n("预训练的SoVITS-D模型路径"), value=pretrained_sovits_name[-int(version[-1])+2].replace("s2G","s2D"), interactive=True) | |
| pretrained_s1 = gr.Textbox(label=i18n("预训练的GPT模型路径"), value=pretrained_gpt_name[-int(version[-1])+2], interactive=True) | |
| with gr.TabItem(i18n("1A-训练集格式化工具")): | |
| gr.Markdown(value=i18n("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=i18n("*文本标注文件"),value=r"D:\RVC1006\GPT-SoVITS\raw\xxx.list",interactive=True) | |
| inp_wav_dir = gr.Textbox( | |
| label=i18n("*训练集音频文件目录"), | |
| # value=r"D:\RVC1006\GPT-SoVITS\raw\xxx", | |
| interactive=True, | |
| placeholder=i18n("填切割后音频所在目录！读取的音频文件完整路径=该目录-拼接-list文件里波形对应的文件名（不是全路径）。如果留空则使用.list文件里的绝对全路径。") | |
| ) | |
| gr.Markdown(value=i18n("1Aa-文本内容")) | |
| with gr.Row(): | |
| gpu_numbers1a = gr.Textbox(label=i18n("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=i18n("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(i18n("开启文本获取"), variant="primary",visible=True) | |
| button1a_close = gr.Button(i18n("终止文本获取进程"), variant="primary",visible=False) | |
| info1a=gr.Textbox(label=i18n("文本进程输出信息")) | |
| gr.Markdown(value=i18n("1Ab-SSL自监督特征提取")) | |
| with gr.Row(): | |
| gpu_numbers1Ba = gr.Textbox(label=i18n("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=i18n("预训练的SSL模型路径"),value="GPT_SoVITS/pretrained_models/chinese-hubert-base",interactive=False) | |
| button1b_open = gr.Button(i18n("开启SSL提取"), variant="primary",visible=True) | |
| button1b_close = gr.Button(i18n("终止SSL提取进程"), variant="primary",visible=False) | |
| info1b=gr.Textbox(label=i18n("SSL进程输出信息")) | |
| gr.Markdown(value=i18n("1Ac-语义token提取")) | |
| with gr.Row(): | |
| gpu_numbers1c = gr.Textbox(label=i18n("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(i18n("开启语义token提取"), variant="primary",visible=True) | |
| button1c_close = gr.Button(i18n("终止语义token提取进程"), variant="primary",visible=False) | |
| info1c=gr.Textbox(label=i18n("语义token提取进程输出信息")) | |
| gr.Markdown(value=i18n("1Aabc-训练集格式化一键三连")) | |
| with gr.Row(): | |
| button1abc_open = gr.Button(i18n("开启一键三连"), variant="primary",visible=True) | |
| button1abc_close = gr.Button(i18n("终止一键三连"), variant="primary",visible=False) | |
| info1abc=gr.Textbox(label=i18n("一键三连进程输出信息")) | |
| open_asr_button.click(open_asr, [asr_inp_dir, asr_opt_dir, asr_model, asr_size, asr_lang, asr_precision], [asr_info,open_asr_button,close_asr_button,path_list,inp_text,inp_wav_dir]) | |
| 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,asr_inp_dir,denoise_input_dir,inp_wav_dir]) | |
| close_slicer_button.click(close_slice, [], [slicer_info,open_slicer_button,close_slicer_button]) | |
| open_denoise_button.click(open_denoise, [denoise_input_dir,denoise_output_dir], [denoise_info,open_denoise_button,close_denoise_button,asr_inp_dir,inp_wav_dir]) | |
| close_denoise_button.click(close_denoise, [], [denoise_info,open_denoise_button,close_denoise_button]) | |
| 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(i18n("1B-微调训练")): | |
| gr.Markdown(value=i18n("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=25,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=i18n("文本模块学习率权重"),value=0.4,interactive=True) | |
| save_every_epoch = gr.Slider(minimum=1,maximum=25,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=i18n("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(i18n("开启SoVITS训练"), variant="primary",visible=True) | |
| button1Ba_close = gr.Button(i18n("终止SoVITS训练"), variant="primary",visible=False) | |
| info1Ba=gr.Textbox(label=i18n("SoVITS训练进程输出信息")) | |
| gr.Markdown(value=i18n("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=50,step=1,label=i18n("总训练轮数total_epoch"),value=15,interactive=True) | |
| if_dpo = gr.Checkbox(label=i18n("是否开启dpo训练选项(实验性)"), value=False, interactive=True, show_label=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=i18n("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(i18n("开启GPT训练"), variant="primary",visible=True) | |
| button1Bb_close = gr.Button(i18n("终止GPT训练"), variant="primary",visible=False) | |
| info1Bb=gr.Textbox(label=i18n("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_dpo,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(i18n("1C-推理")): | |
| gr.Markdown(value=i18n("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=i18n("*GPT模型列表"), choices=sorted(GPT_names,key=custom_sort_key),value=pretrained_gpt_name[0],interactive=True) | |
| SoVITS_dropdown = gr.Dropdown(label=i18n("*SoVITS模型列表"), choices=sorted(SoVITS_names,key=custom_sort_key),value=pretrained_sovits_name[0],interactive=True) | |
| gpu_number_1C=gr.Textbox(label=i18n("GPU卡号,只能填1个整数"), value=gpus, interactive=True) | |
| refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary") | |
| refresh_button.click(fn=change_choices,inputs=[],outputs=[SoVITS_dropdown,GPT_dropdown]) | |
| with gr.Row(): | |
| if_tts = gr.Checkbox(label=i18n("是否开启TTS推理WebUI"), show_label=True) | |
| tts_info = gr.Textbox(label=i18n("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]) | |
| version_checkbox.change(switch_version,[version_checkbox],[pretrained_s2G,pretrained_s2D,pretrained_s1,GPT_dropdown,SoVITS_dropdown]) | |
| with gr.TabItem(i18n("2-GPT-SoVITS-变声")):gr.Markdown(value=i18n("施工中，请静候佳音")) | |
| app.queue(concurrency_count=511, max_size=1022).launch( | |
| server_name="0.0.0.0", | |
| inbrowser=True, | |
| share=True, | |
| server_port=webui_port_main, | |
| quiet=True, | |
| ) |