Delete easy_infer.py

easy_infer.py

@@ -1,1421 +0,0 @@
-import subprocess
-import os
-import sys
-import errno
-import shutil
-import yt_dlp
-from mega import Mega
-import datetime
-import unicodedata
-import torch
-import glob
-import gradio as gr
-import gdown
-import zipfile
-import traceback
-import json
-import requests
-import wget
-import hashlib
-now_dir = os.getcwd()
-sys.path.append(now_dir)
-from unidecode import unidecode
-import re
-from lib.infer_pack.models_onnx import SynthesizerTrnMsNSFsidM
-from vc_infer_pipeline import VC
-from MDXNet import MDXNetDereverb
-from infer_uvr5 import _audio_pre_, _audio_pre_new
-from huggingface_hub import HfApi, list_models
-from huggingface_hub import login
-from i18n import I18nAuto
-i18n = I18nAuto()
-from bs4 import BeautifulSoup
-
-weight_root = "weights"
-weight_uvr5_root = "uvr5_weights"
-index_root = "./logs/"
-audio_root = "audios"
-names = []
-for name in os.listdir(weight_root):
-    if name.endswith(".pth"):
-        names.append(name)
-index_paths = []
-
-global indexes_list
-indexes_list = []
-
-audio_paths = []
-for root, dirs, files in os.walk(index_root, topdown=False):
-    for name in files:
-        if name.endswith(".index") and "trained" not in name:
-            index_paths.append("%s\\%s" % (root, name))
-
-for root, dirs, files in os.walk(audio_root, topdown=False):
-    for name in files:
-        audio_paths.append("%s/%s" % (root, name))
-
-uvr5_names = []
-for name in os.listdir(weight_uvr5_root):
-    if name.endswith(".pth") or "onnx" in name:
-        uvr5_names.append(name.replace(".pth", ""))
-
-def calculate_md5(file_path):
-    hash_md5 = hashlib.md5()
-    with open(file_path, "rb") as f:
-        for chunk in iter(lambda: f.read(4096), b""):
-            hash_md5.update(chunk)
-    return hash_md5.hexdigest()
-
-def silentremove(filename):
-    try:
-        os.remove(filename)
-    except OSError as e: # this would be "except OSError, e:" before Python 2.6
-        if e.errno != errno.ENOENT: # errno.ENOENT = no such file or directory
-            raise # re-raise exception if a different error occurred
-def get_md5(temp_folder):
-  for root, subfolders, files in os.walk(temp_folder):
-    for file in files:
-      if not file.startswith("G_") and not file.startswith("D_") and file.endswith(".pth") and not "_G_" in file and not "_D_" in file:
-        md5_hash = calculate_md5(os.path.join(root, file))
-        return md5_hash
-
-  return None
-
-def find_parent(search_dir, file_name):
-    for dirpath, dirnames, filenames in os.walk(search_dir):
-        if file_name in filenames:
-            return os.path.abspath(dirpath)
-    return None
-
-def find_folder_parent(search_dir, folder_name):
-    for dirpath, dirnames, filenames in os.walk(search_dir):
-        if folder_name in dirnames:
-            return os.path.abspath(dirpath)
-    return None
-
-def get_drive_folder_id(url):
-    if "drive.google.com" in url:
-        if "file/d/" in url:
-            file_id = url.split("file/d/")[1].split("/")[0]
-        elif "id=" in url:
-            file_id = url.split("id=")[1].split("&")[0]
-        else:
-            return None
-
-def download_from_url(url):
-    parent_path = find_folder_parent(".", "pretrained_v2")
-    zips_path = os.path.join(parent_path, 'zips')
-    
-    if url != '':
-        print(i18n("下载文件：") + f"{url}")
-        if "drive.google.com" in url:
-            if "file/d/" in url:
-                file_id = url.split("file/d/")[1].split("/")[0]
-            elif "id=" in url:
-                file_id = url.split("id=")[1].split("&")[0]
-            else:
-                return None
-            
-            if file_id:
-                os.chdir('./zips')
-                result = subprocess.run(["gdown", f"https://drive.google.com/uc?id={file_id}", "--fuzzy"], capture_output=True, text=True, encoding='utf-8')
-                if "Too many users have viewed or downloaded this file recently" in str(result.stderr):
-                    return "demasiado uso"
-                if "Cannot retrieve the public link of the file." in str(result.stderr):
-                    return "link privado"
-                print(result.stderr)
-                
-        elif "/blob/" in url:
-            os.chdir('./zips')
-            url = url.replace("blob", "resolve")
-          # print("Resolved URL:", url)  # Print the resolved URL
-            wget.download(url)
-        elif "mega.nz" in url:
-            if "#!" in url:
-                file_id = url.split("#!")[1].split("!")[0]
-            elif "file/" in url:
-                file_id = url.split("file/")[1].split("/")[0]
-            else:
-                return None
-            if file_id:
-                m = Mega()
-                m.download_url(url, zips_path)
-        elif "/tree/main" in url:
-           response = requests.get(url)
-           soup = BeautifulSoup(response.content, 'html.parser')
-           temp_url = ''
-           for link in soup.find_all('a', href=True):
-               if link['href'].endswith('.zip'):
-                  temp_url = link['href']
-                  break
-           if temp_url:
-              url = temp_url
-          # print("Updated URL:", url)  # Print the updated URL
-              url = url.replace("blob", "resolve")
-          # print("Resolved URL:", url)  # Print the resolved URL
-
-              if "huggingface.co" not in url:
-                 url = "https://huggingface.co" + url
-
-                 wget.download(url)
-           else:
-                 print("No .zip file found on the page.")
-            # Handle the case when no .zip file is found
-        else:
-            os.chdir('./zips')
-            wget.download(url)
-            
-        os.chdir(parent_path)
-        print(i18n("完整下载"))
-        return "downloaded"
-    else:
-        return None
-                
-class error_message(Exception):
-    def __init__(self, mensaje):
-        self.mensaje = mensaje
-        super().__init__(mensaje)
-
-# 一个选项卡全局只能有一个音色
-def get_vc(sid, to_return_protect0, to_return_protect1):
-    global n_spk, tgt_sr, net_g, vc, cpt, version
-    if sid == "" or sid == []:
-        global hubert_model
-        if hubert_model is not None:  # 考虑到轮询, 需要加个判断看是否 sid 是由有模型切换到无模型的
-            print("clean_empty_cache")
-            del net_g, n_spk, vc, hubert_model, tgt_sr  # ,cpt
-            hubert_model = net_g = n_spk = vc = hubert_model = tgt_sr = None
-            if torch.cuda.is_available():
-                torch.cuda.empty_cache()
-            ###楼下不这么折腾清理不干净
-            if_f0 = cpt.get("f0", 1)
-            version = cpt.get("version", "v1")
-            if version == "v1":
-                if if_f0 == 1:
-                    net_g = SynthesizerTrnMs256NSFsid(
-                        *cpt["config"], is_half=config.is_half
-                    )
-                else:
-                    net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
-            elif version == "v2":
-                if if_f0 == 1:
-                    net_g = SynthesizerTrnMs768NSFsid(
-                        *cpt["config"], is_half=config.is_half
-                    )
-                else:
-                    net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
-            del net_g, cpt
-            if torch.cuda.is_available():
-                torch.cuda.empty_cache()
-            cpt = None
-        return (
-            {"visible": False, "__type__": "update"},
-            {"visible": False, "__type__": "update"},
-            {"visible": False, "__type__": "update"},
-        )
-    person = "%s/%s" % (weight_root, sid)
-    print("loading %s" % person)
-    cpt = torch.load(person, map_location="cpu")
-    tgt_sr = cpt["config"][-1]
-    cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
-    if_f0 = cpt.get("f0", 1)
-    if if_f0 == 0:
-        to_return_protect0 = to_return_protect1 = {
-            "visible": False,
-            "value": 0.5,
-            "__type__": "update",
-        }
-    else:
-        to_return_protect0 = {
-            "visible": True,
-            "value": to_return_protect0,
-            "__type__": "update",
-        }
-        to_return_protect1 = {
-            "visible": True,
-            "value": to_return_protect1,
-            "__type__": "update",
-        }
-    version = cpt.get("version", "v1")
-    if version == "v1":
-        if if_f0 == 1:
-            net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
-        else:
-            net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
-    elif version == "v2":
-        if if_f0 == 1:
-            net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
-        else:
-            net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
-    del net_g.enc_q
-    print(net_g.load_state_dict(cpt["weight"], strict=False))
-    net_g.eval().to(config.device)
-    if config.is_half:
-        net_g = net_g.half()
-    else:
-        net_g = net_g.float()
-    vc = VC(tgt_sr, config)
-    n_spk = cpt["config"][-3]
-    return (
-        {"visible": True, "maximum": n_spk, "__type__": "update"},
-        to_return_protect0,
-        to_return_protect1,
-    )
-        
-def load_downloaded_model(url):
-    parent_path = find_folder_parent(".", "pretrained_v2")
-    try:
-        infos = []
-        logs_folders = ['0_gt_wavs','1_16k_wavs','2a_f0','2b-f0nsf','3_feature256','3_feature768']
-        zips_path = os.path.join(parent_path, 'zips')
-        unzips_path = os.path.join(parent_path, 'unzips')
-        weights_path = os.path.join(parent_path, 'weights')
-        logs_dir = ""
-        
-        if os.path.exists(zips_path):
-            shutil.rmtree(zips_path)
-        if os.path.exists(unzips_path):
-            shutil.rmtree(unzips_path)
-
-        os.mkdir(zips_path)
-        os.mkdir(unzips_path)
-        
-        download_file = download_from_url(url)
-        if not download_file:
-            print(i18n("无法下载模型。"))
-            infos.append(i18n("无法下载模型。"))
-            yield "\n".join(infos)
-        elif download_file == "downloaded":
-            print(i18n("模型下载成功。"))
-            infos.append(i18n("模型下载成功。"))
-            yield "\n".join(infos)
-        elif download_file == "demasiado uso":
-            raise Exception(i18n("最近查看或下载此文件的用户过多"))
-        elif download_file == "link privado":
-            raise Exception(i18n("无法从该私人链接获取文件"))
-        
-        # Descomprimir archivos descargados
-        for filename in os.listdir(zips_path):
-            if filename.endswith(".zip"):
-                zipfile_path = os.path.join(zips_path,filename)
-                print(i18n("继续提取..."))
-                infos.append(i18n("继续提取..."))
-                shutil.unpack_archive(zipfile_path, unzips_path, 'zip')
-                model_name = os.path.basename(zipfile_path)
-                logs_dir = os.path.join(parent_path,'logs', os.path.normpath(str(model_name).replace(".zip","")))
-                yield "\n".join(infos)
-            else:
-                print(i18n("解压缩出错。"))
-                infos.append(i18n("解压缩出错。"))
-                yield "\n".join(infos)
-        
-        index_file = False
-        model_file = False
-        D_file = False
-        G_file = False
-        
-        # Copiar archivo pth
-        for path, subdirs, files in os.walk(unzips_path):
-            for item in files:
-                item_path = os.path.join(path, item)
-                if not 'G_' in item and not 'D_' in item and item.endswith('.pth'):
-                    model_file = True
-                    model_name = item.replace(".pth","")
-                    logs_dir = os.path.join(parent_path,'logs', model_name)
-                    if os.path.exists(logs_dir):
-                        shutil.rmtree(logs_dir)
-                    os.mkdir(logs_dir)
-                    if not os.path.exists(weights_path):
-                        os.mkdir(weights_path)
-                    if os.path.exists(os.path.join(weights_path, item)):
-                        os.remove(os.path.join(weights_path, item))
-                    if os.path.exists(item_path):
-                        shutil.move(item_path, weights_path)
-        
-        if not model_file and not os.path.exists(logs_dir):
-            os.mkdir(logs_dir)
-        # Copiar index
-        for path, subdirs, files in os.walk(unzips_path):
-            for item in files:
-                item_path = os.path.join(path, item)
-                if item.startswith('added_') and item.endswith('.index'):
-                    index_file = True
-                    if os.path.exists(item_path):
-                        if os.path.exists(os.path.join(logs_dir, item)):
-                            os.remove(os.path.join(logs_dir, item))
-                        shutil.move(item_path, logs_dir)
-                if item.startswith('total_fea.npy') or item.startswith('events.'):
-                    if os.path.exists(item_path):
-                        if os.path.exists(os.path.join(logs_dir, item)):
-                            os.remove(os.path.join(logs_dir, item))
-                        shutil.move(item_path, logs_dir)
-        
-                
-        result = ""
-        if model_file:
-            if index_file:
-                print(i18n("该模型可用于推理，并有 .index 文件。"))
-                infos.append("\n" + i18n("该模型可用于推理，并有 .index 文件。"))
-                yield "\n".join(infos)
-            else:
-                print(i18n("该模型可用于推理，但没有 .index 文件。"))
-                infos.append("\n" + i18n("该模型可用于推理，但没有 .index 文件。"))
-                yield "\n".join(infos)
-        
-        if not index_file and not model_file:
-            print(i18n("未找到可上传的相关文件"))
-            infos.append(i18n("未找到可上传的相关文件"))
-            yield "\n".join(infos)
-        
-        if os.path.exists(zips_path):
-            shutil.rmtree(zips_path)
-        if os.path.exists(unzips_path):
-            shutil.rmtree(unzips_path)
-        os.chdir(parent_path)    
-        return result
-    except Exception as e:
-        os.chdir(parent_path)
-        if "demasiado uso" in str(e):
-            print(i18n("最近查看或下载此文件的用户过多"))
-            yield i18n("最近查看或下载此文件的用户过多")
-        elif "link privado" in str(e):
-            print(i18n("无法从该私人链接获取文件"))
-            yield i18n("无法从该私人链接获取文件")
-        else:
-            print(e)
-            yield i18n("下载模型时发生错误。")
-    finally:
-        os.chdir(parent_path)
-      
-def load_dowloaded_dataset(url):
-    parent_path = find_folder_parent(".", "pretrained_v2")
-    infos = []
-    try:
-        zips_path = os.path.join(parent_path, 'zips')
-        unzips_path = os.path.join(parent_path, 'unzips')
-        datasets_path = os.path.join(parent_path, 'datasets')
-        audio_extenions =["flac","wav"]
-        
-        if os.path.exists(zips_path):
-            shutil.rmtree(zips_path)
-        if os.path.exists(unzips_path):
-            shutil.rmtree(unzips_path)
-            
-        if not os.path.exists(datasets_path):
-            os.mkdir(datasets_path)
-            
-        os.mkdir(zips_path)
-        os.mkdir(unzips_path)
-        
-        download_file = download_from_url(url)
-        
-        if not download_file:
-            print(i18n("下载模型时发生错误。"))
-            infos.append(i18n("下载模型时发生错误。"))
-            yield "\n".join(infos)
-            raise Exception(i18n("下载模型时发生错误。"))
-        elif download_file == "downloaded":
-            print(i18n("模型下载成功。"))
-            infos.append(i18n("模型下载成功。"))
-            yield "\n".join(infos)
-        elif download_file == "demasiado uso":
-            raise Exception(i18n("最近查看或下载此文件的用户过多"))
-        elif download_file == "link privado":
-            raise Exception(i18n("无法从该私人链接获取文件"))
-  
-        zip_path = os.listdir(zips_path)
-        foldername = ""
-        for file in zip_path:
-            if file.endswith('.zip'):
-                file_path = os.path.join(zips_path, file)
-                print("....")
-                foldername = file.replace(".zip","").replace(" ","").replace("-","_")
-                dataset_path = os.path.join(datasets_path, foldername)
-                print(i18n("继续提取..."))
-                infos.append(i18n("继续提取..."))
-                yield "\n".join(infos)
-                shutil.unpack_archive(file_path, unzips_path, 'zip')
-                if os.path.exists(dataset_path):
-                    shutil.rmtree(dataset_path)
-                    
-                os.mkdir(dataset_path)
-                
-                for root, subfolders, songs in os.walk(unzips_path):
-                    for song in songs:
-                        song_path = os.path.join(root, song)
-                        if song.endswith(tuple(audio_extenions)):
-                            shutil.move(song_path, dataset_path)
-            else:
-                print(i18n("解压缩出错。"))
-                infos.append(i18n("解压缩出错。"))
-                yield "\n".join(infos)
-                
-                
-
-        if os.path.exists(zips_path):
-            shutil.rmtree(zips_path)
-        if os.path.exists(unzips_path):
-            shutil.rmtree(unzips_path)
-            
-        print(i18n("数据集加载成功。"))
-        infos.append(i18n("数据集加载成功。"))
-        yield "\n".join(infos)
-    except Exception as e:
-        os.chdir(parent_path)
-        if "demasiado uso" in str(e):
-            print(i18n("最近查看或下载此文件的用户过多"))
-            yield i18n("最近查看或下载此文件的用户过多")   
-        elif "link privado" in str(e):
-            print(i18n("无法从该私人链接获取文件"))
-            yield i18n("无法从该私人链接获取文件")
-        else:
-            print(e)
-            yield i18n("下载模型时发生错误。")
-    finally:
-        os.chdir(parent_path)
-
-def save_model(modelname, save_action):
-       
-    parent_path = find_folder_parent(".", "pretrained_v2")
-    zips_path = os.path.join(parent_path, 'zips')
-    dst = os.path.join(zips_path,modelname)
-    logs_path = os.path.join(parent_path, 'logs', modelname)
-    weights_path = os.path.join(parent_path, 'weights', f"{modelname}.pth")
-    save_folder = parent_path
-    infos = []    
-    
-    try:
-        if not os.path.exists(logs_path):
-            raise Exception("No model found.")
-        
-        if not 'content' in parent_path:
-            save_folder = os.path.join(parent_path, 'RVC_Backup')
-        else:
-            save_folder = '/content/drive/MyDrive/RVC_Backup'
-        
-        infos.append(i18n("保存模型..."))
-        yield "\n".join(infos)
-        
-        # Si no existe el folder RVC para guardar los modelos
-        if not os.path.exists(save_folder):
-            os.mkdir(save_folder)
-        if not os.path.exists(os.path.join(save_folder, 'ManualTrainingBackup')):
-            os.mkdir(os.path.join(save_folder, 'ManualTrainingBackup'))
-        if not os.path.exists(os.path.join(save_folder, 'Finished')):
-            os.mkdir(os.path.join(save_folder, 'Finished'))
-
-        # Si ya existe el folders zips borro su contenido por si acaso
-        if os.path.exists(zips_path):
-            shutil.rmtree(zips_path)
-            
-        os.mkdir(zips_path)
-        added_file = glob.glob(os.path.join(logs_path, "added_*.index"))
-        d_file = glob.glob(os.path.join(logs_path, "D_*.pth"))
-        g_file = glob.glob(os.path.join(logs_path, "G_*.pth"))
-        
-        if save_action == i18n("选择模型保存方法"):
-            raise Exception("No method choosen.")
-        
-        if save_action == i18n("保存所有"):
-            print(i18n("保存所有"))
-            save_folder = os.path.join(save_folder, 'ManualTrainingBackup')
-            shutil.copytree(logs_path, dst)
-        else:
-            # Si no existe el folder donde se va a comprimir el modelo
-            if not os.path.exists(dst):
-                os.mkdir(dst)
-            
-        if save_action == i18n("保存 D 和 G"):
-            print(i18n("保存 D 和 G"))
-            save_folder = os.path.join(save_folder, 'ManualTrainingBackup')
-            if len(d_file) > 0:
-                shutil.copy(d_file[0], dst)
-            if len(g_file) > 0:
-                shutil.copy(g_file[0], dst)    
-                
-            if len(added_file) > 0:
-                shutil.copy(added_file[0], dst)
-            else:
-                infos.append(i18n("保存时未编制索引..."))
-                
-        if save_action == i18n("保存声音"):
-            print(i18n("保存声音"))
-            save_folder = os.path.join(save_folder, 'Finished')
-            if len(added_file) > 0:
-                shutil.copy(added_file[0], dst)
-            else:
-                infos.append(i18n("保存时未编制索引..."))
-                #raise gr.Error("¡No ha generado el archivo added_*.index!")
-        
-        yield "\n".join(infos)
-        # Si no existe el archivo del modelo no copiarlo
-        if not os.path.exists(weights_path):
-            infos.append(i18n("无模型保存（PTH）"))
-            #raise gr.Error("¡No ha generado el modelo pequeño!")
-        else:
-            shutil.copy(weights_path, dst)
-        
-        yield "\n".join(infos)
-        infos.append("\n" + i18n("这可能需要几分钟时间，请稍候..."))
-        yield "\n".join(infos)
-        
-        shutil.make_archive(os.path.join(zips_path,f"{modelname}"), 'zip', zips_path)
-        shutil.move(os.path.join(zips_path,f"{modelname}.zip"), os.path.join(save_folder, f'{modelname}.zip'))
-        
-        shutil.rmtree(zips_path)
-        #shutil.rmtree(zips_path)
-        
-        infos.append("\n" + i18n("正确存储模型"))
-        yield "\n".join(infos)
-        
-    except Exception as e:
-        print(e)
-        if "No model found." in str(e):
-            infos.append(i18n("您要保存的模型不存在，请确保输入的名称正确。"))
-        else:
-            infos.append(i18n("保存模型时发生错误"))
-            
-        yield "\n".join(infos)
-    
-def load_downloaded_backup(url):
-    parent_path = find_folder_parent(".", "pretrained_v2")
-    try:
-        infos = []
-        logs_folders = ['0_gt_wavs','1_16k_wavs','2a_f0','2b-f0nsf','3_feature256','3_feature768']
-        zips_path = os.path.join(parent_path, 'zips')
-        unzips_path = os.path.join(parent_path, 'logs')
-        weights_path = os.path.join(parent_path, 'weights')
-        logs_dir = ""
-        
-        if os.path.exists(zips_path):
-            shutil.rmtree(zips_path)
-
-        os.mkdir(zips_path)
-        
-        download_file = download_from_url(url)
-        if not download_file:
-            print(i18n("无法下载模型。"))
-            infos.append(i18n("无法下载模型。"))
-            yield "\n".join(infos)
-        elif download_file == "downloaded":
-            print(i18n("模型下载成功。"))
-            infos.append(i18n("模型下载成功。"))
-            yield "\n".join(infos)
-        elif download_file == "demasiado uso":
-            raise Exception(i18n("最近查看或下载此文件的用户过多"))
-        elif download_file == "link privado":
-            raise Exception(i18n("无法从该私人链接获取文件"))
-        
-        # Descomprimir archivos descargados
-        for filename in os.listdir(zips_path):
-            if filename.endswith(".zip"):
-                zipfile_path = os.path.join(zips_path,filename)
-                zip_dir_name = os.path.splitext(filename)[0]
-                unzip_dir = os.path.join(parent_path,'logs', zip_dir_name)
-                print(i18n("继续提取..."))
-                infos.append(i18n("继续提取..."))
-                shutil.unpack_archive(zipfile_path, unzip_dir, 'zip')
-                yield "\n".join(infos)
-            else:
-                print(i18n("解压缩出错。"))
-                infos.append(i18n("解压缩出错。"))
-                yield "\n".join(infos)
-                
-        result = ""
-        
-        for filename in os.listdir(unzips_path):
-            if filename.endswith(".zip"):
-                silentremove(filename)
-        
-        if os.path.exists(zips_path):
-            shutil.rmtree(zips_path)
-        print(i18n("备份已成功上传。"))
-        infos.append("\n" + i18n("备份已成功上传。"))
-        yield "\n".join(infos)
-        os.chdir(parent_path)    
-        return result
-    except Exception as e:
-        os.chdir(parent_path)
-        if "demasiado uso" in str(e):
-            print(i18n("最近查看或下载此文件的用户过多"))
-            yield i18n("最近查看或下载此文件的用户过多")
-        elif "link privado" in str(e):
-            print(i18n("无法从该私人链接获取文件"))
-            yield i18n("无法从该私人链接获取文件") 
-        else:
-            print(e)
-            yield i18n("下载模型时发生错误。")
-    finally:
-        os.chdir(parent_path)
-
-def save_to_wav(record_button):
-    if record_button is None:
-        pass
-    else:
-        path_to_file=record_button
-        new_name = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")+'.wav'
-        new_path='./audios/'+new_name
-        shutil.move(path_to_file,new_path)
-        return new_name
-
-def save_to_wav2(dropbox):
-    file_path = dropbox.name
-    target_path = os.path.join('./audios', os.path.basename(file_path))
-
-    if os.path.exists(target_path):
-        os.remove(target_path)
-      # print('Replacing old dropdown file...')
-
-    shutil.move(file_path, target_path)
-    return target_path
-
-def change_choices2():
-    audio_paths=[]
-    for filename in os.listdir("./audios"):
-        if filename.endswith(('wav', 'mp3', 'flac', 'ogg', 'opus',
-                'm4a', 'mp4', 'aac', 'alac', 'wma',
-                'aiff', 'webm', 'ac3')):
-            audio_paths.append(os.path.join('./audios',filename).replace('\\', '/'))
-    return {"choices": sorted(audio_paths), "__type__": "update"}, {"__type__": "update"}
-
-def get_models_by_name(modelname):
-    url = "https://script.google.com/macros/s/AKfycbzyrdLZzUww9qbjxnbnI08budD4yxbmRPHkWbp3UEJ9h3Id5cnNNVg0UtfFAnqqX5Rr/exec"
-    
-    response = requests.post(url, json={
-        'type': 'search_by_filename',
-        'filename': unidecode(modelname.strip().lower())
-    })
-
-    response_json = response.json()
-    models = response_json['ocurrences']
-    
-    result = []
-    message = "Busqueda realizada"
-    if len(models) == 0:
-        message = "No se han encontrado resultados."
-    else:
-        message = f"Se han encontrado {len(models)} resultados para {modelname}"
-        
-    for i in range(20):
-        if i  < len(models):
-            urls = models[i].get('url')
-            url = eval(urls)[0]
-            name = str(models[i].get('name'))
-            filename = str(models[i].get('filename')) if not name or name.strip() == "" else name
-            # Nombre
-            result.append(
-                {
-                    "visible": True,
-                    "value": str("### ") + filename,
-                    "__type__": "update",
-                })
-            # Url
-            result.append(
-                {
-                    "visible": False,
-                    "value": url,
-                    "__type__": "update",
-                })
-            # Boton
-            result.append({
-                    "visible": True,
-                    "__type__": "update",
-                })
-            
-            # Linea separadora
-            if i == len(models) - 1:
-                result.append({
-                        "visible": False,
-                        "__type__": "update",
-                })
-            else:
-                result.append({
-                    "visible": True,
-                    "__type__": "update",
-                })
-                
-            # Row
-            result.append(
-                {
-                    "visible": True,
-                    "__type__": "update",
-                })
-        else:
-            # Nombre
-            result.append(
-                {
-                    "visible": False,
-                    "__type__": "update",
-                })
-            # Url
-            result.append(
-                {
-                    "visible": False,
-                    "value": False,
-                    "__type__": "update",
-                })
-            # Boton
-            result.append({
-                    "visible": False,
-                    "__type__": "update",
-                })
-            # Linea
-            result.append({
-                    "visible": False,
-                    "__type__": "update",
-                })
-            # Row
-            result.append(
-                {
-                    "visible": False,
-                    "__type__": "update",
-                })
-     # Result
-    result.append(
-        {
-            "value": message,
-            "__type__": "update",
-        }
-    )
-    
-    return result
-
-def search_model():
-    gr.Markdown(value="# Buscar un modelo")
-    with gr.Row():
-        model_name = gr.inputs.Textbox(lines=1, label="Término de búsqueda")
-        search_model_button=gr.Button("Buscar modelo")
-        
-    models = []
-    results = gr.Textbox(label="Resultado", value="", max_lines=20)
-    with gr.Row(visible=False) as row1:
-        l1 = gr.Markdown(value="", visible=False)
-        l1_url = gr.Textbox("Label 1", visible=False)
-        b1 = gr.Button("Cargar modelo", visible=False)
-    
-    mk1 = gr.Markdown(value="---", visible=False)
-    b1.click(fn=load_downloaded_model, inputs=l1_url, outputs=results)
-    
-    with gr.Row(visible=False) as row2:
-        l2 = gr.Markdown(value="", visible=False)
-        l2_url = gr.Textbox("Label 1", visible=False)
-        b2 = gr.Button("Cargar modelo", visible=False)
-    
-    mk2 = gr.Markdown(value="---", visible=False)
-    b2.click(fn=load_downloaded_model, inputs=l2_url, outputs=results)
-    
-    with gr.Row(visible=False) as row3:
-        l3 = gr.Markdown(value="", visible=False)
-        l3_url = gr.Textbox("Label 1", visible=False)
-        b3 = gr.Button("Cargar modelo", visible=False)
-    
-    mk3 = gr.Markdown(value="---", visible=False)
-    b3.click(fn=load_downloaded_model, inputs=l3_url, outputs=results)
-        
-    with gr.Row(visible=False) as row4:
-        l4 = gr.Markdown(value="", visible=False)
-        l4_url = gr.Textbox("Label 1", visible=False)
-        b4 = gr.Button("Cargar modelo", visible=False)
-    mk4 = gr.Markdown(value="---", visible=False)    
-    b4.click(fn=load_downloaded_model, inputs=l4_url, outputs=results)
-    
-    with gr.Row(visible=False) as row5:
-        l5 = gr.Markdown(value="", visible=False)
-        l5_url = gr.Textbox("Label 1", visible=False)
-        b5 = gr.Button("Cargar modelo", visible=False)
-    
-    mk5 = gr.Markdown(value="---", visible=False) 
-    b5.click(fn=load_downloaded_model, inputs=l5_url, outputs=results)
-        
-    with gr.Row(visible=False) as row6:
-        l6 = gr.Markdown(value="", visible=False)
-        l6_url = gr.Textbox("Label 1", visible=False)
-        b6 = gr.Button("Cargar modelo", visible=False)
-
-    mk6 = gr.Markdown(value="---", visible=False)        
-    b6.click(fn=load_downloaded_model, inputs=l6_url, outputs=results)
-        
-    with gr.Row(visible=False) as row7:
-        l7 = gr.Markdown(value="", visible=False)
-        l7_url = gr.Textbox("Label 1", visible=False)
-        b7 = gr.Button("Cargar modelo", visible=False)
-    
-    mk7 = gr.Markdown(value="---", visible=False)
-    b7.click(fn=load_downloaded_model, inputs=l7_url, outputs=results)
-        
-    with gr.Row(visible=False) as row8:
-        l8 = gr.Markdown(value="", visible=False)
-        l8_url = gr.Textbox("Label 1", visible=False)
-        b8 = gr.Button("Cargar modelo", visible=False)
-    
-    mk8 = gr.Markdown(value="---", visible=False)
-    b8.click(fn=load_downloaded_model, inputs=l8_url, outputs=results)
-        
-    with gr.Row(visible=False) as row9:
-        l9 = gr.Markdown(value="", visible=False)
-        l9_url = gr.Textbox("Label 1", visible=False)
-        b9 = gr.Button("Cargar modelo", visible=False)
-        
-    mk9 = gr.Markdown(value="---", visible=False)
-    b9.click(fn=load_downloaded_model, inputs=l9_url, outputs=results)
-        
-    with gr.Row(visible=False) as row10:
-        l10 = gr.Markdown(value="", visible=False)
-        l10_url = gr.Textbox("Label 1", visible=False)
-        b10 = gr.Button("Cargar modelo", visible=False)
-    
-    mk10 = gr.Markdown(value="---", visible=False) 
-    b10.click(fn=load_downloaded_model, inputs=l10_url, outputs=results)
-        
-    with gr.Row(visible=False) as row11:
-        l11 = gr.Markdown(value="", visible=False)
-        l11_url = gr.Textbox("Label 1", visible=False)
-        b11 = gr.Button("Cargar modelo", visible=False)
-        
-    mk11 = gr.Markdown(value="---", visible=False)
-    b11.click(fn=load_downloaded_model, inputs=l11_url, outputs=results)
-        
-    with gr.Row(visible=False) as row12:
-        l12 = gr.Markdown(value="", visible=False)
-        l12_url = gr.Textbox("Label 1", visible=False)
-        b12 = gr.Button("Cargar modelo", visible=False)
-
-    mk12 = gr.Markdown(value="---", visible=False)        
-    b12.click(fn=load_downloaded_model, inputs=l12_url, outputs=results)
-        
-    with gr.Row(visible=False) as row13:
-        l13 = gr.Markdown(value="", visible=False)
-        l13_url = gr.Textbox("Label 1", visible=False)
-        b13 = gr.Button("Cargar modelo", visible=False)
-    
-    mk13 = gr.Markdown(value="---", visible=False)
-    b13.click(fn=load_downloaded_model, inputs=l13_url, outputs=results)
-    
-    with gr.Row(visible=False) as row14:
-        l14 = gr.Markdown(value="", visible=False)
-        l14_url = gr.Textbox("Label 1", visible=False)
-        b14 = gr.Button("Cargar modelo", visible=False)
-    
-    mk14 = gr.Markdown(value="---", visible=False)
-    b14.click(fn=load_downloaded_model, inputs=l14_url, outputs=results)
-    
-    with gr.Row(visible=False) as row15:
-        l15 = gr.Markdown(value="", visible=False)
-        l15_url = gr.Textbox("Label 1", visible=False)
-        b15 = gr.Button("Cargar modelo", visible=False)
-
-    mk15 = gr.Markdown(value="---", visible=False)        
-    b15.click(fn=load_downloaded_model, inputs=l15_url, outputs=results)
-        
-    with gr.Row(visible=False) as row16:
-        l16 = gr.Markdown(value="", visible=False)
-        l16_url = gr.Textbox("Label 1", visible=False)
-        b16 = gr.Button("Cargar modelo", visible=False)
-        
-    mk16 = gr.Markdown(value="---", visible=False)
-    b16.click(fn=load_downloaded_model, inputs=l16_url, outputs=results)
-        
-    with gr.Row(visible=False) as row17:
-        l17 = gr.Markdown(value="", visible=False)
-        l17_url = gr.Textbox("Label 1", visible=False)
-        b17 = gr.Button("Cargar modelo", visible=False)
-    
-    mk17 = gr.Markdown(value="---", visible=False)    
-    b17.click(fn=load_downloaded_model, inputs=l17_url, outputs=results)
-        
-    with gr.Row(visible=False) as row18:
-        l18 = gr.Markdown(value="", visible=False)
-        l18_url = gr.Textbox("Label 1", visible=False)
-        b18 = gr.Button("Cargar modelo", visible=False)
-        
-    mk18 = gr.Markdown(value="---", visible=False)
-    b18.click(fn=load_downloaded_model, inputs=l18_url, outputs=results)
-        
-    with gr.Row(visible=False) as row19:
-        l19 = gr.Markdown(value="", visible=False)
-        l19_url = gr.Textbox("Label 1", visible=False)
-        b19 = gr.Button("Cargar modelo", visible=False)
-        
-    mk19 = gr.Markdown(value="---", visible=False)
-    b19.click(fn=load_downloaded_model, inputs=l19_url, outputs=results)
-        
-    with gr.Row(visible=False) as row20:
-        l20 = gr.Markdown(value="", visible=False)
-        l20_url = gr.Textbox("Label 1", visible=False)
-        b20 = gr.Button("Cargar modelo", visible=False)
-    
-    mk20 = gr.Markdown(value="---", visible=False)
-    b20.click(fn=load_downloaded_model, inputs=l20_url, outputs=results)
-    
-    #   to_return_protect1 = 
-
-    search_model_button.click(fn=get_models_by_name, inputs=model_name, outputs=[l1,l1_url, b1, mk1, row1,
-                                                                                 l2,l2_url, b2, mk2, row2,
-                                                                                 l3,l3_url, b3, mk3, row3,
-                                                                                 l4,l4_url, b4, mk4, row4,
-                                                                                 l5,l5_url, b5, mk5, row5,
-                                                                                 l6,l6_url, b6, mk6, row6,
-                                                                                 l7,l7_url, b7, mk7, row7,
-                                                                                 l8,l8_url, b8, mk8, row8,
-                                                                                 l9,l9_url, b9, mk9, row9,
-                                                                                 l10,l10_url, b10, mk10, row10,
-                                                                                 l11,l11_url, b11, mk11, row11,
-                                                                                 l12,l12_url, b12, mk12, row12,
-                                                                                 l13,l13_url, b13, mk13, row13,
-                                                                                 l14,l14_url, b14, mk14, row14,
-                                                                                 l15,l15_url, b15, mk15, row15,
-                                                                                 l16,l16_url, b16, mk16, row16,
-                                                                                 l17,l17_url, b17, mk17, row17,
-                                                                                 l18,l18_url, b18, mk18, row18,
-                                                                                 l19,l19_url, b19, mk19, row19,
-                                                                                 l20,l20_url, b20, mk20, row20,
-                                                                                 results
-                                                                                 ])
-    
-
-def descargar_desde_drive(url, name, output_file):
-
-    print(f"Descargando {name} de drive")
-    
-    try:
-        downloaded_file = gdown.download(url, output=output_file, fuzzy=True)
-        return downloaded_file
-    except:
-        print("El intento de descargar con drive no funcionó")
-        return None
-
-def descargar_desde_mega(url, name):
-  response = False
-  try:
-    file_id = None
-
-    if "#!" in url:
-      file_id = url.split("#!")[1].split("!")[0]
-    elif "file/" in url:
-      file_id = url.split("file/")[1].split("/")[0]
-    else:
-      file_id = None
-
-    if file_id:
-      mega = Mega()
-      m = mega.login()
-
-      print(f"Descargando {name} de mega")
-      downloaded_file = m.download_url(url)
-
-      return downloaded_file
-    else:
-      return None
-
-  except Exception as e:
-    print("Error**")
-    print(e)
-    return None
-
-def descargar_desde_url_basica(url, name, output_file):
-  try:
-    print(f"Descargando {name} de URL BASICA")
-    filename = wget.download(url=url, out=output_file)
-    return filename
-  except Exception as e:
-     print(f"Error al descargar el archivo: {str(e)}")
-
-def is_valid_model(name):
-  parent_path = find_folder_parent(".", "pretrained_v2")
-  unzips_path = os.path.join(parent_path, 'unzips')
-  
-  response = []
-  file_path = os.path.join(unzips_path, name)
-
-  has_model = False
-  has_index = False
-
-  for root, subfolders, files in os.walk(file_path):
-    for file in files:
-      current_file_path = os.path.join(root, file)
-      if not file.startswith("G_") and not file.startswith("D_") and file.endswith(".pth") and not "_G_" in file and not "_D_" in file:
-        has_model = True
-      if file.startswith('added_') and file.endswith('.index'):
-        has_index = True
-
-  #if has_model and has_index:
-  if has_index:
-    response.append(".index")
-
-  if has_model:
-    response.append(".pth")
-
-  return response
-
-
-def create_zip(new_name):
-    
-    parent_path = find_folder_parent(".", "pretrained_v2")
-    temp_folder_path = os.path.join(parent_path, 'temp_models')
-    unzips_path = os.path.join(parent_path, 'unzips')
-    zips_path = os.path.join(parent_path, 'zips')
-  
-    file_path = os.path.join(unzips_path, new_name)
-    file_name = os.path.join(temp_folder_path, new_name)
-
-    if not os.path.exists(zips_path):
-        os.mkdir(zips_path)
-
-    if os.path.exists(file_name):
-        shutil.rmtree(file_name)
-
-    os.mkdir(file_name)
-
-    while not os.path.exists(file_name):
-        time.sleep(1)
-
-    for root, subfolders, files in os.walk(file_path):
-        for file in files:
-            current_file_path = os.path.join(root, file)
-            if not file.startswith("G_") and not file.startswith("D_") and file.endswith(".pth") and not "_G_" in file and not "_D_" in file:
-                print(f'Copiando {current_file_path} a {os.path.join(temp_folder_path, new_name)}')
-                shutil.copy(current_file_path, file_name)
-            if file.startswith('added_') and file.endswith('.index'):
-                print(f'Copiando {current_file_path} a {os.path.join(temp_folder_path, new_name)}')
-                shutil.copy(current_file_path, file_name)
-
-    print("Comprimiendo modelo")
-    zip_path =  os.path.join(zips_path, new_name)
-    
-    print(f"Comprimiendo {file_name} en {zip_path}")
-    shutil.make_archive(zip_path, 'zip', file_name)
-  
-def upload_to_huggingface(file_path, new_filename):
-    api = HfApi()
-    login(token="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")
-    api.upload_file(
-        path_or_fileobj=file_path,
-        path_in_repo=new_filename,
-        repo_id="juuxn/RVCModels",
-        repo_type="model",
-    )
-    return f"https://huggingface.co/juuxn/RVCModels/resolve/main/{new_filename}"
-
-
-def publish_model_clicked(model_name, model_url, model_version, model_creator):
-    
-    web_service_url = "https://script.google.com/macros/s/AKfycbzyrdLZzUww9qbjxnbnI08budD4yxbmRPHkWbp3UEJ9h3Id5cnNNVg0UtfFAnqqX5Rr/exec"
-    name = unidecode(model_name)
-    new_name = unidecode(name.strip().replace(" ","_").replace("'",""))
-    
-    downloaded_path = ""
-    url = model_url
-    version = model_version
-    creator = model_creator
-    parent_path = find_folder_parent(".", "pretrained_v2")
-    output_folder = os.path.join(parent_path, 'archivos_descargados')
-    output_file = os.path.join(output_folder, f'{new_name}.zip')
-    unzips_path = os.path.join(parent_path, 'unzips')
-    zips_path = os.path.join(parent_path, 'zips')
-    temp_folder_path = os.path.join(parent_path, 'temp_models')
-    
-    if os.path.exists(output_folder):
-        shutil.rmtree(output_folder)
-    os.mkdir(output_folder)
-    
-    if os.path.exists(temp_folder_path):
-        shutil.rmtree(temp_folder_path)
-    os.mkdir(temp_folder_path)
-    
-    
-    if url and 'drive.google.com' in url:
-    # Descargar el elemento si la URL es de Google Drive
-        downloaded_path = descargar_desde_drive(url, new_name, output_file)
-    elif url and 'mega.nz' in url:
-        downloaded_path = descargar_desde_mega(url, new_name, output_file)
-    elif url and 'pixeldrain' in url:
-        print("No se puede descargar de pixeldrain")
-    else:
-        downloaded_path = descargar_desde_url_basica(url, new_name, output_file)
-        
-    if not downloaded_path:
-        print(f"No se pudo descargar: {name}")
-    else:
-        filename = name.strip().replace(" ","_")
-        dst =f'{filename}.zip'
-        shutil.unpack_archive(downloaded_path, os.path.join(unzips_path, filename))
-        md5_hash = get_md5(os.path.join(unzips_path, filename))
-
-        if not md5_hash:
-            print("No tiene modelo pequeño")
-            return
-
-        md5_response_raw = requests.post(web_service_url, json={
-            'type': 'check_md5',
-            'md5_hash': md5_hash
-        })
-        
-        md5_response = md5_response_raw.json()
-        ok = md5_response["ok"]
-        exists = md5_response["exists"]
-        message = md5_response["message"]
-
-        is_valid = is_valid_model(filename)
-        
-        if md5_hash and exists:
-            print(f"El archivo ya se ha publicado en spreadsheet con md5: {md5_hash}")
-            return f"El archivo ya se ha publicado con md5: {md5_hash}"
-        
-        if ".pth" in is_valid and not exists:
-
-            create_zip(filename)
-            huggingface_url = upload_to_huggingface(os.path.join(zips_path,dst), dst)
-                
-            response = requests.post(web_service_url, json={
-        'type': 'save_model',
-        'elements': [{
-                'name': name,
-                'filename': filename,
-                'url': [huggingface_url],
-                'version': version,
-                'creator': creator,
-                'md5_hash': md5_hash,
-                'content': is_valid
-            }]})
-            
-            response_data = response.json()
-            ok = response_data["ok"]
-            message = response_data["message"]
-
-            print({
-                'name': name,
-                'filename': filename,
-                'url': [huggingface_url],
-                'version': version,
-                'creator': creator,
-                'md5_hash': md5_hash,
-                'content': is_valid
-            })   
-            
-            if ok:
-                return f"El archivo se ha publicado con md5: {md5_hash}"
-            else:
-                print(message)
-                return message         
-            
-        # Eliminar folder donde se decarga el modelo zip
-        if os.path.exists(output_folder):
-            shutil.rmtree(output_folder)
-            
-        # Eliminar folder de zips, donde se descomprimio el modelo descargado
-        if os.path.exists(unzips_path):
-            shutil.rmtree(unzips_path)
-            
-        # Eliminar folder donde se copiaron los archivos indispensables del modelo
-        if os.path.exists(temp_folder_path):
-            shutil.rmtree(temp_folder_path)
-        
-        # Eliminar folder donde se comprimio el modelo para enviarse a huggingface
-        if os.path.exists(zips_path):
-            shutil.rmtree(zips_path)
-
-def uvr(input_url, output_path, model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format0):
-    def format_title(title):
-     formatted_title = title.replace(" ", "_")
-     return formatted_title
-
-    ydl_opts = {
-     'no-windows-filenames': True,
-     'restrict-filenames': True,
-     'extract_audio': True,
-     'format': 'bestaudio',
-     }
-
-    with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-     info_dict = ydl.extract_info(input_url, download=False)
-     formatted_title = format_title(info_dict.get('title', 'default_title'))
-     formatted_outtmpl = output_path + '/' + formatted_title + '.wav'
-     ydl_opts['outtmpl'] = formatted_outtmpl
-     ydl = yt_dlp.YoutubeDL(ydl_opts)
-     ydl.download([input_url])
-    
-    infos = []
-    try:
-        inp_root = inp_root.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
-        save_root_vocal = (
-            save_root_vocal.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
-        )
-        save_root_ins = (
-            save_root_ins.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
-        )
-        if model_name == "onnx_dereverb_By_FoxJoy":
-            pre_fun = MDXNetDereverb(15)
-        else:
-            func = _audio_pre_ if "DeEcho" not in model_name else _audio_pre_new
-            pre_fun = func(
-                agg=int(agg),
-                model_path=os.path.join(weight_uvr5_root, model_name + ".pth"),
-                device=config.device,
-                is_half=config.is_half,
-            )
-        if inp_root != "":
-            paths = [os.path.join(inp_root, name) for name in os.listdir(inp_root)]
-        else:
-            paths = [path.name for path in paths]
-        for path in paths:
-            inp_path = os.path.join(inp_root, path)
-            need_reformat = 1
-            done = 0
-            try:
-                info = ffmpeg.probe(inp_path, cmd="ffprobe")
-                if (
-                    info["streams"][0]["channels"] == 2
-                    and info["streams"][0]["sample_rate"] == "44100"
-                ):
-                    need_reformat = 0
-                    pre_fun._path_audio_(
-                        inp_path, save_root_ins, save_root_vocal, format0
-                    )
-                    done = 1
-            except:
-                need_reformat = 1
-                traceback.print_exc()
-            if need_reformat == 1:
-                tmp_path = "%s/%s.reformatted.wav" % (tmp, os.path.basename(inp_path))
-                os.system(
-                    "ffmpeg -i %s -vn -acodec pcm_s16le -ac 2 -ar 44100 %s -y"
-                    % (inp_path, tmp_path)
-                )
-                inp_path = tmp_path
-            try:
-                if done == 0:
-                    pre_fun._path_audio_(
-                        inp_path, save_root_ins, save_root_vocal, format0
-                    )
-                infos.append("%s->Success" % (os.path.basename(inp_path)))
-                yield "\n".join(infos)
-            except:
-                infos.append(
-                    "%s->%s" % (os.path.basename(inp_path), traceback.format_exc())
-                )
-                yield "\n".join(infos)
-    except:
-        infos.append(traceback.format_exc())
-        yield "\n".join(infos)
-    finally:
-        try:
-            if model_name == "onnx_dereverb_By_FoxJoy":
-                del pre_fun.pred.model
-                del pre_fun.pred.model_
-            else:
-                del pre_fun.model
-                del pre_fun
-        except:
-            traceback.print_exc()
-        print("clean_empty_cache")
-        if torch.cuda.is_available():
-            torch.cuda.empty_cache()
-    yield "\n".join(infos)
-
-            
-def publish_models():
-    with gr.Column():
-        gr.Markdown("# Publicar un modelo en la comunidad")
-        gr.Markdown("El modelo se va a verificar antes de publicarse. Importante que contenga el archivo **.pth** del modelo para que no sea rechazado.")
-        
-        model_name = gr.inputs.Textbox(lines=1, label="Nombre descriptivo del modelo Ej: (Ben 10 [Latino] - RVC V2 - 250 Epoch)")
-        url = gr.inputs.Textbox(lines=1, label="Enlace del modelo")
-        moder_version = gr.Radio(
-            label="Versión",
-            choices=["RVC v1", "RVC v2"],
-            value="RVC v1",
-            interactive=True,
-        )
-        model_creator = gr.inputs.Textbox(lines=1, label="ID de discord del creador del modelo Ej: <@123455656>")
-        publish_model_button=gr.Button("Publicar modelo")
-        results = gr.Textbox(label="Resultado", value="", max_lines=20)
-        
-        publish_model_button.click(fn=publish_model_clicked, inputs=[model_name, url, moder_version, model_creator], outputs=results)
-
-def download_model():
-    gr.Markdown(value="# " + i18n("下载模型"))
-    gr.Markdown(value=i18n("它用于下载您的推理模型。"))
-    with gr.Row():
-        model_url=gr.Textbox(label=i18n("网址"))
-    with gr.Row():
-        download_model_status_bar=gr.Textbox(label=i18n("地位"))
-    with gr.Row():
-        download_button=gr.Button(i18n("下载"))
-        download_button.click(fn=load_downloaded_model, inputs=[model_url], outputs=[download_model_status_bar])
-
-def download_backup():
-    gr.Markdown(value="# " + i18n("下载备份"))
-    gr.Markdown(value=i18n("它用于下载您的训练备份。"))
-    with gr.Row():
-        model_url=gr.Textbox(label=i18n("网址"))
-    with gr.Row():
-        download_model_status_bar=gr.Textbox(label=i18n("地位"))
-    with gr.Row():
-        download_button=gr.Button(i18n("下载"))
-        download_button.click(fn=load_downloaded_backup, inputs=[model_url], outputs=[download_model_status_bar])
-
-def update_dataset_list(name):
-    new_datasets = []
-    for foldername in os.listdir("./datasets"):
-        if "." not in foldername:
-            new_datasets.append(os.path.join(find_folder_parent(".","pretrained"),"datasets",foldername))
-    return gr.Dropdown.update(choices=new_datasets)
-
-def download_dataset(trainset_dir4):
-    gr.Markdown(value="# " + i18n("下载数据集"))
-    gr.Markdown(value=i18n("下载兼容格式（.wav/.flac）的音频数据集以训练模型。"))
-    with gr.Row():
-        dataset_url=gr.Textbox(label=i18n("网址"))
-    with gr.Row():
-        load_dataset_status_bar=gr.Textbox(label=i18n("地位"))
-    with gr.Row():
-        load_dataset_button=gr.Button(i18n("下载"))
-        load_dataset_button.click(fn=load_dowloaded_dataset, inputs=[dataset_url], outputs=[load_dataset_status_bar])
-        load_dataset_status_bar.change(update_dataset_list, dataset_url, trainset_dir4)
-    
-def youtube_separator():
-        input_url = gr.inputs.Textbox(label="Pega el enlace de youtube")
-        output_path = gr.Textbox(
-            label=i18n("输入待处理音频文件夹路径(去文件管理器地址栏拷就行了)"),
-            value=os.path.abspath(os.getcwd()).replace('\\', '/') + "/yt_downloads/",
-            visible=False,
-            )
-        dir_wav_input = gr.Textbox(
-            label=i18n("输入待处理音频文件夹路径"),
-            value=((os.getcwd()).replace('\\', '/') + "/yt_downloads"),
-            visible=False,
-            )
-        model_choose = gr.Textbox(
-            value=os.path.abspath(os.getcwd()).replace('\\', '/') + "/uvr5_weights/HP5_only_main_vocal",
-            visible=False,
-            )
-        opt_vocal_root = gr.Textbox(
-            label=i18n("指定输出主人声文件夹"), value="audios",
-            visible=False,
-            )
-        opt_ins_root = gr.Textbox(
-            label=i18n("指定输出非主人声文件夹"), value="opt",
-            visible=False,
-            )
-        format0 = gr.Radio(
-            label=i18n("导出文件格式"),
-            choices=["wav", "flac", "mp3", "m4a"],
-            value="wav",
-            interactive=True,
-            visible=False,
-            )
-        but2 = gr.Button(i18n("转换"))
-        vc_output4 = gr.Textbox(label=i18n("输出信息"))
-        but2.click(
-                uvr,
-                    [
-                    input_url, 
-                    output_path,
-                    model_choose,
-                    dir_wav_input,
-                    opt_vocal_root,
-                    opt_ins_root,
-                    format0,
-                            ],
-                    [vc_output4],
-                )