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import os
import re
import random
from scipy.io.wavfile import write
from scipy.io.wavfile import read
import numpy as np
import gradio as gr
import yt_dlp
import subprocess
from pydub import AudioSegment
from audio_separator.separator import Separator
from lib.infer import infer_audio
import edge_tts
import tempfile
import anyio
from pathlib import Path
from lib.language_tts import language_dict
import os
import zipfile
import shutil
import urllib.request
import gdown
import subprocess
import time
from argparse import ArgumentParser
from download_model import download_online_model
main_dir = Path().resolve()
os.chdir(main_dir)
models_dir = main_dir / "rvc_models"
def extract_zip(extraction_folder, zip_name):
os.makedirs(extraction_folder)
with zipfile.ZipFile(zip_name, 'r') as zip_ref:
zip_ref.extractall(extraction_folder)
os.remove(zip_name)
index_filepath, model_filepath = None, None
for root, dirs, files in os.walk(extraction_folder):
for name in files:
if name.endswith('.index') and os.stat(os.path.join(root, name)).st_size > 1024 * 100:
index_filepath = os.path.join(root, name)
if name.endswith('.pth') and os.stat(os.path.join(root, name)).st_size > 1024 * 1024 * 40:
model_filepath = os.path.join(root, name)
if not model_filepath:
raise Exception(f'No .pth model file was found in the extracted zip. Please check {extraction_folder}.')
# move model and index file to extraction folder
os.rename(model_filepath, os.path.join(extraction_folder, os.path.basename(model_filepath)))
if index_filepath:
os.rename(index_filepath, os.path.join(extraction_folder, os.path.basename(index_filepath)))
# remove any unnecessary nested folders
for filepath in os.listdir(extraction_folder):
if os.path.isdir(os.path.join(extraction_folder, filepath)):
shutil.rmtree(os.path.join(extraction_folder, filepath))
def download_online_model(url, dir_name, models_dir='./rvc_models'):
try:
print(f'[~] Downloading voice model with name {dir_name}...')
zip_name = url.split('/')[-1]
extraction_folder = os.path.join(models_dir, dir_name)
if os.path.exists(extraction_folder):
return f'[!] Voice model directory {dir_name} already exists! Choose a different name for your voice model.'
# Download from pixeldrain
if 'pixeldrain.com' in url:
url = f'https://pixeldrain.com/api/file/{zip_name}'
urllib.request.urlretrieve(url, zip_name)
# Download from Google Drive
elif 'drive.google.com' in url:
zip_name = dir_name + ".zip"
gdown.download(url, output=zip_name, use_cookies=True, quiet=True)
else:
# General URL download
urllib.request.urlretrieve(url, zip_name)
print(f'[~] Extracting zip file...')
extract_zip(extraction_folder, zip_name)
print(f'[+] {dir_name} Model successfully downloaded!')
# Return success message after successful download
return f"[+] {dir_name} Model successfully downloaded!"
except Exception as e:
# Return the error message instead of raising an exception
return f'[!] Error: {str(e)}'
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