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import zipfile
import shutil
import gdown
import gradio as gr
import spaces
import torch
from rvc_engine.infer import voice_convert
MODEL_DIR = "models"
os.makedirs(
MODEL_DIR,
exist_ok=True
)
print("CUDA:", torch.cuda.is_available())
if torch.cuda.is_available():
print(
"GPU:",
torch.cuda.get_device_name(0)
)
def download_model(drive_url):
zip_path = "model.zip"
if os.path.exists(zip_path):
os.remove(zip_path)
try:
gdown.download(
drive_url,
zip_path,
quiet=False
)
except Exception as e:
return None, None, f"خطأ تحميل الموديل: {str(e)}"
if not os.path.exists(zip_path):
return None, None, "فشل تحميل ملف ZIP"
extract_dir = os.path.join(
MODEL_DIR,
"current"
)
if os.path.exists(extract_dir):
shutil.rmtree(extract_dir)
os.makedirs(
extract_dir,
exist_ok=True
)
try:
with zipfile.ZipFile(zip_path, "r") as z:
z.extractall(extract_dir)
except Exception as e:
return None, None, f"خطأ فك الضغط: {str(e)}"
pth = None
index = None
for root, dirs, files in os.walk(extract_dir):
for file in files:
if file.endswith(".pth"):
pth = os.path.join(
root,
file
)
if file.endswith(".index"):
index = os.path.join(
root,
file
)
if not pth or not index:
return None, None, (
"لم يتم العثور على ملفات "
".pth و .index"
)
return (
pth,
index,
"تم تحميل الموديل بنجاح"
)
@spaces.GPU
def convert(audio, model_url):
if not audio:
return None, "يرجى رفع ملف صوتي"
if not model_url:
return None, "ضع رابط Google Drive للموديل"
pth, index, status = download_model(
model_url
)
if not pth:
return None, status
output = "output.wav"
try:
result = voice_convert(
audio,
pth,
index,
output
)
return (
result,
"تم التحويل بنجاح"
)
except Exception as e:
return (
None,
f"خطأ في محرك RVC: {str(e)}"
)
with gr.Blocks() as demo:
gr.Markdown(
"# 🎙️ RVC Voice Converter"
)
audio = gr.Audio(
type="filepath",
label="الصوت الأصلي"
)
model_url = gr.Textbox(
label="رابط Google Drive للموديل ZIP",
placeholder="ملف ZIP يحتوي pth و index"
)
button = gr.Button(
"تحويل الصوت"
)
output = gr.Audio(
label="الصوت الناتج"
)
info = gr.Textbox(
label="الحالة"
)
button.click(
convert,
inputs=[
audio,
model_url
],
outputs=[
output,
info
]
)
demo.launch() |