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import gradio as gr
import edge_tts
import asyncio
import librosa
import soundfile
import io
from inference.infer_tool import Svc
def get_or_create_eventloop():
try:
return asyncio.get_event_loop()
except RuntimeError as ex:
if "There is no current event loop in thread" in str(ex):
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
return asyncio.get_event_loop()
def tts_get_voices_list():
voices = []
tts_voice_list = asyncio.get_event_loop().run_until_complete(edge_tts.list_voices())
for item in tts_voice_list:
voices.append(item['ShortName'])
return voices
def tts_mode(txt, voice):
tts = asyncio.run(edge_tts.Communicate(txt, voice).save('temp\\test.mp3'))
audio, sr = librosa.load('temp\\test.mp3', sr=16000, mono=True)
raw_path = io.BytesIO()
soundfile.write(raw_path, audio, 16000, format="wav")
raw_path.seek(0)
model = Svc(fr"Herta-Svc/G_10000.pth", f"Herta-Svc/config.json", device = 'cpu')
out_audio, out_sr = model.infer('speaker0', 0, raw_path, auto_predict_f0 = True,)
soundfile.write('temp\\xxx.wav', out_audio.cpu().numpy(), 44100)
audio_file = open('temp\\xxx.wav', 'rb')
audio_bytes = audio_file.read()
return audio_bytes
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
with gr.Blocks() as app:
gr.Markdown("TEST.")
with gr.Row():
tts_text = gr.Textbox(label="TTS text (100 words limitation)")
tts_voice = gr.Dropdown(choices= tts_get_voices_list(), visible=False)
submit_btn = gr.Button("Generate", variant="primary")
with gr.Column():
audio_output = gr.Audio(label="Output Audio")
submit_btn.click(tts_mode, [tts_text, tts_voice], [audio_output])
app.queue(concurrency_count=1).launch() |