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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: | |
with gr.Tabs(): | |
with gr.TabItem('Herta'): | |
tts_text = gr.Textbox(label="TTS text (100 words limitation)", visible = True) | |
tts_voice = gr.Dropdown(choices= tts_get_voices_list(), visible = True) | |
audio_output = gr.Audio(label="Output Audio") | |
btn_submit = gr.Button("Generate") | |
btn_submit.click(tts_mode, [tts_text, tts_voice], [audio_output]) | |
app.launch() |