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app.py
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app.py
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import gradio as gr
import torch
import platform
import random
import json
from pathlib import Path
from TTS.api import TTS
import uuid
import html
import soundfile as sf
def is_mac_os():
return platform.system() == 'Darwin'
params = {
"activate": True,
"autoplay": True,
"show_text": True,
"remove_trailing_dots": False,
"voice": "钢铁侠.wav",
"language": "Chinese",
"model_name": "tts_models/multilingual/multi-dataset/xtts_v2",
}
# SUPPORTED_FORMATS = ['wav', 'mp3', 'flac', 'ogg']
SAMPLE_RATE = 16000
device = None
# Set the default speaker name
default_speaker_name = "钢铁侠"
if is_mac_os():
device = torch.device('cpu')
else:
device = torch.device('cuda:0')
# Load model
tts = TTS(model_name=params["model_name"]).to(device)
# # Random sentence (assuming harvard_sentences.txt is in the correct path)
# def random_sentence():
# with open(Path("harvard_sentences.txt")) as f:
# return random.choice(list(f))
# Voice generation function
def gen_voice(string, spk, speed, english):
string = html.unescape(string)
short_uuid = str(uuid.uuid4())[:8]
fl_name='outputs/' + spk + "-" + short_uuid +'.wav'
output_file = Path(fl_name)
this_dir = str(Path(__file__).parent.resolve())
tts.tts_to_file(
text=string,
speed=speed,
file_path=output_file,
speaker_wav=[f"{this_dir}/targets/" +spk + ".wav"],
language=languages[english]
)
return output_file
def update_speakers():
speakers = {p.stem: str(p) for p in list(Path('targets').glob("*.wav"))}
return list(speakers.keys())
def update_dropdown(_=None, selected_speaker=default_speaker_name):
return gr.Dropdown(choices=update_speakers(), value=selected_speaker, label="Select Speaker")
def handle_recorded_audio(audio_data, speaker_dropdown, filename = "user_entered"):
if not audio_data:
return speaker_dropdown
sample_rate, audio_content = audio_data
save_path = f"targets/{filename}.wav"
# Write the audio content to a WAV file
sf.write(save_path, audio_content, sample_rate)
# Create a new Dropdown with the updated speakers list, including the recorded audio
updated_dropdown = update_dropdown(selected_speaker=filename)
return updated_dropdown
# Load the language data
with open(Path('languages.json'), encoding='utf8') as f:
languages = json.load(f)
# Gradio Blocks interface
with gr.Blocks() as app:
gr.Markdown("### TTS based Voice Cloning.")
with gr.Row():
with gr.Column():
text_input = gr.Textbox(lines=2, label="文本",value="事实上,我就是钢铁侠")
speed_slider = gr.Slider(label='语速', minimum=0.1, maximum=1.99, value=0.8, step=0.01)
language_dropdown = gr.Dropdown(list(languages.keys()), label="语言", value="Chinese")
gr.Markdown("### Speaker Selection and Voice Cloning")
with gr.Row():
with gr.Column():
speaker_dropdown = update_dropdown()
refresh_button = gr.Button("Refresh Speakers")
with gr.Column():
filename_input = gr.Textbox(label="Add new Speaker", placeholder="输入角色名称")
save_button = gr.Button("保存角色")
refresh_button.click(fn=update_dropdown, inputs=[], outputs=speaker_dropdown)
with gr.Row():
record_button = gr.Audio(label="开启录音")
save_button.click(fn=handle_recorded_audio, inputs=[record_button, speaker_dropdown, filename_input], outputs=speaker_dropdown)
record_button.stop_recording(fn=handle_recorded_audio, inputs=[record_button, filename_input], outputs=speaker_dropdown)
record_button.upload(fn=handle_recorded_audio, inputs=[record_button, filename_input], outputs=speaker_dropdown)
submit_button = gr.Button("推理")
with gr.Column():
audio_output = gr.Audio()
submit_button.click(
fn=gen_voice,
inputs=[text_input, speaker_dropdown, speed_slider, language_dropdown],
outputs=audio_output
)
if __name__ == "__main__":
app.launch()