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import spaces
import os
import random
import argparse
import torch
import gradio as gr
import numpy as np
import ChatTTS
print("loading TTS model...")
chat = ChatTTS.Chat()
chat.load_models()
def generate_seed():
new_seed = random.randint(1, 100000000)
return {
"__type__": "update",
"value": new_seed
}
@spaces.GPU
def generate_audio(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag):
torch.manual_seed(audio_seed_input)
rand_spk = torch.randn(768)
params_infer_code = {
'spk_emb': rand_spk,
'temperature': temperature,
'top_P': top_P,
'top_K': top_K,
}
params_refine_text = {'prompt': '[oral_2][laugh_0][break_6]'}
torch.manual_seed(text_seed_input)
if refine_text_flag:
text = chat.infer(text,
skip_refine_text=False,
refine_text_only=True,
params_refine_text=params_refine_text,
params_infer_code=params_infer_code
)
wav = chat.infer(text,
skip_refine_text=True,
params_refine_text=params_refine_text,
params_infer_code=params_infer_code
)
audio_data = np.array(wav[0]).flatten()
sample_rate = 24000
text_data = text[0] if isinstance(text, list) else text
return [(sample_rate, audio_data), text_data]
with gr.Blocks() as demo:
gr.Markdown("#Next Generation TTS")
default_text = "英伟达投的Sora竞品免费了，网友挤爆服务器，120秒120帧支持垫图。这个新推出的模型名为Dream Machine，现已推出免费公开测试版，支持文生视频、图生视频。"
text_input = gr.Textbox(label="Input Text", lines=4, placeholder="Please Input Text...", value=default_text)
with gr.Row():
refine_text_checkbox = gr.Checkbox(label="Refine text", value=True, visible=False)
temperature_slider = gr.Slider(minimum=0.00001, maximum=1.0, step=0.00001, value=0.3, label="Audio temperature", visible=False)
top_p_slider = gr.Slider(minimum=0.1, maximum=0.9, step=0.05, value=0.7, label="top_P", visible=False)
top_k_slider = gr.Slider(minimum=1, maximum=20, step=1, value=20, label="top_K", visible=False)
with gr.Row():
audio_seed_input = gr.Number(value=42, label="Audio Seed", visible=False)
generate_audio_seed = gr.Button("\U0001F3B2", visible=False)
text_seed_input = gr.Number(value=42, label="Text Seed", visible=False)
generate_text_seed = gr.Button("\U0001F3B2", visible=False)
generate_button = gr.Button("Generate")
text_output = gr.Textbox(label="Output Text", interactive=False)
audio_output = gr.Audio(label="Output Audio",autoplay=True)
generate_audio_seed.click(generate_seed,
inputs=[],
outputs=audio_seed_input)
generate_text_seed.click(generate_seed,
inputs=[],
outputs=text_seed_input)
generate_button.click(generate_audio,
inputs=[text_input, temperature_slider, top_p_slider, top_k_slider, audio_seed_input, text_seed_input, refine_text_checkbox],
outputs=[audio_output, text_output])
parser = argparse.ArgumentParser(description='Next Generation TTS Online')
parser.add_argument('--server_name', type=str, default='0.0.0.0', help='Server name')
parser.add_argument('--server_port', type=int, default=8080, help='Server port')
args = parser.parse_args()
# demo.launch(server_name=args.server_name, server_port=args.server_port, inbrowser=True)
if __name__ == '__main__':
demo.launch(share=True, show_api=False) |