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)