Spaces:
Running
Running
File size: 6,325 Bytes
604b23b c140265 604b23b c140265 604b23b 34de65c 604b23b c140265 604b23b c140265 604b23b c140265 604b23b c140265 604b23b c140265 604b23b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 |
import spaces
import os
import random
import argparse
import torch
import gradio as gr
import numpy as np
import ChatTTS
import OpenVoice.se_extractor as se_extractor
from OpenVoice.api import ToneColorConverter
import soundfile
print("loading ChatTTS 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 chat_tts(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag, refine_text_input, output_path=None):
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:
if refine_text_input:
params_refine_text['prompt'] = refine_text_input
text = chat.infer(text,
skip_refine_text=False,
refine_text_only=True,
params_refine_text=params_refine_text,
params_infer_code=params_infer_code
)
print("Text has been refined!")
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 = 22050
text_data = text[0] if isinstance(text, list) else text
if output_path is None:
return [(sample_rate, audio_data), text_data]
else:
soundfile.write(output_path, audio_data, sample_rate)
return text_data
# OpenVoice Clone
ckpt_converter_en = 'checkpoints/converter'
device = 'cuda:0'
#device = "cpu"
tone_color_converter = ToneColorConverter(f'{ckpt_converter_en}/config.json', device=device)
tone_color_converter.load_ckpt(f'{ckpt_converter_en}/checkpoint.pth')
def generate_audio(text, audio_ref, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag, refine_text_input):
save_path = "output.wav"
if audio_ref != "" :
# Run the base speaker tts
src_path = "tmp.wav"
text_data = chat_tts(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag, refine_text_input, src_path)
print("Ready for voice cloning!")
source_se, audio_name = se_extractor.get_se(src_path, tone_color_converter, target_dir='processed', vad=True)
reference_speaker = audio_ref
target_se, audio_name = se_extractor.get_se(reference_speaker, tone_color_converter, target_dir='processed', vad=True)
print("Get voices segment!")
# Run the tone color converter
# convert from file
tone_color_converter.convert(
audio_src_path=src_path,
src_se=source_se,
tgt_se=target_se,
output_path=save_path)
else:
chat_tts(text, temperature, top_P, top_K, audio_seed_input, text_seed_input, refine_text_flag, refine_text_input, save_path)
print("Finished!")
return [save_path, text_data]
with gr.Blocks() as demo:
gr.Markdown("# <center>🥳 ChatTTS x OpenVoice 🥳</center>")
gr.Markdown("## <center>🌟 Make it sound super natural and switch it up to any voice you want, nailing the mood and tone also!🌟 </center>")
gr.Markdown("### <center>💕 Slide on over to [linkin.love](https://linkin.love) for a chat-fest with your AI buds!💕</center>")
default_text = "Today a man knocked on my door and asked for a small donation toward the local swimming pool. I gave him a glass of water."
text_input = gr.Textbox(label="Input Text", lines=4, placeholder="Please Input Text...", value=default_text)
default_refine_text = "[oral_2][laugh_0][break_6]"
refine_text_checkbox = gr.Checkbox(label="Refine text", info="'oral' means add filler words, 'laugh' means add laughter, and 'break' means add a pause. (0-10) ", value=True)
refine_text_input = gr.Textbox(label="Refine Prompt", lines=1, placeholder="Please Refine Prompt...", value=default_refine_text)
with gr.Column():
voice_ref = gr.Audio(label="Reference Audio", info="Click on the ✎ button to upload your own target speaker audio", type="filepath", value="examples/speaker.mp3")
with gr.Row():
temperature_slider = gr.Slider(minimum=0.00001, maximum=1.0, step=0.00001, value=0.3, label="Audio temperature")
top_p_slider = gr.Slider(minimum=0.1, maximum=0.9, step=0.05, value=0.7, label="top_P")
top_k_slider = gr.Slider(minimum=1, maximum=20, step=1, value=20, label="top_K")
with gr.Row():
audio_seed_input = gr.Number(value=42, label="Speaker Seed")
generate_audio_seed = gr.Button("\U0001F3B2")
text_seed_input = gr.Number(value=42, label="Text Seed")
generate_text_seed = gr.Button("\U0001F3B2")
generate_button = gr.Button("Generate")
text_output = gr.Textbox(label="Refined Text", interactive=False)
audio_output = gr.Audio(label="Output Audio")
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, voice_ref, temperature_slider, top_p_slider, top_k_slider, audio_seed_input, text_seed_input, refine_text_checkbox, refine_text_input],
outputs=[audio_output,text_output])
parser = argparse.ArgumentParser(description='ChatTTS-OpenVoice Launch')
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() |