239 lines
9.9 KiB
Python
239 lines
9.9 KiB
Python
|
import os
|
||
|
|
import torch
|
||
|
|
import argparse
|
||
|
|
import gradio as gr
|
||
|
|
from zipfile import ZipFile
|
||
|
|
import langid
|
||
|
|
import se_extractor
|
||
|
|
from api import BaseSpeakerTTS, ToneColorConverter
|
||
|
|
|
||
|
|
parser = argparse.ArgumentParser()
|
||
|
|
parser.add_argument("--share", action='store_true', default=False, help="make link public")
|
||
|
|
args = parser.parse_args()
|
||
|
|
|
||
|
|
en_ckpt_base = 'checkpoints/base_speakers/EN'
|
||
|
|
ckpt_converter = 'checkpoints/converter'
|
||
|
|
device = 'cuda' if torch.cuda.is_available() else 'cpu'
|
||
|
|
output_dir = 'outputs'
|
||
|
|
os.makedirs(output_dir, exist_ok=True)
|
||
|
|
|
||
|
|
# load models
|
||
|
|
en_base_speaker_tts = BaseSpeakerTTS(f'{en_ckpt_base}/config.json', device=device)
|
||
|
|
en_base_speaker_tts.load_ckpt(f'{en_ckpt_base}/checkpoint.pth')
|
||
|
|
tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device=device)
|
||
|
|
tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth')
|
||
|
|
|
||
|
|
# load speaker embeddings
|
||
|
|
en_source_default_se = torch.load(f'{en_ckpt_base}/en_default_se.pth').to(device)
|
||
|
|
en_source_style_se = torch.load(f'{en_ckpt_base}/en_style_se.pth').to(device)
|
||
|
|
|
||
|
|
# This online demo mainly supports English and Chinese
|
||
|
|
supported_languages = ['en']
|
||
|
|
|
||
|
|
def predict(prompt, style, audio_file_pth, agree):
|
||
|
|
# initialize a empty info
|
||
|
|
text_hint = ''
|
||
|
|
|
||
|
|
# first detect the input language
|
||
|
|
language_predicted = langid.classify(prompt)[0].strip()
|
||
|
|
print(f"Detected language:{language_predicted}")
|
||
|
|
|
||
|
|
if language_predicted not in supported_languages:
|
||
|
|
text_hint += f"[ERROR] The detected language {language_predicted} for your input text is not in our Supported Languages: {supported_languages}\n"
|
||
|
|
gr.Warning(
|
||
|
|
f"The detected language {language_predicted} for your input text is not in our Supported Languages: {supported_languages}"
|
||
|
|
)
|
||
|
|
|
||
|
|
return (
|
||
|
|
text_hint,
|
||
|
|
None,
|
||
|
|
None,
|
||
|
|
)
|
||
|
|
else:
|
||
|
|
tts_model = en_base_speaker_tts
|
||
|
|
if style == 'default':
|
||
|
|
source_se = en_source_default_se
|
||
|
|
else:
|
||
|
|
source_se = en_source_style_se
|
||
|
|
language = 'English'
|
||
|
|
if style not in ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']:
|
||
|
|
text_hint += f"[ERROR] The style {style} is not supported for English, which should be in ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']\n"
|
||
|
|
gr.Warning(f"The style {style} is not supported for English, which should be in ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']")
|
||
|
|
return (
|
||
|
|
text_hint,
|
||
|
|
None,
|
||
|
|
None,
|
||
|
|
)
|
||
|
|
|
||
|
|
speaker_wav = audio_file_pth
|
||
|
|
|
||
|
|
if len(prompt) < 2:
|
||
|
|
text_hint += f"[ERROR] Please give a longer prompt text \n"
|
||
|
|
gr.Warning("Please give a longer prompt text")
|
||
|
|
return (
|
||
|
|
text_hint,
|
||
|
|
None,
|
||
|
|
None,
|
||
|
|
)
|
||
|
|
|
||
|
|
# note diffusion_conditioning not used on hifigan (default mode), it will be empty but need to pass it to model.inference
|
||
|
|
try:
|
||
|
|
target_se, audio_name = se_extractor.get_se(speaker_wav, tone_color_converter, target_dir='processed', vad=True)
|
||
|
|
except Exception as e:
|
||
|
|
text_hint += f"[ERROR] Get target tone color error {str(e)} \n"
|
||
|
|
gr.Warning(
|
||
|
|
"[ERROR] Get target tone color error {str(e)} \n"
|
||
|
|
)
|
||
|
|
return (
|
||
|
|
text_hint,
|
||
|
|
None,
|
||
|
|
None,
|
||
|
|
)
|
||
|
|
|
||
|
|
src_path = f'{output_dir}/tmp.wav'
|
||
|
|
tts_model.tts(prompt, src_path, speaker=style, language=language)
|
||
|
|
|
||
|
|
save_path = f'{output_dir}/output.wav'
|
||
|
|
# Run the tone color converter
|
||
|
|
encode_message = "@MyShell"
|
||
|
|
tone_color_converter.convert(
|
||
|
|
audio_src_path=src_path,
|
||
|
|
src_se=source_se,
|
||
|
|
tgt_se=target_se,
|
||
|
|
output_path=save_path,
|
||
|
|
message=encode_message)
|
||
|
|
|
||
|
|
text_hint += f'''Get response successfully \n'''
|
||
|
|
|
||
|
|
return (
|
||
|
|
text_hint,
|
||
|
|
save_path,
|
||
|
|
speaker_wav,
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
title = "MyShell OpenVoice"
|
||
|
|
|
||
|
|
description = """
|
||
|
|
We introduce OpenVoice, a versatile instant voice cloning approach that requires only a short audio clip from the reference speaker to replicate their voice and generate speech in multiple languages. OpenVoice enables granular control over voice styles, including emotion, accent, rhythm, pauses, and intonation, in addition to replicating the tone color of the reference speaker. OpenVoice also achieves zero-shot cross-lingual voice cloning for languages not included in the massive-speaker training set.
|
||
|
|
"""
|
||
|
|
|
||
|
|
markdown_table = """
|
||
|
|
<div align="center" style="margin-bottom: 10px;">
|
||
|
|
|
||
|
|
| | | |
|
||
|
|
| :-----------: | :-----------: | :-----------: |
|
||
|
|
| **OpenSource Repo** | **Project Page** | **Join the Community** |
|
||
|
|
| <div style='text-align: center;'><a style="display:inline-block,align:center" href='https://github.com/myshell-ai/OpenVoice'><img src='https://img.shields.io/github/stars/myshell-ai/OpenVoice?style=social' /></a></div> | [OpenVoice](https://research.myshell.ai/open-voice) | [](https://discord.gg/myshell) |
|
||
|
|
|
||
|
|
</div>
|
||
|
|
"""
|
||
|
|
|
||
|
|
markdown_table_v2 = """
|
||
|
|
<div align="center" style="margin-bottom: 2px;">
|
||
|
|
|
||
|
|
| | | | |
|
||
|
|
| :-----------: | :-----------: | :-----------: | :-----------: |
|
||
|
|
| **OpenSource Repo** | <div style='text-align: center;'><a style="display:inline-block,align:center" href='https://github.com/myshell-ai/OpenVoice'><img src='https://img.shields.io/github/stars/myshell-ai/OpenVoice?style=social' /></a></div> | **Project Page** | [OpenVoice](https://research.myshell.ai/open-voice) |
|
||
|
|
|
||
|
|
| | |
|
||
|
|
| :-----------: | :-----------: |
|
||
|
|
**Join the Community** | [](https://discord.gg/myshell) |
|
||
|
|
|
||
|
|
</div>
|
||
|
|
"""
|
||
|
|
content = """
|
||
|
|
<div>
|
||
|
|
<strong>If the generated voice does not sound like the reference voice, please refer to <a href='https://github.com/myshell-ai/OpenVoice/blob/main/docs/QA.md'>this QnA</a>.</strong> <strong>For multi-lingual & cross-lingual examples, please refer to <a href='https://github.com/myshell-ai/OpenVoice/blob/main/demo_part2.ipynb'>this jupyter notebook</a>.</strong>
|
||
|
|
This online demo mainly supports <strong>English</strong>. The <em>default</em> style also supports <strong>Chinese</strong>. But OpenVoice can adapt to any other language as long as a base speaker is provided.
|
||
|
|
</div>
|
||
|
|
"""
|
||
|
|
wrapped_markdown_content = f"<div style='border: 1px solid #000; padding: 10px;'>{content}</div>"
|
||
|
|
|
||
|
|
|
||
|
|
examples = [
|
||
|
|
[
|
||
|
|
"今天天气真好，我们一起出去吃饭吧。",
|
||
|
|
'default',
|
||
|
|
"resources/demo_speaker1.mp3",
|
||
|
|
True,
|
||
|
|
],[
|
||
|
|
"This audio is generated by open voice with a half-performance model.",
|
||
|
|
'whispering',
|
||
|
|
"resources/demo_speaker2.mp3",
|
||
|
|
True,
|
||
|
|
],
|
||
|
|
[
|
||
|
|
"He hoped there would be stew for dinner, turnips and carrots and bruised potatoes and fat mutton pieces to be ladled out in thick, peppered, flour-fattened sauce.",
|
||
|
|
'sad',
|
||
|
|
"resources/demo_speaker0.mp3",
|
||
|
|
True,
|
||
|
|
],
|
||
|
|
]
|
||
|
|
|
||
|
|
with gr.Blocks(analytics_enabled=False) as demo:
|
||
|
|
|
||
|
|
with gr.Row():
|
||
|
|
with gr.Column():
|
||
|
|
with gr.Row():
|
||
|
|
gr.Markdown(
|
||
|
|
"""
|
||
|
|
## <img src="https://huggingface.co/spaces/myshell-ai/OpenVoice/raw/main/logo.jpg" height="40"/>
|
||
|
|
"""
|
||
|
|
)
|
||
|
|
with gr.Row():
|
||
|
|
gr.Markdown(markdown_table_v2)
|
||
|
|
with gr.Row():
|
||
|
|
gr.Markdown(description)
|
||
|
|
with gr.Column():
|
||
|
|
gr.Video('https://github.com/myshell-ai/OpenVoice/assets/40556743/3cba936f-82bf-476c-9e52-09f0f417bb2f', autoplay=True)
|
||
|
|
|
||
|
|
with gr.Row():
|
||
|
|
gr.HTML(wrapped_markdown_content)
|
||
|
|
|
||
|
|
with gr.Row():
|
||
|
|
with gr.Column():
|
||
|
|
input_text_gr = gr.Textbox(
|
||
|
|
label="Text Prompt",
|
||
|
|
info="One or two sentences at a time is better. Up to 200 text characters.",
|
||
|
|
value="He hoped there would be stew for dinner, turnips and carrots and bruised potatoes and fat mutton pieces to be ladled out in thick, peppered, flour-fattened sauce.",
|
||
|
|
)
|
||
|
|
style_gr = gr.Dropdown(
|
||
|
|
label="Style",
|
||
|
|
info="Select a style of output audio for the synthesised speech. (Chinese only support 'default' now)",
|
||
|
|
choices=['default', 'whispering', 'cheerful', 'terrified', 'angry', 'sad', 'friendly'],
|
||
|
|
max_choices=1,
|
||
|
|
value="default",
|
||
|
|
)
|
||
|
|
ref_gr = gr.Audio(
|
||
|
|
label="Reference Audio",
|
||
|
|
info="Click on the ✎ button to upload your own target speaker audio",
|
||
|
|
type="filepath",
|
||
|
|
value="resources/demo_speaker2.mp3",
|
||
|
|
)
|
||
|
|
tos_gr = gr.Checkbox(
|
||
|
|
label="Agree",
|
||
|
|
value=False,
|
||
|
|
info="I agree to the terms of the cc-by-nc-4.0 license-: https://github.com/myshell-ai/OpenVoice/blob/main/LICENSE",
|
||
|
|
)
|
||
|
|
|
||
|
|
tts_button = gr.Button("Send", elem_id="send-btn", visible=True)
|
||
|
|
|
||
|
|
|
||
|
|
with gr.Column():
|
||
|
|
out_text_gr = gr.Text(label="Info")
|
||
|
|
audio_gr = gr.Audio(label="Synthesised Audio", autoplay=True)
|
||
|
|
ref_audio_gr = gr.Audio(label="Reference Audio Used")
|
||
|
|
|
||
|
|
gr.Examples(examples,
|
||
|
|
label="Examples",
|
||
|
|
inputs=[input_text_gr, style_gr, ref_gr, tos_gr],
|
||
|
|
outputs=[out_text_gr, audio_gr, ref_audio_gr],
|
||
|
|
fn=predict,
|
||
|
|
cache_examples=False,)
|
||
|
|
tts_button.click(predict, [input_text_gr, style_gr, ref_gr, tos_gr], outputs=[out_text_gr, audio_gr, ref_audio_gr])
|
||
|
|
|
||
|
|
demo.queue()
|
||
|
|
demo.launch(server_name='0.0.0.0', server_port=7862, debug=True, show_api=True, share=False)
|