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import gradio as gr
import numpy as np
import torch
from pathlib import Path
import tempfile
from TTS.api import TTS
from TTS.utils.manage import ModelManager
title = ""
description = """"""
article = """"""
class TTS_local(TTS):
def __init__(self, model_name=None, output_prefix: str = './', progress_bar: bool = True, gpu=False):
super().__init__(
model_name=None,
model_path=None,
config_path=None,
vocoder_path=None,
vocoder_config_path=None,
progress_bar=progress_bar,
gpu=False,
)
self.manager = ModelManager(models_file=self.get_models_file_path(), output_prefix=output_prefix, progress_bar=progress_bar, verbose=False)
if model_name is not None:
if "tts_models" in model_name or "coqui_studio" in model_name:
self.load_tts_model_by_name(model_name, gpu)
elif "voice_conversion_models" in model_name:
self.load_vc_model_by_name(model_name, gpu)
device = "cuda" if torch.cuda.is_available() else "cpu"
GPU = device == "cuda"
INT16MAX = np.iinfo(np.int16).max
MODEL_DIR = './'
MANAGER = ModelManager(verbose=False)
model_ids = MANAGER.list_models()
local_model_ids = [p.parts[-1].replace('--', '/') for p in (Path(MODEL_DIR) / 'tts').glob('*') if p.is_dir() and (p.parts[-1].replace('--', '/') in model_ids)]
model_tts_ids = [model for model in local_model_ids if 'tts_models' in model and ('/multilingual/' in model or '/en/' in model)]
model_vocoder_ids = [model for model in local_model_ids if 'vocoder_models' in model and ('/universal/' in model or '/en/' in model)]
model_vconv_ids = [model for model in local_model_ids if 'voice_conversion_models' in model and ('/multilingual/' in model or '/en/' in model)]
VC_MODEL = TTS_local(model_name='voice_conversion_models/multilingual/vctk/freevc24',
output_prefix=MODEL_DIR, progress_bar=False, gpu=GPU)
examples_pt = 'examples'
allowed_extentions = ['.mp3', '.wav']
examples = {f.name: f for f in Path(examples_pt).glob('*') if f.suffix in allowed_extentions}
verse = """Mary had a little lamb,
Its fleece was white as snow.
Everywhere the child went,
The little lamb was sure to go."""
def on_model_tts_select(model_name):
tts_var = TTS(model_name=model_name, progress_bar=False, gpu=GPU)
languages = tts_var.languages if tts_var.is_multi_lingual else ['']
speakers = [s.replace('\n', '-n') for s in tts_var.speakers] if tts_var.is_multi_speaker else [''] # there's weird speaker formatting
language = languages[0]
speaker = speakers[0]
return tts_var, gr.update(choices=languages, value=language, interactive=tts_var.is_multi_lingual),\
gr.update(choices=speakers, value=speaker, interactive=tts_var.is_multi_speaker)
def on_voicedropdown(x):
return examples[x]
def voice_clone(source_wav, target_wav):
print(f'model: {VC_MODEL.model_name}\nsource_wav: {source_wav}\ntarget_wav: {target_wav}')
sample_rate = VC_MODEL.voice_converter.output_sample_rate
if source_wav is None or target_wav is None:
return (sample_rate, np.zeros(0).astype(np.int16))
speech = VC_MODEL.voice_conversion(source_wav=source_wav, target_wav=target_wav)
speech = (np.array(speech) * INT16MAX).astype(np.int16)
return (sample_rate, speech)
def text_to_speech(text, tts_model, language, speaker, target_wav, use_original_voice):
if len(text.strip()) == 0 or tts_model is None or (target_wav is None and not use_original_voice):
return (16000, np.zeros(0).astype(np.int16))
sample_rate = tts_model.synthesizer.output_sample_rate
if tts_model.is_multi_speaker:
speaker = {s.replace('\n', '-n'): s for s in tts_model.speakers}[speaker] # there's weird speaker formatting
print(f'model: {tts_model.model_name}\nlanguage: {language}\nspeaker: {speaker}')
language = None if language == '' else language
speaker = None if speaker == '' else speaker
if use_original_voice:
print('Using original voice')
speech = tts_model.tts(text, language=language, speaker=speaker)
elif tts_model.synthesizer.tts_model.speaker_manager and tts_model.synthesizer.tts_model.speaker_manager.encoder_ap:
print('voice cloning with the tts')
speech = tts_model.tts(text, language=language, speaker_wav=target_wav)
else:
print('voice cloning with the voice conversion model')
# speech = tts_model.tts_with_vc(text, language=language, speaker_wav=target_wav)
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
# Lazy code... save it to a temp file to resample it while reading it for VC
tts_model.tts_to_file(text, language=language, speaker=speaker, file_path=fp.name)
speech = VC_MODEL.voice_conversion(source_wav=fp.name, target_wav=target_wav)
sample_rate = VC_MODEL.voice_converter.output_sample_rate
speech = (np.array(speech) * INT16MAX).astype(np.int16)
return (sample_rate, speech)
with gr.Blocks() as demo:
tts_model = gr.State(None)
def activate(*args):
return gr.update(interactive=True) if len(args) == 1 else [gr.update(interactive=True)] * len(args)
def deactivate(*args):
return gr.update(interactive=False) if len(args) == 1 else [gr.update(interactive=False)] * len(args)
gr.Markdown(description)
with gr.Row(equal_height=True):
with gr.Column(scale=5, min_width=50):
model_tts_dropdown = gr.Dropdown(model_tts_ids, value=None, label='Text-to-speech model', interactive=True)
with gr.Column(scale=1, min_width=10):
language_dropdown = gr.Dropdown(None, value=None, label='Language', interactive=False, visible=True)
with gr.Column(scale=1, min_width=10):
speaker_dropdown = gr.Dropdown(None, value=None, label='Speaker', interactive=False, visible=True)
with gr.Accordion("Target voice", open=False) as accordion:
gr.Markdown("Upload target voice...")
with gr.Row(equal_height=True):
voice_upload = gr.Audio(label='Upload target voice', source='upload', type='filepath')
voice_dropdown = gr.Dropdown(examples, label='Examples', interactive=True)
with gr.Row(equal_height=True):
with gr.Column(scale=2):
with gr.Row(equal_height=True):
with gr.Column():
text_to_convert = gr.Textbox(verse)
orig_voice = gr.Checkbox(label='Use original voice')
voice_to_convert = gr.Audio(label="Upload voice to convert", source='upload', type='filepath')
with gr.Row(equal_height=True):
button_text = gr.Button('Text to speech', interactive=True)
button_audio = gr.Button('Convert audio', interactive=True)
with gr.Row(equal_height=True):
speech = gr.Audio(label='Converted Speech', type='numpy', visible=True, interactive=False)
# actions
model_tts_dropdown.change(deactivate, [button_text, button_audio], [button_text, button_audio]).\
then(fn=on_model_tts_select, inputs=[model_tts_dropdown], outputs=[tts_model, language_dropdown, speaker_dropdown]).\
then(activate, [button_text, button_audio], [button_text, button_audio])
voice_dropdown.change(deactivate, [button_text, button_audio], [button_text, button_audio]).\
then(fn=on_voicedropdown, inputs=voice_dropdown, outputs=voice_upload).\
then(activate, [button_text, button_audio], [button_text, button_audio])
button_text.click(deactivate, [button_text, button_audio], [button_text, button_audio]).\
then(fn=text_to_speech, inputs=[text_to_convert, tts_model, language_dropdown, speaker_dropdown, voice_upload, orig_voice],
outputs=speech).\
then(activate, [button_text, button_audio], [button_text, button_audio])
button_audio.click(deactivate, [button_text, button_audio], [button_text, button_audio]).\
then(fn=voice_clone, inputs=[voice_to_convert, voice_upload], outputs=speech).\
then(activate, [button_text, button_audio], [button_text, button_audio])
gr.HTML(article)
demo.launch(share=False) |