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import utils
from models import SynthesizerTrn
import torch
from torch import no_grad, LongTensor
from text import text_to_sequence
import gradio as gr
import commons
model_path = "./OUTPUT_MODEL/G_SakuraMiko.pth"
config_path = "./OUTPUT_MODEL/config.json"
length = 1.0
device = "cuda:0" if torch.cuda.is_available() else "cpu"
def get_text(text, hps, is_symbol):
text_norm = text_to_sequence(text, hps.symbols, [] if is_symbol else hps.data.text_cleaners)
if hps.data.add_blank:
text_norm = commons.intersperse(text_norm, 0)
text_norm = LongTensor(text_norm)
return text_norm
def get_vits_array(text):
hps = utils.get_hparams_from_file(config_path)
net_g = SynthesizerTrn(
len(hps.symbols),
hps.data.filter_length // 2 + 1,
hps.train.segment_size // hps.data.hop_length,
n_speakers=hps.data.n_speakers,
**hps.model).to(device)
_ = net_g.eval()
_ = utils.load_checkpoint(model_path, net_g, None)
speaker_ids = hps.speakers
#text = "[JA]" + text + "[JA]"
speaker_id = 0
stn_tst = get_text(text, hps, False)
with no_grad():
x_tst = stn_tst.unsqueeze(0).to(device)
x_tst_lengths = LongTensor([stn_tst.size(0)]).to(device)
sid = LongTensor([speaker_id]).to(device)
audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=.667, noise_scale_w=0.6,
length_scale=1.0 / length)[0][0, 0].data.cpu().float().numpy()
del stn_tst, x_tst, x_tst_lengths, sid
return (hps.data.sampling_rate, audio)
app = gr.Blocks()
with app:
gr.Markdown("# VITS-TTS-Japanese-Only-Sakura-Miko\n\n"
"Dataset from [Elite35P-Server/EliteVoiceProject](https://huggingface.co/datasets/Elite35P-Server/EliteVoiceProject) \n"
"Sample usage of Finetune model [Lycoris53/Vits-Japanese-Only-Sakura-Miko](https://huggingface.co/Lycoris53/Vits-TTS-Japanese-Only-Sakura-Miko) \n"
"Base finetuning code is from [Plachtaa/VITS-fast-fine-tuning](https://github.com/Plachtaa/VITS-fast-fine-tuning)"
)
with gr.Row():
with gr.Column():
textbox = gr.TextArea(label="Text",
placeholder="Type your sentence here (Maximum 150 words)",
value="おはようございます。")
with gr.Column():
audio_output = gr.Audio(label="Output Audio")
btn = gr.Button("Generate Voice!")
btn.click(get_vits_array,
inputs=[textbox],
outputs=[audio_output])
app.queue(concurrency_count=3).launch() |