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