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| import re | |
| import gradio as gr | |
| import torch | |
| import unicodedata | |
| import commons | |
| import utils | |
| from models import SynthesizerTrn | |
| from text import text_to_sequence | |
| config_json = "muse_tricolor_b.json" | |
| pth_path = "G=869.pth" | |
| def get_text(text, hps, cleaned=False): | |
| if cleaned: | |
| text_norm = text_to_sequence(text, hps.symbols, []) | |
| else: | |
| text_norm = text_to_sequence(text, hps.symbols, hps.data.text_cleaners) | |
| if hps.data.add_blank: | |
| text_norm = commons.intersperse(text_norm, 0) | |
| text_norm = torch.LongTensor(text_norm) | |
| return text_norm | |
| def get_label(text, label): | |
| if f'[{label}]' in text: | |
| return True, text.replace(f'[{label}]', '') | |
| else: | |
| return False, text | |
| def clean_text(text): | |
| print(text) | |
| jap = re.compile(r'[\u3040-\u309F\u30A0-\u30FF]') # 匹配日文 | |
| text = unicodedata.normalize('NFKC', text) | |
| text = f"[JA]{text}[JA]" if jap.search(text) else f"[ZH]{text}[ZH]" | |
| return text | |
| def load_model(config_json, pth_path): | |
| dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") | |
| hps_ms = utils.get_hparams_from_file(f"{config_json}") | |
| n_speakers = hps_ms.data.n_speakers if 'n_speakers' in hps_ms.data.keys() else 0 | |
| n_symbols = len(hps_ms.symbols) if 'symbols' in hps_ms.keys() else 0 | |
| net_g_ms = SynthesizerTrn( | |
| n_symbols, | |
| hps_ms.data.filter_length // 2 + 1, | |
| hps_ms.train.segment_size // hps_ms.data.hop_length, | |
| n_speakers=n_speakers, | |
| **hps_ms.model).to(dev) | |
| _ = net_g_ms.eval() | |
| _ = utils.load_checkpoint(pth_path, net_g_ms) | |
| return net_g_ms | |
| net_g_ms = load_model(config_json, pth_path) | |
| def selection(speaker): | |
| if speaker == "南小鸟": | |
| spk = 0 | |
| return spk | |
| elif speaker == "园田海未": | |
| spk = 1 | |
| return spk | |
| elif speaker == "小泉花阳": | |
| spk = 2 | |
| return spk | |
| elif speaker == "星空凛": | |
| spk = 3 | |
| return spk | |
| elif speaker == "东条希": | |
| spk = 4 | |
| return spk | |
| elif speaker == "矢泽妮可": | |
| spk = 5 | |
| return spk | |
| elif speaker == "绚濑绘里": | |
| spk = 6 | |
| return spk | |
| elif speaker == "西木野真姬": | |
| spk = 7 | |
| return spk | |
| elif speaker == "高坂穗乃果": | |
| spk = 8 | |
| return spk | |
| def infer(text,speaker_id, n_scale= 0.667,n_scale_w = 0.8, l_scale = 1 ): | |
| text = clean_text(text) | |
| speaker_id = int(selection(speaker_id)) | |
| dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") | |
| hps_ms = utils.get_hparams_from_file(f"{config_json}") | |
| with torch.no_grad(): | |
| stn_tst = get_text(text, hps_ms, cleaned=False) | |
| x_tst = stn_tst.unsqueeze(0).to(dev) | |
| x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).to(dev) | |
| sid = torch.LongTensor([speaker_id]).to(dev) | |
| audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=n_scale, noise_scale_w=n_scale_w, length_scale=l_scale)[0][ | |
| 0, 0].data.cpu().float().numpy() | |
| return (hps_ms.data.sampling_rate, audio) | |
| idols = ["南小鸟","园田海未","小泉花阳","星空凛","东条希","矢泽妮可","绚濑绘里","西木野真姬","高坂穗乃果"] | |
| app = gr.Blocks() | |
| with app: | |
| with gr.Tabs(): | |
| with gr.TabItem("Basic"): | |
| tts_input1 = gr.TextArea(label="请输入纯中文或纯日文", value="大家好") | |
| para_input1 = gr.Slider(minimum= 0.01,maximum=1.0,label="更改噪声比例", value=0.667) | |
| para_input2 = gr.Slider(minimum= 0.01,maximum=1.0,label="更改噪声偏差", value=0.8) | |
| para_input3 = gr.Slider(minimum= 0.1,maximum=10,label="更改时间比例", value=1) | |
| tts_submit = gr.Button("Generate", variant="primary") | |
| speaker1 = gr.Dropdown(label="选择说话人",choices=idols, value="高坂穗乃果", interactive=True) | |
| tts_output2 = gr.Audio(label="Output") | |
| tts_submit.click(infer, [tts_input1,speaker1,para_input1,para_input2,para_input3], [tts_output2]) | |
| app.launch() | |