Spaces:
Runtime error
Runtime error
| # coding:utf-8 | |
| import re | |
| import torch | |
| import unicodedata | |
| from pydub import AudioSegment | |
| from scipy.io.wavfile import write | |
| import commons | |
| import config | |
| import utils | |
| from models import SynthesizerTrn | |
| from text import text_to_sequence | |
| pth_path = config.pth_path | |
| config_json = config.config_json | |
| def wav2mp3(file_name): | |
| sourcefile = AudioSegment.from_wav(f"{file_name}.wav") | |
| sourcefile.export(f"{file_name}.mp3", format="mp3") | |
| 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): | |
| jap = re.compile(r'[\u3040-\u309F\u30A0-\u30FF\uAC00-\uD7A3]') # \uAC00-\uD7A3为匹配韩文的，其余为日文 | |
| text = f"[JA]{text}[JA]" if jap.search(text) else f"[ZH]{text}[ZH]" | |
| text = unicodedata.normalize('NFKC', text) | |
| 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"./configs/{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, hps_ms | |
| def infer(text, net_g_ms, speaker_id, out_name): | |
| dev = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") | |
| hps_ms = utils.get_hparams_from_file(f"./configs/{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=0.667, noise_scale_w=0.8, length_scale=1)[0][ | |
| 0, 0].data.cpu().float().numpy() | |
| write(f"{out_name}.wav", hps_ms.data.sampling_rate, audio) | |
| wav2mp3(out_name) | |
| return audio | |
| if __name__ == "__main__": | |
| out_name = "水调歌头" | |
| speaker_id = 0 | |
| text = "明月几时有，把酒问青天。不知天上宫阙，今夕是何年。我欲乘风归去，又恐琼楼玉宇，高处不胜寒。" | |
| text = clean_text(text) | |
| net_g_ms = load_model(config_json, pth_path) | |
| infer(text, net_g_ms, speaker_id, out_name) | |