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Configuration error
# coding=utf-8 | |
import sys | |
import os | |
run_dir = os.path.dirname(os.path.realpath(__file__)) | |
sys.path.append(run_dir) | |
import re | |
import argparse | |
import utils | |
import commons | |
import json | |
import torch | |
from models import SynthesizerTrn | |
from text import text_to_sequence, _clean_text | |
from torch import no_grad, LongTensor | |
import logging | |
logging.getLogger('numba').setLevel(logging.WARNING) | |
limitation = os.getenv("SYSTEM") == "spaces" # limit text and audio length in huggingface spaces | |
import scipy | |
hps_ms = utils.get_hparams_from_file(f'{run_dir}/config/config.json') | |
device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu') | |
tts_fn = None | |
voice_opt = (0.6, 0.668, 1) | |
def get_text(text, hps, is_symbol): | |
text_norm, clean_text = 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, clean_text | |
def create_tts_fn(net_g_ms, speaker_id): | |
def tts_fn(text, language, noise_scale, noise_scale_w, length_scale, is_symbol): | |
text = text.replace('\n', ' ').replace('\r', '').replace(" ", "") | |
if limitation: | |
text_len = len(re.sub("\[([A-Z]{2})\]", "", text)) | |
max_len = 100 | |
if is_symbol: | |
max_len *= 3 | |
if text_len > max_len: | |
return "Error: Text is too long", None | |
if not is_symbol: | |
if language == 0: | |
text = f"[ZH]{text}[ZH]" | |
elif language == 1: | |
text = f"[JA]{text}[JA]" | |
else: | |
text = f"{text}" | |
stn_tst, clean_text = get_text(text, hps_ms, is_symbol) | |
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_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale, noise_scale_w=noise_scale_w, | |
length_scale=length_scale)[0][0, 0].data.cpu().float().numpy() | |
return "Success", (22050, audio) | |
return tts_fn | |
def create_to_symbol_fn(hps): | |
def to_symbol_fn(is_symbol_input, input_text, temp_lang): | |
if temp_lang == 0: | |
clean_text = f'[ZH]{input_text}[ZH]' | |
elif temp_lang == 1: | |
clean_text = f'[JA]{input_text}[JA]' | |
else: | |
clean_text = input_text | |
return _clean_text(clean_text, hps.data.text_cleaners) if is_symbol_input else '' | |
return to_symbol_fn | |
def _LoadCharacter(name): | |
with open(f"{run_dir}/pretrained_models/info.json", "r", encoding="utf-8") as f: | |
models_info = json.load(f) | |
for i, info in models_info.items(): | |
sid = info['sid'] | |
name_en = info['name_en'] | |
name_zh = info['name_zh'] | |
title = info['title'] | |
cover = f"{run_dir}/pretrained_models/{i}/{info['cover']}" | |
example = info['example'] | |
language = info['language'] | |
if name == 'Any' or name == name_zh or name == name_en: | |
net_g_ms = SynthesizerTrn( | |
len(hps_ms.symbols), | |
hps_ms.data.filter_length // 2 + 1, | |
hps_ms.train.segment_size // hps_ms.data.hop_length, | |
n_speakers=hps_ms.data.n_speakers if info['type'] == "multi" else 0, | |
**hps_ms.model) | |
utils.load_checkpoint(f'{run_dir}/pretrained_models/{i}/{i}.pth', net_g_ms, None) | |
_ = net_g_ms.eval().to(device) | |
tts_fn = create_tts_fn(net_g_ms, sid) | |
to_symbol_fn = create_to_symbol_fn(hps_ms) | |
return True, tts_fn | |
return False, None | |
def LoadCharacter(name): | |
global tts_fn | |
_, tts_fn = _LoadCharacter(name) | |
def SetVoiceOption(ns, nsw, ls): | |
global voice_opt | |
voice_opt = (ns, nsw, ls) | |
LoadCharacter("Any") | |
def GenerateTTS(text): | |
if tts_fn != None and voice_opt != None: | |
(ns, nsw, ls) = voice_opt | |
symbol_input = False | |
result, (sampling_rate, output) = tts_fn(text, 0, ns, nsw, ls, symbol_input) | |
if result == "Success": | |
save_path = f"{run_dir}/output.wav" | |
scipy.io.wavfile.write(save_path, rate=sampling_rate, data=output.T) | |
return True, save_path | |
else: | |
print(f'TTS: {result}') | |
return False, None | |
__all__ = ['LoadCharacter', 'SetVoiceOption', 'GenerateTTS'] | |