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This commit is contained in:
litagin02
2024-03-11 09:47:47 +09:00
parent 42ee7d7608
commit c776c08235
31 changed files with 463 additions and 298 deletions
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137
style_bert_vits2/tts_model.py
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@@ -25,7 +25,9 @@ from style_bert_vits2.constants import (
from style_bert_vits2.models.hyper_parameters import HyperParameters
from style_bert_vits2.models.infer import get_net_g, infer
from style_bert_vits2.models.models import SynthesizerTrn
from style_bert_vits2.models.models_jp_extra import SynthesizerTrn as SynthesizerTrnJPExtra
from style_bert_vits2.models.models_jp_extra import (
SynthesizerTrn as SynthesizerTrnJPExtra,
)
from style_bert_vits2.logging import logger
from style_bert_vits2.voice import adjust_voice
@@ -36,7 +38,6 @@ class TTSModel:
モデル/ハイパーパラメータ/スタイルベクトルのパスとデバイスを指定して初期化し、model.infer() メソッドを呼び出すと音声合成を行える。
"""
def __init__(
self,
model_path: Path,
@@ -59,7 +60,9 @@ class TTSModel:
self.config_path: Path = config_path
self.style_vec_path: Path = style_vec_path
self.device: str = device
self.hyper_parameters: HyperParameters = HyperParameters.load_from_json(self.config_path)
self.hyper_parameters: HyperParameters = HyperParameters.load_from_json(
self.config_path
)
self.spk2id: dict[str, int] = self.hyper_parameters.data.spk2id
self.id2spk: dict[int, str] = {v: k for k, v in self.spk2id.items()}
@@ -82,19 +85,17 @@ class TTSModel:
self.__net_g: Union[SynthesizerTrn, SynthesizerTrnJPExtra, None] = None
def load(self) -> None:
"""
音声合成モデルをデバイスにロードする。
"""
self.__net_g = get_net_g(
model_path = str(self.model_path),
version = self.hyper_parameters.version,
device = self.device,
hps = self.hyper_parameters,
model_path=str(self.model_path),
version=self.hyper_parameters.version,
device=self.device,
hps=self.hyper_parameters,
)
def __get_style_vector(self, style_id: int, weight: float = 1.0) -> NDArray[Any]:
"""
スタイルベクトルを取得する。
@@ -111,8 +112,9 @@ class TTSModel:
style_vec = mean + (style_vec - mean) * weight
return style_vec
def __get_style_vector_from_audio(self, audio_path: str, weight: float = 1.0) -> NDArray[Any]:
def __get_style_vector_from_audio(
self, audio_path: str, weight: float = 1.0
) -> NDArray[Any]:
"""
音声からスタイルベクトルを推論する。
@@ -126,8 +128,10 @@ class TTSModel:
# スタイルベクトルを取得するための推論モデルを初期化
if self.__style_vector_inference is None:
self.__style_vector_inference = pyannote.audio.Inference(
model = pyannote.audio.Model.from_pretrained("pyannote/wespeaker-voxceleb-resnet34-LM"),
window = "whole",
model=pyannote.audio.Model.from_pretrained(
"pyannote/wespeaker-voxceleb-resnet34-LM"
),
window="whole",
)
self.__style_vector_inference.to(torch.device(self.device))
@@ -137,7 +141,6 @@ class TTSModel:
xvec = mean + (xvec - mean) * weight
return xvec
def infer(
self,
text: str,
@@ -209,20 +212,20 @@ class TTSModel:
if not line_split:
with torch.no_grad():
audio = infer(
text = text,
sdp_ratio = sdp_ratio,
noise_scale = noise,
noise_scale_w = noise_w,
length_scale = length,
sid = speaker_id,
language = language,
hps = self.hyper_parameters,
net_g = self.__net_g,
device = self.device,
assist_text = assist_text,
assist_text_weight = assist_text_weight,
style_vec = style_vector,
given_tone = given_tone,
text=text,
sdp_ratio=sdp_ratio,
noise_scale=noise,
noise_scale_w=noise_w,
length_scale=length,
sid=speaker_id,
language=language,
hps=self.hyper_parameters,
net_g=self.__net_g,
device=self.device,
assist_text=assist_text,
assist_text_weight=assist_text_weight,
style_vec=style_vector,
given_tone=given_tone,
)
else:
texts = text.split("\n")
@@ -232,19 +235,19 @@ class TTSModel:
for i, t in enumerate(texts):
audios.append(
infer(
text = t,
sdp_ratio = sdp_ratio,
noise_scale = noise,
noise_scale_w = noise_w,
length_scale = length,
sid = speaker_id,
language = language,
hps = self.hyper_parameters,
net_g = self.__net_g,
device = self.device,
assist_text = assist_text,
assist_text_weight = assist_text_weight,
style_vec = style_vector,
text=t,
sdp_ratio=sdp_ratio,
noise_scale=noise,
noise_scale_w=noise_w,
length_scale=length,
sid=speaker_id,
language=language,
hps=self.hyper_parameters,
net_g=self.__net_g,
device=self.device,
assist_text=assist_text,
assist_text_weight=assist_text_weight,
style_vec=style_vector,
)
)
if i != len(texts) - 1:
@@ -253,10 +256,10 @@ class TTSModel:
logger.info("Audio data generated successfully")
if not (pitch_scale == 1.0 and intonation_scale == 1.0):
_, audio = adjust_voice(
fs = self.hyper_parameters.data.sampling_rate,
wave = audio,
pitch_scale = pitch_scale,
intonation_scale = intonation_scale,
fs=self.hyper_parameters.data.sampling_rate,
wave=audio,
pitch_scale=pitch_scale,
intonation_scale=intonation_scale,
)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
@@ -277,7 +280,6 @@ class TTSModelHolder:
model_holder.models_info から指定されたディレクトリ内にある音声合成モデルの一覧を取得できる。
"""
def __init__(self, model_root_dir: Path, device: str) -> None:
"""
Style-Bert-Vits2 の音声合成モデルを管理するクラスを初期化する。
@@ -308,7 +310,6 @@ class TTSModelHolder:
self.models_info: list[TTSModelInfo] = []
self.refresh()
def refresh(self) -> None:
"""
音声合成モデルの一覧を更新する。
@@ -342,13 +343,14 @@ class TTSModelHolder:
styles = list(style2id.keys())
spk2id: dict[str, int] = hyper_parameters.data.spk2id
speakers = list(spk2id.keys())
self.models_info.append(TTSModelInfo(
name = model_dir.name,
files = [str(f) for f in model_files],
styles = styles,
speakers = speakers,
))
self.models_info.append(
TTSModelInfo(
name=model_dir.name,
files=[str(f) for f in model_files],
styles=styles,
speakers=speakers,
)
)
def get_model(self, model_name: str, model_path_str: str) -> TTSModel:
"""
@@ -370,16 +372,17 @@ class TTSModelHolder:
raise ValueError(f"Model file `{model_path}` is not found")
if self.current_model is None or self.current_model.model_path != model_path:
self.current_model = TTSModel(
model_path = model_path,
config_path = self.root_dir / model_name / "config.json",
style_vec_path = self.root_dir / model_name / "style_vectors.npy",
device = self.device,
model_path=model_path,
config_path=self.root_dir / model_name / "config.json",
style_vec_path=self.root_dir / model_name / "style_vectors.npy",
device=self.device,
)
return self.current_model
def get_model_for_gradio(self, model_name: str, model_path_str: str) -> tuple[gr.Dropdown, gr.Button, gr.Dropdown]:
def get_model_for_gradio(
self, model_name: str, model_path_str: str
) -> tuple[gr.Dropdown, gr.Button, gr.Dropdown]:
model_path = Path(model_path_str)
if model_name not in self.model_files_dict:
raise ValueError(f"Model `{model_name}` is not found")
@@ -398,10 +401,10 @@ class TTSModelHolder:
gr.Dropdown(choices=speakers, value=speakers[0]), # type: ignore
)
self.current_model = TTSModel(
model_path = model_path,
config_path = self.root_dir / model_name / "config.json",
style_vec_path = self.root_dir / model_name / "style_vectors.npy",
device = self.device,
model_path=model_path,
config_path=self.root_dir / model_name / "config.json",
style_vec_path=self.root_dir / model_name / "style_vectors.npy",
device=self.device,
)
speakers = list(self.current_model.spk2id.keys())
styles = list(self.current_model.style2id.keys())
@@ -411,13 +414,13 @@ class TTSModelHolder:
gr.Dropdown(choices=speakers, value=speakers[0]), # type: ignore
)
def update_model_files_for_gradio(self, model_name: str) -> gr.Dropdown:
model_files = self.model_files_dict[model_name]
return gr.Dropdown(choices=model_files, value=model_files[0]) # type: ignore
def update_model_names_for_gradio(self) -> tuple[gr.Dropdown, gr.Dropdown, gr.Button]:
def update_model_names_for_gradio(
self,
) -> tuple[gr.Dropdown, gr.Dropdown, gr.Button]:
self.refresh()
initial_model_name = self.model_names[0]
initial_model_files = self.model_files_dict[initial_model_name]