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Fix: server_fastapi.py, support auto split (#152)

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* Fix: server_fastapi.py, support auto split

* Fix: translate.py
This commit is contained in:
Sora
2023-11-06 19:40:58 +08:00
committed by GitHub
parent 855774213e
commit 096d661a4b
3 changed files with 45 additions and 20 deletions
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56
server_fastapi.py
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@@ -5,6 +5,7 @@ import logging
import gc
import random
import numpy as np
import utils
from fastapi import FastAPI, Query, Request
from fastapi.responses import Response, FileResponse
@@ -23,6 +24,8 @@ from urllib.parse import unquote
from infer import infer, get_net_g, latest_version
import tools.translate as trans
from re_matching import cut_sent
from config import config
@@ -183,6 +186,7 @@ if __name__ == "__main__":
length: float = Query(1, description="语速"),
language: str = Query(None, description="语言"), # 若不指定使用语言则使用默认值
auto_translate: bool = Query(False, description="自动翻译"),
auto_split: bool = Query(False, description="自动切分"),
):
"""语音接口"""
logger.info(
@@ -206,19 +210,41 @@ if __name__ == "__main__":
language = loaded_models.models[model_id].language
if auto_translate:
text = trans.translate(Sentence=text, to_Language=language.lower())
with torch.no_grad():
audio = infer(
text=text,
sdp_ratio=sdp_ratio,
noise_scale=noise,
noise_scale_w=noisew,
length_scale=length,
sid=speaker_name,
language=language,
hps=loaded_models.models[model_id].hps,
net_g=loaded_models.models[model_id].net_g,
device=loaded_models.models[model_id].device,
)
if not auto_split:
with torch.no_grad():
audio = infer(
text=text,
sdp_ratio=sdp_ratio,
noise_scale=noise,
noise_scale_w=noisew,
length_scale=length,
sid=speaker_name,
language=language,
hps=loaded_models.models[model_id].hps,
net_g=loaded_models.models[model_id].net_g,
device=loaded_models.models[model_id].device,
)
else:
texts = cut_sent(text)
audios = []
with torch.no_grad():
for t in texts:
audios.append(
infer(
text=t,
sdp_ratio=sdp_ratio,
noise_scale=noise,
noise_scale_w=noisew,
length_scale=length,
sid=speaker_name,
language=language,
hps=loaded_models.models[model_id].hps,
net_g=loaded_models.models[model_id].net_g,
device=loaded_models.models[model_id].device,
)
)
audios.append(np.zeros((int)(44100 * 0.3)))
audio = np.concatenate(audios)
wavContent = BytesIO()
wavfile.write(
wavContent, loaded_models.models[model_id].hps.data.sampling_rate, audio
@@ -308,7 +334,7 @@ if __name__ == "__main__":
model_files = []
for sub_file in sub_files:
relpath = os.path.realpath(os.path.join(sub_dir, sub_file))
if only_unloaded and relpath in loaded_models.path2count.keys():
if only_unloaded and relpath in loaded_models.path2ids.keys():
continue
if sub_file.endswith(".pth") and sub_file.startswith("G_"):
if os.path.isfile(relpath):
@@ -327,7 +353,7 @@ if __name__ == "__main__":
sub_files = os.listdir(models_dir)
for sub_file in sub_files:
relpath = os.path.realpath(os.path.join(models_dir, sub_file))
if only_unloaded and relpath in loaded_models.path2count.keys():
if only_unloaded and relpath in loaded_models.path2ids.keys():
continue
if sub_file.endswith(".pth") and sub_file.startswith("G_"):
if os.path.isfile(os.path.join(models_dir, sub_file)):