53 lines
1.5 KiB
Python
53 lines
1.5 KiB
Python
# 音频预缓存实用程序, 独立于主程序之外, 但依赖 particles 组件
|
|
import particles as pt
|
|
import edge_tts as tts
|
|
from pathlib import Path
|
|
import shutil
|
|
|
|
|
|
def precache(text: str):
|
|
"""预缓存单个文本的音频"""
|
|
cache_dir = Path("./cache/voice/")
|
|
cache_dir.mkdir(parents=True, exist_ok=True)
|
|
cache = cache_dir / f"{text}.wav"
|
|
if not cache.exists():
|
|
communicate = tts.Communicate(text, "zh-CN-YunjianNeural")
|
|
communicate.save_sync(f"./cache/voice/{text}.wav")
|
|
|
|
|
|
def proc_file(path: Path):
|
|
"""处理单个文件"""
|
|
nu = pt.NucleonUnion(path)
|
|
c = 0
|
|
for i in nu.nucleons:
|
|
c += 1
|
|
print(f"预缓存 [{nu.name}] ({c}/{len(nu)}): {i['content'].replace('/', '')}")
|
|
precache(i['content'].replace('/', ''))
|
|
|
|
|
|
def walk(path_str: str):
|
|
"""遍历目录处理所有文件"""
|
|
path = Path(path_str)
|
|
print(f"正在遍历目录: {path}")
|
|
|
|
for item in path.iterdir():
|
|
if item.is_file() and item.suffix == ".toml":
|
|
print(f"正预缓存文件: {item.name}")
|
|
proc_file(item)
|
|
elif item.is_dir():
|
|
print(f"进入目录: {item.name}")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
print("音频预缓存实用程序")
|
|
print("A: 全部缓存")
|
|
print("C: 清空缓存")
|
|
|
|
choice = input("输入选项 $ ").upper()
|
|
|
|
if choice == "A":
|
|
walk("./nucleon")
|
|
elif choice == "C":
|
|
shutil.rmtree("./cache/voice", ignore_errors=True)
|
|
print("缓存已清空")
|