Files
TalkEdit/backend/services/audio_cleaner.py

80 lines
2.2 KiB
Python
Raw Normal View History

"""
Audio noise reduction using DeepFilterNet.
Falls back to a basic FFmpeg noise filter if DeepFilterNet is not installed.
"""
import logging
import subprocess
import tempfile
from pathlib import Path
logger = logging.getLogger(__name__)
try:
from df.enhance import enhance, init_df, load_audio, save_audio
DEEPFILTER_AVAILABLE = True
except ImportError:
DEEPFILTER_AVAILABLE = False
_df_model = None
_df_state = None
def _init_deepfilter():
global _df_model, _df_state
if _df_model is None:
logger.info("Initializing DeepFilterNet model")
_df_model, _df_state, _ = init_df()
return _df_model, _df_state
def clean_audio(
input_path: str,
output_path: str = "",
) -> str:
"""
Apply noise reduction to an audio file.
If DeepFilterNet is available, uses it for high-quality results.
Otherwise falls back to FFmpeg's anlmdn filter.
Returns: path to the cleaned audio file.
"""
input_path = Path(input_path)
if not output_path:
output_path = str(input_path.with_stem(input_path.stem + "_clean"))
if DEEPFILTER_AVAILABLE:
return _clean_with_deepfilter(str(input_path), output_path)
else:
return _clean_with_ffmpeg(str(input_path), output_path)
def _clean_with_deepfilter(input_path: str, output_path: str) -> str:
model, state = _init_deepfilter()
audio, info = load_audio(input_path, sr=state.sr())
enhanced = enhance(model, state, audio)
save_audio(output_path, enhanced, sr=state.sr())
logger.info(f"DeepFilterNet cleaned audio saved to {output_path}")
return output_path
def _clean_with_ffmpeg(input_path: str, output_path: str) -> str:
"""Fallback: basic noise reduction using FFmpeg's anlmdn filter."""
cmd = [
"ffmpeg", "-y",
"-i", input_path,
"-af", "anlmdn=s=7:p=0.002:r=0.002:m=15",
output_path,
]
result = subprocess.run(cmd, capture_output=True, text=True)
if result.returncode != 0:
raise RuntimeError(f"FFmpeg audio cleaning failed: {result.stderr[-300:]}")
logger.info(f"FFmpeg cleaned audio saved to {output_path}")
return output_path
def is_deepfilter_available() -> bool:
return DEEPFILTER_AVAILABLE