File size: 2,276 Bytes
819e690 f722fb4 819e690 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 | """RNNoise 降噪示例：处理一段 48k 单声道音频，输出去噪结果。
用法:
python example.py --model model.axmodel --input in.pcm [--output-dir out]
输入格式：48kHz f32le PCM（16-bit 等价域，±32768，不做归一化）；
也可传 16-bit PCM .wav（wave 标准库自动解码为 ±32768 域）。
"""
import argparse
import sys
import wave
from pathlib import Path
import numpy as np
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from rnnoise_sdk import RNNoiseDenoiser, dsp # noqa: E402
def load_pcm(path: Path) -> np.ndarray:
if path.suffix.lower() == ".wav":
with wave.open(str(path), "rb") as w:
assert w.getframerate() == 48000, "仅支持 48kHz WAV"
assert w.getsampwidth() == 2, "仅支持 16-bit PCM WAV"
raw = w.readframes(w.getnframes())
return np.frombuffer(raw, dtype="<i2").astype(np.float32)
return np.fromfile(path, dtype=np.float32)
def write_wav(path: Path, pcm: np.ndarray, sr: int = 48000) -> None:
pcm = np.clip(pcm, -32768.0, 32767.0).astype(np.int16)
with wave.open(str(path), "wb") as w:
w.setnchannels(1)
w.setsampwidth(2)
w.setframerate(sr)
w.writeframes(pcm.tobytes())
def main() -> None:
parser = argparse.ArgumentParser(description="RNNoise 48k 实时降噪示例")
parser.add_argument("--model", required=True, help="model.axmodel 路径")
parser.add_argument("--input", required=True, help="48k f32 PCM 或 16-bit WAV")
parser.add_argument("--output-dir", default="output")
args = parser.parse_args()
pcm = load_pcm(Path(args.input))
print(f"input: {pcm.size / 48000:.2f}s ({pcm.size // dsp.FRAME_SIZE} 帧)")
denoiser = RNNoiseDenoiser(args.model)
out, vads = denoiser.process(pcm)
out_dir = Path(args.output_dir)
out_dir.mkdir(parents=True, exist_ok=True)
out.astype(np.float32).tofile(out_dir / "out.pcm")
write_wav(out_dir / "out.wav", out)
np.save(out_dir / "vad.npy", vads)
print(f"backend: {denoiser.backend}")
print(f"frames: {vads.size} vad_mean: {float(vads.mean()):.4f}")
print(f"output RMS: {float(np.sqrt((out ** 2).mean())):.1f}")
print(f"saved to: {out_dir}")
if __name__ == "__main__":
main()
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