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76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
from io import BufferedWriter, BytesIO
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from pathlib import Path
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from typing import Dict
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import av
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from av.audio.resampler import AudioResampler
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import numpy as np
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video_format_dict: Dict[str, str] = {
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"m4a": "mp4",
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}
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audio_format_dict: Dict[str, str] = {
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"ogg": "libvorbis",
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"mp4": "aac",
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}
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def wav2(i: BytesIO, o: BufferedWriter, format: str):
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"""
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https://github.com/fumiama/Retrieval-based-Voice-Conversion-WebUI/blob/412a9950a1e371a018c381d1bfb8579c4b0de329/infer/lib/audio.py#L20
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"""
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inp = av.open(i, "r")
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format = video_format_dict.get(format, format)
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out = av.open(o, "w", format=format)
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format = audio_format_dict.get(format, format)
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ostream = out.add_stream(format)
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for frame in inp.decode(audio=0):
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for p in ostream.encode(frame):
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out.mux(p)
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for p in ostream.encode(None):
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out.mux(p)
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out.close()
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inp.close()
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def load_audio(file: str, sr: int) -> np.ndarray:
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if not Path(file).exists():
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raise FileNotFoundError(f"File not found: {file}")
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try:
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container = av.open(file)
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resampler = AudioResampler(format="fltp", layout="mono", rate=sr)
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# Estimated maximum total number of samples to pre-allocate the array
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# AV stores length in microseconds by default
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estimated_total_samples = int(container.duration * sr // 1_000_000)
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decoded_audio = np.zeros(estimated_total_samples + 1, dtype=np.float32)
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offset = 0
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for frame in container.decode(audio=0):
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frame.pts = None # Clear presentation timestamp to avoid resampling issues
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resampled_frames = resampler.resample(frame)
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for resampled_frame in resampled_frames:
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frame_data = resampled_frame.to_ndarray()[0]
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end_index = offset + len(frame_data)
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# Check if decoded_audio has enough space, and resize if necessary
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if end_index > decoded_audio.shape[0]:
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decoded_audio = np.resize(decoded_audio, end_index + 1)
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decoded_audio[offset:end_index] = frame_data
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offset += len(frame_data)
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# Truncate the array to the actual size
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decoded_audio = decoded_audio[:offset]
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except Exception as e:
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raise RuntimeError(f"Failed to load audio: {e}")
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return decoded_audio
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