mirror of
https://github.com/fumiama/Retrieval-based-Voice-Conversion-WebUI.git
synced 2026-06-05 01:10:22 +08:00
perf: use hashing to determine the format in infer/lib/audio.py (#26)
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@@ -1,18 +1,24 @@
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import platform
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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 ffmpeg
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import ffmpeg
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import numpy as np
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import numpy as np
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import av
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import av
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video_format_dict: Dict[str, str] = {
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"m4a": "mp4",
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}
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def wav2(i, o, format):
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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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inp = av.open(i, "r")
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inp = av.open(i, "r")
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if format == "m4a":
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format = video_format_dict.get(format, format)
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format = "mp4"
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out = av.open(o, "w", format=format)
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out = av.open(o, "w", format=format)
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if format == "ogg":
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format = audio_format_dict.get(format, format)
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format = "libvorbis"
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if format == "mp4":
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format = "aac"
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ostream = out.add_stream(format)
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ostream = out.add_stream(format)
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@@ -27,12 +33,15 @@ def wav2(i, o, format):
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inp.close()
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inp.close()
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def load_audio(file, sr):
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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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try:
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# https://github.com/openai/whisper/blob/main/whisper/audio.py#L26
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# https://github.com/openai/whisper/blob/main/whisper/audio.py#L26
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# This launches a subprocess to decode audio while down-mixing and resampling as necessary.
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# This launches a subprocess to decode audio while down-mixing and resampling as necessary.
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# Requires the ffmpeg CLI and `ffmpeg-python` package to be installed.
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# Requires the ffmpeg CLI and `ffmpeg-python` package to be installed.
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file = clean_path(file) # 防止小白拷路径头尾带了空格和"和回车
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file = str(clean_path(file)) # 防止小白拷路径头尾带了空格和"和回车
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out, _ = (
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out, _ = (
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ffmpeg.input(file, threads=0)
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ffmpeg.input(file, threads=0)
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.output("-", format="f32le", acodec="pcm_f32le", ac=1, ar=sr)
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.output("-", format="f32le", acodec="pcm_f32le", ac=1, ar=sr)
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@@ -44,7 +53,5 @@ def load_audio(file, sr):
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return np.frombuffer(out, np.float32).flatten()
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return np.frombuffer(out, np.float32).flatten()
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def clean_path(path_str):
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def clean_path(path: str) -> Path:
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if platform.system() == "Windows":
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return Path(path.strip(' "\n')).resolve()
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path_str = path_str.replace("/", "\\")
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return path_str.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
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