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| import os | |
| from typing import BinaryIO | |
| import ffmpeg | |
| import numpy as np | |
| SAMPLE_RATE = 16000 | |
| FFMPEG_BIN = os.getenv("FFMPEG_BIN", "ffmpeg") | |
| def load_audio(file: BinaryIO, encode=True, sr: int = SAMPLE_RATE): | |
| """ | |
| Open an audio file object and read as mono waveform, resampling as necessary. | |
| Modified from https://github.com/openai/whisper/blob/main/whisper/audio.py to accept a file object | |
| Parameters | |
| ---------- | |
| file: BinaryIO | |
| The audio file like object | |
| encode: Boolean | |
| If true, encode audio stream to WAV before sending to whisper | |
| sr: int | |
| The sample rate to resample the audio if necessary | |
| Returns | |
| ------- | |
| A NumPy array containing the audio waveform, in float32 dtype. | |
| """ | |
| if encode: | |
| try: | |
| # This launches a subprocess to decode audio while down-mixing and resampling as necessary. | |
| # Requires the ffmpeg CLI and `ffmpeg-python` package to be installed. | |
| out, _ = ( | |
| ffmpeg.input("pipe:", threads=0) | |
| .output("-", format="s16le", acodec="pcm_s16le", ac=1, ar=sr) | |
| .run(cmd=FFMPEG_BIN, capture_stdout=True, capture_stderr=True, input=file.read()) | |
| ) | |
| except ffmpeg.Error as e: | |
| raise RuntimeError(f"Failed to load audio: {e.stderr.decode()}") from e | |
| else: | |
| out = file.read() | |
| try: | |
| return np.frombuffer(out, np.int16).flatten().astype(np.float32) / 32768.0 | |
| except Exception as e: | |
| # TODO: Unsupported file formats can raise the following exception: | |
| # ValueError: buffer size must be a multiple of element size | |
| # This should be made more robust. | |
| raise RuntimeError("Failed to load audio") from e | |