mirror of
https://github.com/blakeblackshear/frigate.git
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2bd6fa53fe
* install new packages for transcription support * add config options * audio maintainer modifications to support transcription * pass main config to audio process * embeddings support * api and transcription post processor * embeddings maintainer support for post processor * live audio transcription with sherpa and faster-whisper * update dispatcher with live transcription topic * frontend websocket * frontend live transcription * frontend changes for speech events * i18n changes * docs * mqtt docs * fix linter * use float16 and small model on gpu for real-time * fix return value and use requestor to embed description instead of passing embeddings * run real-time transcription in its own thread * tweaks * publish live transcriptions on their own topic instead of tracked_object_update * config validator and docs * clarify docs
117 lines
3.3 KiB
Python
117 lines
3.3 KiB
Python
"""Utilities for creating and manipulating audio."""
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import logging
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import os
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import subprocess as sp
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from typing import Optional
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from pathvalidate import sanitize_filename
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from frigate.const import CACHE_DIR
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from frigate.models import Recordings
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logger = logging.getLogger(__name__)
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def get_audio_from_recording(
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ffmpeg,
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camera_name: str,
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start_ts: float,
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end_ts: float,
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sample_rate: int = 16000,
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) -> Optional[bytes]:
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"""Extract audio from recording files between start_ts and end_ts in WAV format suitable for sherpa-onnx.
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Args:
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ffmpeg: FFmpeg configuration object
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camera_name: Name of the camera
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start_ts: Start timestamp in seconds
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end_ts: End timestamp in seconds
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sample_rate: Sample rate for output audio (default 16kHz for sherpa-onnx)
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Returns:
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Bytes of WAV audio data or None if extraction failed
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"""
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# Fetch all relevant recording segments
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recordings = (
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Recordings.select(
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Recordings.path,
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Recordings.start_time,
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Recordings.end_time,
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)
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.where(
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(Recordings.start_time.between(start_ts, end_ts))
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| (Recordings.end_time.between(start_ts, end_ts))
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| ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
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)
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.where(Recordings.camera == camera_name)
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.order_by(Recordings.start_time.asc())
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)
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if not recordings:
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logger.debug(
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f"No recordings found for {camera_name} between {start_ts} and {end_ts}"
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)
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return None
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# Generate concat playlist file
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file_name = sanitize_filename(
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f"audio_playlist_{camera_name}_{start_ts}-{end_ts}.txt"
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)
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file_path = os.path.join(CACHE_DIR, file_name)
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try:
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with open(file_path, "w") as file:
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for clip in recordings:
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file.write(f"file '{clip.path}'\n")
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if clip.start_time < start_ts:
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file.write(f"inpoint {int(start_ts - clip.start_time)}\n")
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if clip.end_time > end_ts:
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file.write(f"outpoint {int(end_ts - clip.start_time)}\n")
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ffmpeg_cmd = [
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ffmpeg.ffmpeg_path,
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"-hide_banner",
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"-loglevel",
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"warning",
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"-protocol_whitelist",
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"pipe,file",
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"-f",
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"concat",
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"-safe",
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"0",
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"-i",
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file_path,
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"-vn", # No video
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"-acodec",
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"pcm_s16le", # 16-bit PCM encoding
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"-ar",
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str(sample_rate),
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"-ac",
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"1", # Mono audio
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"-f",
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"wav",
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"-",
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]
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process = sp.run(
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ffmpeg_cmd,
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capture_output=True,
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)
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if process.returncode == 0:
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logger.debug(
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f"Successfully extracted audio for {camera_name} from {start_ts} to {end_ts}"
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)
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return process.stdout
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else:
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logger.error(f"Failed to extract audio: {process.stderr.decode()}")
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return None
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except Exception as e:
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logger.error(f"Error extracting audio from recordings: {e}")
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return None
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finally:
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try:
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os.unlink(file_path)
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except OSError:
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pass
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