mirror of
https://github.com/blakeblackshear/frigate.git
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45e9030358
* Output frame name to frames processor * Finish implementing round robin * Formatting
572 lines
22 KiB
Python
572 lines
22 KiB
Python
"""Maintain recording segments in cache."""
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import asyncio
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import datetime
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import logging
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import os
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import random
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import string
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import threading
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import time
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from collections import defaultdict
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from multiprocessing.synchronize import Event as MpEvent
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from pathlib import Path
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from typing import Any, Optional, Tuple
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import numpy as np
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import psutil
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from frigate.comms.config_updater import ConfigSubscriber
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from frigate.comms.detections_updater import DetectionSubscriber, DetectionTypeEnum
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from frigate.comms.inter_process import InterProcessRequestor
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from frigate.config import FrigateConfig, RetainModeEnum
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from frigate.const import (
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CACHE_DIR,
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CACHE_SEGMENT_FORMAT,
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INSERT_MANY_RECORDINGS,
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MAX_SEGMENT_DURATION,
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MAX_SEGMENTS_IN_CACHE,
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RECORD_DIR,
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)
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from frigate.models import Recordings, ReviewSegment
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from frigate.util.services import get_video_properties
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logger = logging.getLogger(__name__)
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QUEUE_READ_TIMEOUT = 0.00001 # seconds
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class SegmentInfo:
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def __init__(
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self,
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motion_count: int,
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active_object_count: int,
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region_count: int,
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average_dBFS: int,
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) -> None:
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self.motion_count = motion_count
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self.active_object_count = active_object_count
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self.region_count = region_count
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self.average_dBFS = average_dBFS
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def should_discard_segment(self, retain_mode: RetainModeEnum) -> bool:
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return (
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retain_mode == RetainModeEnum.motion
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and self.motion_count == 0
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and self.average_dBFS == 0
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) or (
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retain_mode == RetainModeEnum.active_objects
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and self.active_object_count == 0
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)
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class RecordingMaintainer(threading.Thread):
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def __init__(self, config: FrigateConfig, stop_event: MpEvent):
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super().__init__(name="recording_maintainer")
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self.config = config
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# create communication for retained recordings
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self.requestor = InterProcessRequestor()
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self.config_subscriber = ConfigSubscriber("config/record/")
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self.detection_subscriber = DetectionSubscriber(DetectionTypeEnum.all)
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self.stop_event = stop_event
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self.object_recordings_info: dict[str, list] = defaultdict(list)
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self.audio_recordings_info: dict[str, list] = defaultdict(list)
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self.end_time_cache: dict[str, Tuple[datetime.datetime, float]] = {}
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async def move_files(self) -> None:
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cache_files = [
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d
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for d in os.listdir(CACHE_DIR)
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if os.path.isfile(os.path.join(CACHE_DIR, d))
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and d.endswith(".mp4")
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and not d.startswith("preview_")
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]
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files_in_use = []
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for process in psutil.process_iter():
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try:
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if process.name() != "ffmpeg":
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continue
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file_list = process.open_files()
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if file_list:
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for nt in file_list:
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if nt.path.startswith(CACHE_DIR):
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files_in_use.append(nt.path.split("/")[-1])
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except psutil.Error:
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continue
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# group recordings by camera
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grouped_recordings: defaultdict[str, list[dict[str, Any]]] = defaultdict(list)
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for cache in cache_files:
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# Skip files currently in use
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if cache in files_in_use:
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continue
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cache_path = os.path.join(CACHE_DIR, cache)
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basename = os.path.splitext(cache)[0]
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camera, date = basename.rsplit("@", maxsplit=1)
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# important that start_time is utc because recordings are stored and compared in utc
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start_time = datetime.datetime.strptime(
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date, CACHE_SEGMENT_FORMAT
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).astimezone(datetime.timezone.utc)
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grouped_recordings[camera].append(
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{
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"cache_path": cache_path,
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"start_time": start_time,
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}
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)
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# delete all cached files past the most recent MAX_SEGMENTS_IN_CACHE
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keep_count = MAX_SEGMENTS_IN_CACHE
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for camera in grouped_recordings.keys():
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# sort based on start time
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grouped_recordings[camera] = sorted(
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grouped_recordings[camera], key=lambda s: s["start_time"]
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)
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camera_info = self.object_recordings_info[camera]
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most_recently_processed_frame_time = (
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camera_info[-1][0] if len(camera_info) > 0 else 0
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)
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processed_segment_count = len(
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list(
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filter(
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lambda r: r["start_time"].timestamp()
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< most_recently_processed_frame_time,
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grouped_recordings[camera],
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)
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)
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)
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# see if the recording mover is too slow and segments need to be deleted
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if processed_segment_count > keep_count:
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logger.warning(
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f"Unable to keep up with recording segments in cache for {camera}. Keeping the {keep_count} most recent segments out of {processed_segment_count} and discarding the rest..."
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)
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to_remove = grouped_recordings[camera][:-keep_count]
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for rec in to_remove:
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cache_path = rec["cache_path"]
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Path(cache_path).unlink(missing_ok=True)
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self.end_time_cache.pop(cache_path, None)
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grouped_recordings[camera] = grouped_recordings[camera][-keep_count:]
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# see if detection has failed and unprocessed segments need to be deleted
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unprocessed_segment_count = (
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len(grouped_recordings[camera]) - processed_segment_count
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)
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if unprocessed_segment_count > keep_count:
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logger.warning(
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f"Too many unprocessed recording segments in cache for {camera}. This likely indicates an issue with the detect stream, keeping the {keep_count} most recent segments out of {unprocessed_segment_count} and discarding the rest..."
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)
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to_remove = grouped_recordings[camera][:-keep_count]
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for rec in to_remove:
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cache_path = rec["cache_path"]
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Path(cache_path).unlink(missing_ok=True)
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self.end_time_cache.pop(cache_path, None)
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grouped_recordings[camera] = grouped_recordings[camera][-keep_count:]
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tasks = []
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for camera, recordings in grouped_recordings.items():
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# clear out all the object recording info for old frames
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while (
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len(self.object_recordings_info[camera]) > 0
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and self.object_recordings_info[camera][0][0]
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< recordings[0]["start_time"].timestamp()
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):
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self.object_recordings_info[camera].pop(0)
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# clear out all the audio recording info for old frames
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while (
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len(self.audio_recordings_info[camera]) > 0
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and self.audio_recordings_info[camera][0][0]
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< recordings[0]["start_time"].timestamp()
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):
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self.audio_recordings_info[camera].pop(0)
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# get all reviews with the end time after the start of the oldest cache file
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# or with end_time None
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reviews: ReviewSegment = (
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ReviewSegment.select(
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ReviewSegment.start_time,
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ReviewSegment.end_time,
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ReviewSegment.data,
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)
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.where(
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ReviewSegment.camera == camera,
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(ReviewSegment.end_time == None)
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| (
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ReviewSegment.end_time
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>= recordings[0]["start_time"].timestamp()
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),
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)
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.order_by(ReviewSegment.start_time)
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)
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tasks.extend(
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[self.validate_and_move_segment(camera, reviews, r) for r in recordings]
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)
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recordings_to_insert: list[Optional[Recordings]] = await asyncio.gather(*tasks)
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# fire and forget recordings entries
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self.requestor.send_data(
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INSERT_MANY_RECORDINGS,
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[r for r in recordings_to_insert if r is not None],
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)
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async def validate_and_move_segment(
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self, camera: str, reviews: list[ReviewSegment], recording: dict[str, any]
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) -> None:
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cache_path = recording["cache_path"]
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start_time = recording["start_time"]
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record_config = self.config.cameras[camera].record
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# Just delete files if recordings are turned off
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if (
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camera not in self.config.cameras
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or not self.config.cameras[camera].record.enabled
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):
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Path(cache_path).unlink(missing_ok=True)
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self.end_time_cache.pop(cache_path, None)
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return
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if cache_path in self.end_time_cache:
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end_time, duration = self.end_time_cache[cache_path]
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else:
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segment_info = await get_video_properties(
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self.config.ffmpeg, cache_path, get_duration=True
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)
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if segment_info["duration"]:
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duration = float(segment_info["duration"])
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else:
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duration = -1
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# ensure duration is within expected length
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if 0 < duration < MAX_SEGMENT_DURATION:
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end_time = start_time + datetime.timedelta(seconds=duration)
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self.end_time_cache[cache_path] = (end_time, duration)
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else:
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if duration == -1:
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logger.warning(f"Failed to probe corrupt segment {cache_path}")
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logger.warning(f"Discarding a corrupt recording segment: {cache_path}")
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Path(cache_path).unlink(missing_ok=True)
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return
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# if cached file's start_time is earlier than the retain days for the camera
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if start_time <= (
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datetime.datetime.now().astimezone(datetime.timezone.utc)
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- datetime.timedelta(days=self.config.cameras[camera].record.retain.days)
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):
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# if the cached segment overlaps with the events:
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overlaps = False
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for review in reviews:
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# if the event starts in the future, stop checking events
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# and remove this segment
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if review.start_time > end_time.timestamp():
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overlaps = False
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Path(cache_path).unlink(missing_ok=True)
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self.end_time_cache.pop(cache_path, None)
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break
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# if the event is in progress or ends after the recording starts, keep it
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# and stop looking at events
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if review.end_time is None or review.end_time >= start_time.timestamp():
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overlaps = True
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break
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if overlaps:
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record_mode = (
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record_config.alerts.retain.mode
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if review.severity == "alert"
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else record_config.detections.retain.mode
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)
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# move from cache to recordings immediately
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return await self.move_segment(
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camera,
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start_time,
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end_time,
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duration,
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cache_path,
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record_mode,
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)
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# if it doesn't overlap with an event, go ahead and drop the segment
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# if it ends more than the configured pre_capture for the camera
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else:
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camera_info = self.object_recordings_info[camera]
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most_recently_processed_frame_time = (
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camera_info[-1][0] if len(camera_info) > 0 else 0
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)
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retain_cutoff = datetime.datetime.fromtimestamp(
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most_recently_processed_frame_time - record_config.event_pre_capture
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).astimezone(datetime.timezone.utc)
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if end_time < retain_cutoff:
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Path(cache_path).unlink(missing_ok=True)
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self.end_time_cache.pop(cache_path, None)
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# else retain days includes this segment
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else:
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# assume that empty means the relevant recording info has not been received yet
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camera_info = self.object_recordings_info[camera]
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most_recently_processed_frame_time = (
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camera_info[-1][0] if len(camera_info) > 0 else 0
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)
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# ensure delayed segment info does not lead to lost segments
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if (
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datetime.datetime.fromtimestamp(
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most_recently_processed_frame_time
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).astimezone(datetime.timezone.utc)
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>= end_time
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):
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record_mode = self.config.cameras[camera].record.retain.mode
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return await self.move_segment(
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camera, start_time, end_time, duration, cache_path, record_mode
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)
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def segment_stats(
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self, camera: str, start_time: datetime.datetime, end_time: datetime.datetime
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) -> SegmentInfo:
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video_frame_count = 0
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active_count = 0
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region_count = 0
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motion_count = 0
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for frame in self.object_recordings_info[camera]:
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# frame is after end time of segment
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if frame[0] > end_time.timestamp():
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break
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# frame is before start time of segment
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if frame[0] < start_time.timestamp():
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continue
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video_frame_count += 1
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active_count += len(
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[
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o
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for o in frame[1]
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if not o["false_positive"] and o["motionless_count"] == 0
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]
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)
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motion_count += len(frame[2])
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region_count += len(frame[3])
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audio_values = []
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for frame in self.audio_recordings_info[camera]:
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# frame is after end time of segment
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if frame[0] > end_time.timestamp():
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break
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# frame is before start time of segment
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if frame[0] < start_time.timestamp():
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continue
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# add active audio label count to count of active objects
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active_count += len(frame[2])
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# add sound level to audio values
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audio_values.append(frame[1])
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average_dBFS = 0 if not audio_values else np.average(audio_values)
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return SegmentInfo(
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motion_count, active_count, region_count, round(average_dBFS)
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)
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async def move_segment(
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self,
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camera: str,
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start_time: datetime.datetime,
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end_time: datetime.datetime,
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duration: float,
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cache_path: str,
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store_mode: RetainModeEnum,
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) -> Optional[Recordings]:
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segment_info = self.segment_stats(camera, start_time, end_time)
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# check if the segment shouldn't be stored
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if segment_info.should_discard_segment(store_mode):
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Path(cache_path).unlink(missing_ok=True)
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self.end_time_cache.pop(cache_path, None)
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return
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# directory will be in utc due to start_time being in utc
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directory = os.path.join(
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RECORD_DIR,
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start_time.strftime("%Y-%m-%d/%H"),
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camera,
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)
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if not os.path.exists(directory):
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os.makedirs(directory)
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# file will be in utc due to start_time being in utc
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file_name = f"{start_time.strftime('%M.%S.mp4')}"
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file_path = os.path.join(directory, file_name)
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try:
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if not os.path.exists(file_path):
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start_frame = datetime.datetime.now().timestamp()
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# add faststart to kept segments to improve metadata reading
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p = await asyncio.create_subprocess_exec(
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self.config.ffmpeg.ffmpeg_path,
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"-hide_banner",
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"-y",
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"-i",
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cache_path,
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"-c",
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"copy",
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"-movflags",
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"+faststart",
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file_path,
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stderr=asyncio.subprocess.PIPE,
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stdout=asyncio.subprocess.DEVNULL,
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)
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await p.wait()
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if p.returncode != 0:
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logger.error(f"Unable to convert {cache_path} to {file_path}")
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logger.error((await p.stderr.read()).decode("ascii"))
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return None
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else:
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logger.debug(
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f"Copied {file_path} in {datetime.datetime.now().timestamp()-start_frame} seconds."
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)
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try:
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# get the segment size of the cache file
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# file without faststart is same size
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segment_size = round(
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float(os.path.getsize(cache_path)) / pow(2, 20), 1
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)
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except OSError:
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segment_size = 0
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os.remove(cache_path)
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rand_id = "".join(
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random.choices(string.ascii_lowercase + string.digits, k=6)
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)
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return {
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Recordings.id.name: f"{start_time.timestamp()}-{rand_id}",
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Recordings.camera.name: camera,
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Recordings.path.name: file_path,
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Recordings.start_time.name: start_time.timestamp(),
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Recordings.end_time.name: end_time.timestamp(),
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Recordings.duration.name: duration,
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Recordings.motion.name: segment_info.motion_count,
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# TODO: update this to store list of active objects at some point
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Recordings.objects.name: segment_info.active_object_count,
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Recordings.regions.name: segment_info.region_count,
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Recordings.dBFS.name: segment_info.average_dBFS,
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Recordings.segment_size.name: segment_size,
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}
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except Exception as e:
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logger.error(f"Unable to store recording segment {cache_path}")
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Path(cache_path).unlink(missing_ok=True)
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logger.error(e)
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# clear end_time cache
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self.end_time_cache.pop(cache_path, None)
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return None
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def run(self) -> None:
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# Check for new files every 5 seconds
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wait_time = 0.0
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while not self.stop_event.is_set():
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time.sleep(wait_time)
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if self.stop_event.is_set():
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break
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run_start = datetime.datetime.now().timestamp()
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# check if there is an updated config
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while True:
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(
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updated_topic,
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updated_record_config,
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) = self.config_subscriber.check_for_update()
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if not updated_topic:
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break
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camera_name = updated_topic.rpartition("/")[-1]
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self.config.cameras[camera_name].record = updated_record_config
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stale_frame_count = 0
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stale_frame_count_threshold = 10
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# empty the object recordings info queue
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while True:
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(topic, data) = self.detection_subscriber.check_for_update(
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timeout=QUEUE_READ_TIMEOUT
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)
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if not topic:
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break
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if topic == DetectionTypeEnum.video:
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(
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camera,
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_,
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frame_time,
|
|
current_tracked_objects,
|
|
motion_boxes,
|
|
regions,
|
|
) = data
|
|
|
|
if self.config.cameras[camera].record.enabled:
|
|
self.object_recordings_info[camera].append(
|
|
(
|
|
frame_time,
|
|
current_tracked_objects,
|
|
motion_boxes,
|
|
regions,
|
|
)
|
|
)
|
|
elif topic == DetectionTypeEnum.audio:
|
|
(
|
|
camera,
|
|
frame_time,
|
|
dBFS,
|
|
audio_detections,
|
|
) = data
|
|
|
|
if self.config.cameras[camera].record.enabled:
|
|
self.audio_recordings_info[camera].append(
|
|
(
|
|
frame_time,
|
|
dBFS,
|
|
audio_detections,
|
|
)
|
|
)
|
|
elif topic == DetectionTypeEnum.api:
|
|
continue
|
|
|
|
if frame_time < run_start - stale_frame_count_threshold:
|
|
stale_frame_count += 1
|
|
|
|
if stale_frame_count > 0:
|
|
logger.debug(f"Found {stale_frame_count} old frames.")
|
|
|
|
try:
|
|
asyncio.run(self.move_files())
|
|
except Exception as e:
|
|
logger.error(
|
|
"Error occurred when attempting to maintain recording cache"
|
|
)
|
|
logger.error(e)
|
|
duration = datetime.datetime.now().timestamp() - run_start
|
|
wait_time = max(0, 5 - duration)
|
|
|
|
self.requestor.stop()
|
|
self.config_subscriber.stop()
|
|
self.detection_subscriber.stop()
|
|
logger.info("Exiting recording maintenance...")
|