mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
b909ff4ecb
* Expose dBFS when doing audio analysis * Implement metadata communicator * revert test changes * Reverting the tests changes. For real this time * Address feedback * Address feedback * Address feedback * Address feedback
655 lines
25 KiB
Python
655 lines
25 KiB
Python
import datetime
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import logging
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import multiprocessing as mp
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import os
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import shutil
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import signal
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import sys
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import traceback
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from multiprocessing.synchronize import Event as MpEvent
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from types import FrameType
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from typing import Optional
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import faster_fifo as ff
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import psutil
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from faster_fifo import Queue
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from peewee_migrate import Router
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from playhouse.sqlite_ext import SqliteExtDatabase
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from playhouse.sqliteq import SqliteQueueDatabase
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from frigate.comms.dispatcher import Communicator, Dispatcher
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from frigate.comms.inter_process import InterProcessCommunicator
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from frigate.comms.mqtt import MqttClient
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from frigate.comms.ws import WebSocketClient
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from frigate.config import FrigateConfig
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from frigate.const import (
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CACHE_DIR,
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CLIPS_DIR,
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CONFIG_DIR,
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DEFAULT_DB_PATH,
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DEFAULT_QUEUE_BUFFER_SIZE,
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EXPORT_DIR,
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MODEL_CACHE_DIR,
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RECORD_DIR,
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)
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from frigate.events.audio import listen_to_audio
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from frigate.events.cleanup import EventCleanup
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from frigate.events.external import ExternalEventProcessor
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from frigate.events.maintainer import EventProcessor
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from frigate.http import create_app
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from frigate.log import log_process, root_configurer
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from frigate.models import Event, Recordings, Timeline
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from frigate.object_detection import ObjectDetectProcess
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from frigate.object_processing import TrackedObjectProcessor
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from frigate.output import output_frames
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from frigate.plus import PlusApi
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from frigate.ptz.autotrack import PtzAutoTrackerThread
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from frigate.ptz.onvif import OnvifController
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from frigate.record.record import manage_recordings
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from frigate.stats import StatsEmitter, stats_init
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from frigate.storage import StorageMaintainer
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from frigate.timeline import TimelineProcessor
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from frigate.types import CameraMetricsTypes, FeatureMetricsTypes, PTZMetricsTypes
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from frigate.version import VERSION
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from frigate.video import capture_camera, track_camera
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from frigate.watchdog import FrigateWatchdog
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logger = logging.getLogger(__name__)
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class FrigateApp:
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def __init__(self) -> None:
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self.stop_event: MpEvent = mp.Event()
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self.detection_queue: Queue = ff.Queue()
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self.detectors: dict[str, ObjectDetectProcess] = {}
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self.detection_out_events: dict[str, MpEvent] = {}
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self.detection_shms: list[mp.shared_memory.SharedMemory] = []
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self.log_queue: Queue = ff.Queue()
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self.plus_api = PlusApi()
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self.camera_metrics: dict[str, CameraMetricsTypes] = {}
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self.feature_metrics: dict[str, FeatureMetricsTypes] = {}
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self.ptz_metrics: dict[str, PTZMetricsTypes] = {}
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self.processes: dict[str, int] = {}
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def set_environment_vars(self) -> None:
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for key, value in self.config.environment_vars.items():
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os.environ[key] = value
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def ensure_dirs(self) -> None:
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for d in [
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CONFIG_DIR,
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RECORD_DIR,
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CLIPS_DIR,
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CACHE_DIR,
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MODEL_CACHE_DIR,
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EXPORT_DIR,
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]:
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if not os.path.exists(d) and not os.path.islink(d):
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logger.info(f"Creating directory: {d}")
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os.makedirs(d)
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else:
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logger.debug(f"Skipping directory: {d}")
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def init_logger(self) -> None:
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self.log_process = mp.Process(
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target=log_process, args=(self.log_queue,), name="log_process"
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)
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self.log_process.daemon = True
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self.log_process.start()
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self.processes["logger"] = self.log_process.pid or 0
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root_configurer(self.log_queue)
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def init_config(self) -> None:
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config_file = os.environ.get("CONFIG_FILE", "/config/config.yml")
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# Check if we can use .yaml instead of .yml
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config_file_yaml = config_file.replace(".yml", ".yaml")
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if os.path.isfile(config_file_yaml):
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config_file = config_file_yaml
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user_config = FrigateConfig.parse_file(config_file)
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self.config = user_config.runtime_config(self.plus_api)
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for camera_name, camera_config in self.config.cameras.items():
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# create camera_metrics
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self.camera_metrics[camera_name] = {
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"camera_fps": mp.Value("d", 0.0), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"skipped_fps": mp.Value("d", 0.0), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"process_fps": mp.Value("d", 0.0), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"detection_enabled": mp.Value( # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"i",
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self.config.cameras[camera_name].detect.enabled,
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),
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"motion_enabled": mp.Value("i", True), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"improve_contrast_enabled": mp.Value( # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"i",
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self.config.cameras[camera_name].motion.improve_contrast,
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),
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"motion_threshold": mp.Value( # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"i",
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self.config.cameras[camera_name].motion.threshold,
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),
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"motion_contour_area": mp.Value( # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"i",
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self.config.cameras[camera_name].motion.contour_area,
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),
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"detection_fps": mp.Value("d", 0.0), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"detection_frame": mp.Value("d", 0.0), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"read_start": mp.Value("d", 0.0), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"ffmpeg_pid": mp.Value("i", 0), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"frame_queue": mp.Queue(maxsize=2),
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"capture_process": None,
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"process": None,
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}
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self.ptz_metrics[camera_name] = {
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"ptz_autotracker_enabled": mp.Value( # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"i",
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self.config.cameras[camera_name].onvif.autotracking.enabled,
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),
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"ptz_stopped": mp.Event(),
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"ptz_reset": mp.Event(),
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"ptz_start_time": mp.Value("d", 0.0), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"ptz_stop_time": mp.Value("d", 0.0), # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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}
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self.ptz_metrics[camera_name]["ptz_stopped"].set()
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self.feature_metrics[camera_name] = {
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"audio_enabled": mp.Value( # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"i",
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self.config.cameras[camera_name].audio.enabled,
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),
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"record_enabled": mp.Value( # type: ignore[typeddict-item]
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# issue https://github.com/python/typeshed/issues/8799
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# from mypy 0.981 onwards
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"i",
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self.config.cameras[camera_name].record.enabled,
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),
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}
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def set_log_levels(self) -> None:
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logging.getLogger().setLevel(self.config.logger.default.value.upper())
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for log, level in self.config.logger.logs.items():
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logging.getLogger(log).setLevel(level.value.upper())
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if "werkzeug" not in self.config.logger.logs:
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logging.getLogger("werkzeug").setLevel("ERROR")
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if "ws4py" not in self.config.logger.logs:
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logging.getLogger("ws4py").setLevel("ERROR")
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def init_queues(self) -> None:
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# Queues for clip processing
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self.event_queue: Queue = ff.Queue(DEFAULT_QUEUE_BUFFER_SIZE)
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self.event_processed_queue: Queue = ff.Queue(DEFAULT_QUEUE_BUFFER_SIZE)
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self.video_output_queue: Queue = mp.Queue(
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maxsize=len(self.config.cameras.keys()) * 2
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)
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# Queue for cameras to push tracked objects to
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self.detected_frames_queue: Queue = mp.Queue(
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maxsize=len(self.config.cameras.keys()) * 2
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)
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# Queue for recordings info
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self.recordings_info_queue: Queue = ff.Queue(DEFAULT_QUEUE_BUFFER_SIZE)
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# Queue for timeline events
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self.timeline_queue: Queue = ff.Queue(DEFAULT_QUEUE_BUFFER_SIZE)
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# Queue for inter process communication
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self.inter_process_queue: Queue = ff.Queue(DEFAULT_QUEUE_BUFFER_SIZE)
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def init_database(self) -> None:
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def vacuum_db(db: SqliteExtDatabase) -> None:
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db.execute_sql("VACUUM;")
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try:
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with open(f"{CONFIG_DIR}/.vacuum", "w") as f:
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f.write(str(datetime.datetime.now().timestamp()))
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except PermissionError:
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logger.error("Unable to write to /config to save DB state")
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# Migrate DB location
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old_db_path = DEFAULT_DB_PATH
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if not os.path.isfile(self.config.database.path) and os.path.isfile(
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old_db_path
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):
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os.rename(old_db_path, self.config.database.path)
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# Migrate DB schema
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migrate_db = SqliteExtDatabase(self.config.database.path)
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# Run migrations
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del logging.getLogger("peewee_migrate").handlers[:]
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router = Router(migrate_db)
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router.run()
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# check if vacuum needs to be run
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if os.path.exists(f"{CONFIG_DIR}/.vacuum"):
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with open(f"{CONFIG_DIR}/.vacuum") as f:
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try:
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timestamp = round(float(f.readline()))
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except Exception:
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timestamp = 0
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if (
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timestamp
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< (
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datetime.datetime.now() - datetime.timedelta(weeks=2)
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).timestamp()
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):
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vacuum_db(migrate_db)
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else:
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vacuum_db(migrate_db)
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migrate_db.close()
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def init_go2rtc(self) -> None:
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for proc in psutil.process_iter(["pid", "name"]):
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if proc.info["name"] == "go2rtc":
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logger.info(f"go2rtc process pid: {proc.info['pid']}")
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self.processes["go2rtc"] = proc.info["pid"]
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def init_recording_manager(self) -> None:
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recording_process = mp.Process(
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target=manage_recordings,
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name="recording_manager",
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args=(self.config, self.recordings_info_queue, self.feature_metrics),
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)
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recording_process.daemon = True
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self.recording_process = recording_process
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recording_process.start()
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self.processes["recording"] = recording_process.pid or 0
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logger.info(f"Recording process started: {recording_process.pid}")
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def bind_database(self) -> None:
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"""Bind db to the main process."""
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# NOTE: all db accessing processes need to be created before the db can be bound to the main process
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self.db = SqliteQueueDatabase(
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self.config.database.path,
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pragmas={
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"auto_vacuum": "FULL", # Does not defragment database
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"cache_size": -512 * 1000, # 512MB of cache,
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"synchronous": "NORMAL", # Safe when using WAL https://www.sqlite.org/pragma.html#pragma_synchronous
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},
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timeout=60,
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)
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models = [Event, Recordings, Timeline]
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self.db.bind(models)
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def init_stats(self) -> None:
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self.stats_tracking = stats_init(
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self.config, self.camera_metrics, self.detectors, self.processes
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)
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def init_external_event_processor(self) -> None:
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self.external_event_processor = ExternalEventProcessor(
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self.config, self.event_queue
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)
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def init_inter_process_communicator(self) -> None:
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self.inter_process_communicator = InterProcessCommunicator(
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self.inter_process_queue
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)
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def init_web_server(self) -> None:
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self.flask_app = create_app(
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self.config,
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self.db,
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self.stats_tracking,
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self.detected_frames_processor,
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self.storage_maintainer,
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self.onvif_controller,
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self.external_event_processor,
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self.plus_api,
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)
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def init_onvif(self) -> None:
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self.onvif_controller = OnvifController(self.config, self.ptz_metrics)
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def init_dispatcher(self) -> None:
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comms: list[Communicator] = []
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if self.config.mqtt.enabled:
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comms.append(MqttClient(self.config))
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comms.append(WebSocketClient(self.config))
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comms.append(self.inter_process_communicator)
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self.dispatcher = Dispatcher(
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self.config,
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self.onvif_controller,
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self.camera_metrics,
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self.feature_metrics,
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self.ptz_metrics,
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comms,
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)
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def start_detectors(self) -> None:
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for name in self.config.cameras.keys():
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self.detection_out_events[name] = mp.Event()
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try:
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largest_frame = max(
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[
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det.model.height * det.model.width * 3
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for (name, det) in self.config.detectors.items()
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]
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)
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shm_in = mp.shared_memory.SharedMemory(
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name=name,
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create=True,
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size=largest_frame,
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)
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except FileExistsError:
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shm_in = mp.shared_memory.SharedMemory(name=name)
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try:
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shm_out = mp.shared_memory.SharedMemory(
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name=f"out-{name}", create=True, size=20 * 6 * 4
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)
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except FileExistsError:
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shm_out = mp.shared_memory.SharedMemory(name=f"out-{name}")
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self.detection_shms.append(shm_in)
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self.detection_shms.append(shm_out)
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for name, detector_config in self.config.detectors.items():
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self.detectors[name] = ObjectDetectProcess(
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name,
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self.detection_queue,
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self.detection_out_events,
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detector_config,
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)
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def start_ptz_autotracker(self) -> None:
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self.ptz_autotracker_thread = PtzAutoTrackerThread(
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self.config,
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self.onvif_controller,
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self.ptz_metrics,
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self.stop_event,
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)
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self.ptz_autotracker_thread.start()
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def start_detected_frames_processor(self) -> None:
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self.detected_frames_processor = TrackedObjectProcessor(
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self.config,
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self.dispatcher,
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self.detected_frames_queue,
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self.event_queue,
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self.event_processed_queue,
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self.video_output_queue,
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self.recordings_info_queue,
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self.ptz_autotracker_thread,
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self.stop_event,
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)
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self.detected_frames_processor.start()
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def start_video_output_processor(self) -> None:
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output_processor = mp.Process(
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target=output_frames,
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name="output_processor",
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args=(
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self.config,
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self.video_output_queue,
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),
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)
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output_processor.daemon = True
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self.output_processor = output_processor
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output_processor.start()
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logger.info(f"Output process started: {output_processor.pid}")
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def start_camera_processors(self) -> None:
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for name, config in self.config.cameras.items():
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if not self.config.cameras[name].enabled:
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logger.info(f"Camera processor not started for disabled camera {name}")
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continue
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camera_process = mp.Process(
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target=track_camera,
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name=f"camera_processor:{name}",
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args=(
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name,
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config,
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self.config.model,
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self.config.model.merged_labelmap,
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self.detection_queue,
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self.detection_out_events[name],
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self.detected_frames_queue,
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self.camera_metrics[name],
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self.ptz_metrics[name],
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),
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)
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camera_process.daemon = True
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self.camera_metrics[name]["process"] = camera_process
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camera_process.start()
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logger.info(f"Camera processor started for {name}: {camera_process.pid}")
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def start_camera_capture_processes(self) -> None:
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for name, config in self.config.cameras.items():
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if not self.config.cameras[name].enabled:
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logger.info(f"Capture process not started for disabled camera {name}")
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continue
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capture_process = mp.Process(
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target=capture_camera,
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name=f"camera_capture:{name}",
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args=(name, config, self.camera_metrics[name]),
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)
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capture_process.daemon = True
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self.camera_metrics[name]["capture_process"] = capture_process
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capture_process.start()
|
|
logger.info(f"Capture process started for {name}: {capture_process.pid}")
|
|
|
|
def start_audio_processors(self) -> None:
|
|
if len([c for c in self.config.cameras.values() if c.audio.enabled]) > 0:
|
|
audio_process = mp.Process(
|
|
target=listen_to_audio,
|
|
name="audio_capture",
|
|
args=(
|
|
self.config,
|
|
self.feature_metrics,
|
|
self.inter_process_communicator,
|
|
),
|
|
)
|
|
audio_process.daemon = True
|
|
audio_process.start()
|
|
self.processes["audioDetector"] = audio_process.pid or 0
|
|
logger.info(f"Audio process started: {audio_process.pid}")
|
|
|
|
def start_timeline_processor(self) -> None:
|
|
self.timeline_processor = TimelineProcessor(
|
|
self.config, self.timeline_queue, self.stop_event
|
|
)
|
|
self.timeline_processor.start()
|
|
|
|
def start_event_processor(self) -> None:
|
|
self.event_processor = EventProcessor(
|
|
self.config,
|
|
self.camera_metrics,
|
|
self.event_queue,
|
|
self.event_processed_queue,
|
|
self.timeline_queue,
|
|
self.stop_event,
|
|
)
|
|
self.event_processor.start()
|
|
|
|
def start_event_cleanup(self) -> None:
|
|
self.event_cleanup = EventCleanup(self.config, self.stop_event)
|
|
self.event_cleanup.start()
|
|
|
|
def start_storage_maintainer(self) -> None:
|
|
self.storage_maintainer = StorageMaintainer(self.config, self.stop_event)
|
|
self.storage_maintainer.start()
|
|
|
|
def start_stats_emitter(self) -> None:
|
|
self.stats_emitter = StatsEmitter(
|
|
self.config,
|
|
self.stats_tracking,
|
|
self.dispatcher,
|
|
self.stop_event,
|
|
)
|
|
self.stats_emitter.start()
|
|
|
|
def start_watchdog(self) -> None:
|
|
self.frigate_watchdog = FrigateWatchdog(self.detectors, self.stop_event)
|
|
self.frigate_watchdog.start()
|
|
|
|
def check_shm(self) -> None:
|
|
available_shm = round(shutil.disk_usage("/dev/shm").total / pow(2, 20), 1)
|
|
min_req_shm = 30
|
|
|
|
for _, camera in self.config.cameras.items():
|
|
min_req_shm += round(
|
|
(camera.detect.width * camera.detect.height * 1.5 * 9 + 270480)
|
|
/ 1048576,
|
|
1,
|
|
)
|
|
|
|
if available_shm < min_req_shm:
|
|
logger.warning(
|
|
f"The current SHM size of {available_shm}MB is too small, recommend increasing it to at least {min_req_shm}MB."
|
|
)
|
|
|
|
def start(self) -> None:
|
|
self.init_logger()
|
|
logger.info(f"Starting Frigate ({VERSION})")
|
|
try:
|
|
self.ensure_dirs()
|
|
try:
|
|
self.init_config()
|
|
except Exception as e:
|
|
print("*************************************************************")
|
|
print("*************************************************************")
|
|
print("*** Your config file is not valid! ***")
|
|
print("*** Please check the docs at ***")
|
|
print("*** https://docs.frigate.video/configuration/index ***")
|
|
print("*************************************************************")
|
|
print("*************************************************************")
|
|
print("*** Config Validation Errors ***")
|
|
print("*************************************************************")
|
|
print(e)
|
|
print(traceback.format_exc())
|
|
print("*************************************************************")
|
|
print("*** End Config Validation Errors ***")
|
|
print("*************************************************************")
|
|
self.log_process.terminate()
|
|
sys.exit(1)
|
|
self.set_environment_vars()
|
|
self.set_log_levels()
|
|
self.init_queues()
|
|
self.init_database()
|
|
self.init_onvif()
|
|
self.init_recording_manager()
|
|
self.init_go2rtc()
|
|
self.bind_database()
|
|
self.init_inter_process_communicator()
|
|
self.init_dispatcher()
|
|
except Exception as e:
|
|
print(e)
|
|
self.log_process.terminate()
|
|
sys.exit(1)
|
|
self.start_detectors()
|
|
self.start_video_output_processor()
|
|
self.start_ptz_autotracker()
|
|
self.start_detected_frames_processor()
|
|
self.start_camera_processors()
|
|
self.start_camera_capture_processes()
|
|
self.start_audio_processors()
|
|
self.start_storage_maintainer()
|
|
self.init_stats()
|
|
self.init_external_event_processor()
|
|
self.init_web_server()
|
|
self.start_timeline_processor()
|
|
self.start_event_processor()
|
|
self.start_event_cleanup()
|
|
self.start_stats_emitter()
|
|
self.start_watchdog()
|
|
self.check_shm()
|
|
|
|
def receiveSignal(signalNumber: int, frame: Optional[FrameType]) -> None:
|
|
self.stop()
|
|
sys.exit()
|
|
|
|
signal.signal(signal.SIGTERM, receiveSignal)
|
|
|
|
try:
|
|
self.flask_app.run(host="127.0.0.1", port=5001, debug=False)
|
|
except KeyboardInterrupt:
|
|
pass
|
|
|
|
self.stop()
|
|
|
|
def stop(self) -> None:
|
|
logger.info("Stopping...")
|
|
self.stop_event.set()
|
|
|
|
for detector in self.detectors.values():
|
|
detector.stop()
|
|
|
|
# Empty the detection queue and set the events for all requests
|
|
while not self.detection_queue.empty():
|
|
connection_id = self.detection_queue.get(timeout=1)
|
|
self.detection_out_events[connection_id].set()
|
|
self.detection_queue.close()
|
|
self.detection_queue.join_thread()
|
|
|
|
self.dispatcher.stop()
|
|
self.detected_frames_processor.join()
|
|
self.ptz_autotracker_thread.join()
|
|
self.event_processor.join()
|
|
self.event_cleanup.join()
|
|
self.stats_emitter.join()
|
|
self.frigate_watchdog.join()
|
|
self.db.stop()
|
|
|
|
while len(self.detection_shms) > 0:
|
|
shm = self.detection_shms.pop()
|
|
shm.close()
|
|
shm.unlink()
|
|
|
|
for queue in [
|
|
self.event_queue,
|
|
self.event_processed_queue,
|
|
self.video_output_queue,
|
|
self.detected_frames_queue,
|
|
self.recordings_info_queue,
|
|
self.log_queue,
|
|
self.inter_process_queue,
|
|
]:
|
|
while not queue.empty():
|
|
queue.get_nowait()
|
|
queue.close()
|
|
queue.join_thread()
|