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* use ReplayState enum * extract shared ffmpeg progress helper * make start call non-blocking with worker thread * expose replay state on status endpoint and return 202 from start * cancel in-flight ffmpeg when stop is called during preparation * add replay i18n strings for preparing and error states * show status in replay UI * navigate immediately on 202 from debug replay menus and dialog * remove unused * simplify to use Job infrastructure * tests * cleanup and tweaks * fetch schema * update api spec * formatting * fix e2e test * mypy * clean up * formatting * fix * fix test * don't try to show camera image until status reports ready * simplify loading logic * fix race in latest_frame on debug replay shutdown * remove toast when successfully stopping it gets hidden almost immediately
311 lines
11 KiB
Python
311 lines
11 KiB
Python
"""Debug replay camera management for replaying recordings with detection overlays.
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The startup work (ffmpeg concat + camera config publish) lives in
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frigate.jobs.debug_replay. This module owns only session presence
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(active), session metadata, and post-session cleanup.
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"""
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import logging
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import os
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import shutil
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import threading
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from ruamel.yaml import YAML
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from frigate.config import FrigateConfig
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from frigate.config.camera.updater import (
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CameraConfigUpdateEnum,
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CameraConfigUpdatePublisher,
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CameraConfigUpdateTopic,
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)
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from frigate.const import (
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CLIPS_DIR,
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RECORD_DIR,
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REPLAY_CAMERA_PREFIX,
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REPLAY_DIR,
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THUMB_DIR,
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)
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from frigate.jobs.debug_replay import cancel_debug_replay_job, wait_for_runner
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from frigate.util.camera_cleanup import cleanup_camera_db, cleanup_camera_files
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from frigate.util.config import find_config_file
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logger = logging.getLogger(__name__)
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class DebugReplayManager:
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"""Owns the lifecycle pointers for a single debug replay session.
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A session exists from the moment mark_starting is called (synchronously,
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inside the API handler) until clear_session runs (on success cleanup,
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failure, or stop). The active property is the source of truth that the
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status bar consumes — broader than the startup job, which only covers the
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preparing_clip / starting_camera window.
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"""
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def __init__(self) -> None:
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self._lock = threading.Lock()
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self.replay_camera_name: str | None = None
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self.source_camera: str | None = None
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self.clip_path: str | None = None
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self.start_ts: float | None = None
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self.end_ts: float | None = None
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@property
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def active(self) -> bool:
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"""True from mark_starting until clear_session."""
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return self.replay_camera_name is not None
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def mark_starting(
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self,
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source_camera: str,
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replay_camera_name: str,
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start_ts: float,
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end_ts: float,
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) -> None:
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"""Synchronously claim the session before the job runner starts.
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Called inside the API handler so the status bar sees active=True
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immediately, before the worker thread does any ffmpeg work.
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"""
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with self._lock:
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self.replay_camera_name = replay_camera_name
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self.source_camera = source_camera
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self.start_ts = start_ts
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self.end_ts = end_ts
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self.clip_path = None
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def mark_session_ready(self, clip_path: str) -> None:
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"""Record the on-disk clip path after the camera has been published."""
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with self._lock:
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self.clip_path = clip_path
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def clear_session(self) -> None:
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"""Reset session pointers without publishing camera removal.
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Used by the job runner on failure paths. stop() does the camera
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teardown plus this clear in one step.
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"""
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with self._lock:
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self._clear_locked()
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def _clear_locked(self) -> None:
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self.replay_camera_name = None
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self.source_camera = None
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self.clip_path = None
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self.start_ts = None
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self.end_ts = None
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def publish_camera(
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self,
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source_camera: str,
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replay_name: str,
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clip_path: str,
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frigate_config: FrigateConfig,
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config_publisher: CameraConfigUpdatePublisher,
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) -> None:
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"""Build the in-memory replay camera config and publish the add event.
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Called by the job runner during the starting_camera phase.
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"""
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source_config = frigate_config.cameras[source_camera]
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camera_dict = self._build_camera_config_dict(
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source_config, replay_name, clip_path
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)
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config_file = find_config_file()
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yaml_parser = YAML()
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with open(config_file, "r") as f:
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config_data = yaml_parser.load(f)
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if "cameras" not in config_data or config_data["cameras"] is None:
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config_data["cameras"] = {}
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config_data["cameras"][replay_name] = camera_dict
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try:
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new_config = FrigateConfig.parse_object(config_data)
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except Exception as e:
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raise RuntimeError(f"Failed to validate replay camera config: {e}") from e
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frigate_config.cameras[replay_name] = new_config.cameras[replay_name]
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config_publisher.publish_update(
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CameraConfigUpdateTopic(CameraConfigUpdateEnum.add, replay_name),
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new_config.cameras[replay_name],
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)
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def stop(
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self,
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frigate_config: FrigateConfig,
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config_publisher: CameraConfigUpdatePublisher,
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) -> None:
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"""Cancel any in-flight startup job and tear down the active session.
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Safe to call when no session is active (no-op with a warning).
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"""
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cancel_debug_replay_job()
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wait_for_runner(timeout=2.0)
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with self._lock:
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if not self.active:
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logger.warning("No active replay session to stop")
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return
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replay_name = self.replay_camera_name
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# Only publish remove if the camera was actually added to the live
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# config (i.e. the runner reached the starting_camera phase).
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if replay_name is not None and replay_name in frigate_config.cameras:
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config_publisher.publish_update(
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CameraConfigUpdateTopic(CameraConfigUpdateEnum.remove, replay_name),
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frigate_config.cameras[replay_name],
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)
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if replay_name is not None:
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self._cleanup_db(replay_name)
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self._cleanup_files(replay_name)
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self._clear_locked()
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logger.info("Debug replay stopped and cleaned up: %s", replay_name)
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def _build_camera_config_dict(
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self,
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source_config,
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replay_name: str,
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clip_path: str,
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) -> dict:
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"""Build a camera config dictionary for the replay camera."""
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# Extract detect config (exclude computed fields)
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detect_dict = source_config.detect.model_dump(
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exclude={"min_initialized", "max_disappeared", "enabled_in_config"}
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)
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# Extract objects config, using .dict() on filters to convert
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# RuntimeFilterConfig ndarray masks back to string coordinates
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objects_dict = {
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"track": source_config.objects.track,
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"mask": {
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mask_id: (
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mask_cfg.model_dump(
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exclude={"raw_coordinates", "enabled_in_config"}
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)
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if mask_cfg is not None
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else None
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)
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for mask_id, mask_cfg in source_config.objects.mask.items()
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}
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if source_config.objects.mask
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else {},
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"filters": {
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name: filt.dict() if hasattr(filt, "dict") else filt.model_dump()
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for name, filt in source_config.objects.filters.items()
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},
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}
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# Extract zones (exclude_defaults avoids serializing empty defaults
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# like distances=[] that fail validation on re-parse)
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zones_dict = {}
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for zone_name, zone_config in source_config.zones.items():
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zone_dump = zone_config.model_dump(
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exclude={"contour", "color"}, exclude_defaults=True
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)
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zone_dump.setdefault("coordinates", zone_config.coordinates)
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zones_dict[zone_name] = zone_dump
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# Extract motion config (exclude runtime fields)
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motion_dict = {}
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if source_config.motion is not None:
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motion_dict = source_config.motion.model_dump(
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exclude={
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"frame_shape",
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"raw_mask",
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"mask",
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"improved_contrast_enabled",
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"rasterized_mask",
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}
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)
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return {
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"enabled": True,
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"ffmpeg": {
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"inputs": [
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{
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"path": clip_path,
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"roles": ["detect"],
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"input_args": "-re -stream_loop -1 -fflags +genpts",
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}
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],
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"hwaccel_args": [],
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},
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"detect": detect_dict,
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"objects": objects_dict,
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"zones": zones_dict,
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"motion": motion_dict,
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"record": {"enabled": False},
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"snapshots": {"enabled": False},
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"review": {
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"alerts": {"enabled": False},
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"detections": {"enabled": False},
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},
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"birdseye": {"enabled": False},
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"audio": {"enabled": False},
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"lpr": {"enabled": False},
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"face_recognition": {"enabled": False},
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}
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def _cleanup_db(self, camera_name: str) -> None:
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"""Defensively remove any database rows for the replay camera."""
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cleanup_camera_db(camera_name)
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def _cleanup_files(self, camera_name: str) -> None:
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"""Remove filesystem artifacts for the replay camera."""
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cleanup_camera_files(camera_name)
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# Remove replay-specific cache directory
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if os.path.exists(REPLAY_DIR):
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try:
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shutil.rmtree(REPLAY_DIR)
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logger.debug("Removed replay cache directory")
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except Exception as e:
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logger.error("Failed to remove replay cache: %s", e)
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def cleanup_replay_cameras() -> None:
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"""Remove any stale replay camera artifacts on startup.
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Since replay cameras are memory-only and never written to YAML, they
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won't appear in the config after a restart. This function cleans up
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filesystem and database artifacts from any replay that was running when
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the process stopped.
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Must be called AFTER the database is bound.
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"""
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stale_cameras: set[str] = set()
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# Scan filesystem for leftover replay artifacts to derive camera names
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for dir_path in [RECORD_DIR, CLIPS_DIR, THUMB_DIR]:
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if os.path.isdir(dir_path):
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for entry in os.listdir(dir_path):
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if entry.startswith(REPLAY_CAMERA_PREFIX):
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stale_cameras.add(entry)
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if os.path.isdir(REPLAY_DIR):
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for entry in os.listdir(REPLAY_DIR):
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if entry.startswith(REPLAY_CAMERA_PREFIX) and entry.endswith(".mp4"):
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stale_cameras.add(entry.removesuffix(".mp4"))
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if not stale_cameras:
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return
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logger.info("Cleaning up stale replay camera artifacts: %s", list(stale_cameras))
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manager = DebugReplayManager()
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for camera_name in stale_cameras:
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manager._cleanup_db(camera_name)
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manager._cleanup_files(camera_name)
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if os.path.exists(REPLAY_DIR):
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try:
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shutil.rmtree(REPLAY_DIR)
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except Exception as e:
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logger.error("Failed to remove replay cache directory: %s", e)
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