frigate/frigate/debug_replay.py
Josh Hawkins 814c497bef
Some checks are pending
CI / AMD64 Build (push) Waiting to run
CI / ARM Build (push) Waiting to run
CI / Jetson Jetpack 6 (push) Waiting to run
CI / AMD64 Extra Build (push) Blocked by required conditions
CI / ARM Extra Build (push) Blocked by required conditions
CI / Synaptics Build (push) Blocked by required conditions
CI / Assemble and push default build (push) Blocked by required conditions
Use Job infrastructure for Debug Replay (#23099)
* 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
2026-05-03 14:54:20 -06:00

311 lines
11 KiB
Python

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